G'MIC(1)                    General Commands Manual                   G'MIC(1)

NAME
       gmic - Perform image processing operations using the G'MIC framework.


HELP
         gmic: GREYC's Magic for Image Computing: command-line interface
               Version 3.3.5
               (https://gmic.eu)

               Copyright (c) Since 2008, David Tschumperle / GREYC / CNRS.
               (https://www.greyc.fr)

         1. Usage
            -----

           gmic [command1 [arg1_1,arg1_2,..]] .. [commandN [argN_1,argN_2,..]]

         'gmic' is the open-source interpreter of the G'MIC language, a
          scripting programming language dedicated to the design of possibly
       complex
          image processing pipelines and operators.
         It can be used to convert, manipulate, filter and visualize image
       datasets made
          of one or several 1D/2D or 3D multi-spectral images.

         This reference documentation describes all the technical aspects of
       the G'MIC
          framework, in its current version 3.3.5.

         As a starting point, you may want to visit our detailed tutorial
       pages, at:
          https://gmic.eu/tutorial/

         2. Overall Context
            ---------------

          * At any time, G'MIC manages one list of numbered (and optionally
       named)
          pixel-based images, entirely stored in computer memory
       (uncompressed).
          * The first image of the list has index '0' and is denoted by
          '[0]'. The second image of the list is denoted by '[1]', the third
          by '[2]' and so on.
          * Negative indices are treated in a periodic way: '[-1]' refers to
       the
          last image of the list, '[-2]' to the penultimate one, etc. Thus, if
       the
          list has 4 images, '[1]' and '[-3]' both designate the second image
          of the list.
          * A named image may be also indicated by '[name]', if 'name' uses
          the character set '[a-zA-Z0-9_]' and does not start with a number.
       Image
          names can be set or reassigned at any moment during the processing
       pipeline
          (see command name for this purpose).
          * G'MIC defines a set of various commands and substitution
       mechanisms to allow
          the design of complex pipelines and operators managing this list of
       images, in
          a very flexible way: You can insert or remove images in the list,
       rearrange
          image order, process images (individually or grouped), merge image
       data
          together, display and output image files, etc.
          * Such a pipeline can define a new custom G'MIC command (stored in a
       user
          command file), and re-used afterwards as a regular command, in a
       larger
          pipeline if necessary.

         3. Image Definition and Terminology
            --------------------------------

          * In G'MIC, each image is modeled as a 1D, 2D, 3D or 4D array of
       scalar
          values, uniformly discretized on a rectangular/parallelepipedic
       domain.
          * The four dimensions of this array are respectively denoted by:
            -  'width', the number of image columns (size along the
          'x-axis').
            -  'height', the number of image rows (size along the 'y-axis').
            -  'depth', the number of image slices (size along the
          'z-axis'). The depth is equal to '1' for usual color or grayscale
          2D images.
            -  'spectrum', the number of image channels (size along the
          'c-axis'). The spectrum is respectively equal to '3' and '4'
          for usual 'RGB' and 'RGBA' color images.

          * There are no hard limitations on the size of the image along each
       dimension.
          For instance, the number of image slices or channels can be of
       arbitrary size
          within the limits of the available memory.
          * The 'width', 'height' and 'depth' of an image are
          considered as spatial dimensions, while the 'spectrum' has a
          multi-spectral meaning. Thus, a 4D image in G'MIC should be most
       often
          regarded as a 3D dataset of multi-spectral voxels. Most of the G'MIC
       commands
          will stick with this idea (e.g. command blur blurs images only along
       the
          spatial 'xyz'-axes).
          * G'MIC stores all the image data as buffers of 'float' values (32
       bits,
          value range '[-3.4E38,+3.4E38]'. It performs all its image
       processing
          operations with floating point numbers. Each image pixel takes then
          32bits/channel (except if double-precision buffers have been enabled
       during the
          compilation of the software, in which case 64bits/channel can be the
       default).
          * Considering 'float'-valued pixels ensure to keep numerical
       precision
          when executing image processing pipelines. For image input/output
       operations,
          you may want to prescribe the image datatype to be different than
       'float'
          (like 'bool', 'char', 'int', etc.). This is possible by
          specifying it as a file option when using I/O commands (see section
          Input/Output Properties to learn more about file options).

         4. Items of a Processing Pipeline
            ------------------------------

          * In G'MIC, an image processing pipeline is described as a sequence
       of
          items separated by the space character. Such items are interpreted
       and
          executed from the left to the right. For instance, the expression:

           filename.jpg blur 3,0 sharpen 10 resize 200%,200% output
       file_out.jpg

         defines a valid pipeline composed of nine G'MIC items.

          * Each G'MIC item is either a command, a list of command arguments,
           a filename or a special input string.
          * Escape characters '' and double quotes '"' can be used to define
       items
          containing spaces or other special characters. For instance, the two
       strings
          'single item' and '"single item"' both define the same single item,
           with a space in it.

         5. Input Data
            ----------

          * If a specified G'MIC item appears to be an existing filename, the
          corresponding image data are loaded and inserted at the end of the
       image list
          (which is equivalent to the use of 'input filename').
          * Special filenames '-' and '-.ext' stand for the standard
          input/output streams, optionally forced to be in a specific 'ext'
       file
          format (e.g. '-.jpg' or '-.png').
          * The following special input strings may be used as G'MIC items to
       create and
          insert new images with prescribed values, at the end of the image
       list:
            -  '[selection]' or '[selection]xN': Insert 1 or N copies of
          already existing images. 'selection' may represent one or several
       images
          (see section Command Items and Selections to learn more about
       selections).
            -  'width[%],_height[%],_depth[%],_spectrum[%],_values[xN]':
       Insert
          one or N images with specified size and values (adding '%' to a
       dimension
          means "percentage of the size along the same axis", taken from the
       last
          image '[-1]'). Any specified dimension can be also written as
          '[image]', and is then set to the size (along the same axis) of the
          existing specified image '[image]'. 'values' can be either a
          sequence of numbers separated by commas ',', or a mathematical
       expression,
           as e.g. in input item '256,256,1,3,[x,y,128]' which creates a
          '256x256' RGB color image with a spatial shading on the red and
       green
          channels. (see section Mathematical Expressions to learn more about
          mathematical expressions).
            -  '(v1,v2,..)[xN]': Insert one or 'N' new images from specified
          prescribed values. Value separator inside parentheses can be ','
       (column
          separator), ';' (row separator), '/' (slice separator) or '^'
          (channel separator). For instance, expression '(1,2,3;4,5,6;7,8,9)'
          creates a 3x3 matrix (scalar image), with values running from 1 to
       9.
            -  '('string'[:delimiter])[xN]': Insert one or N new images from
          specified string, by filling the images with the character codes
       composing the
          string. When specified, 'delimiter' tells about the main orientation
       of
          the image. Delimiter can be 'x' (eq. to ',' which is the default),
          'y' (eq. to ';'), 'z' (eq. to '/') or 'c' (eq. to
          '^'). When specified delimiter is ',', ';', '/' or
          '^', the expression is actually equivalent to
          '({'string'[:delimiter]})[xN]' (see section Substitution Rules for
          more information on the syntax).
            -  '0[xN]': Insert one or N new 'empty' images, containing no
          pixel data. Empty images are used only in rare occasions.

          * Input item 'name=value' declares a new variable 'name', or
          assign a new string value to an existing variable. Variable names
       must use the
          character set '[a-zA-Z0-9_]' and cannot start with a number.
          * A variable definition is always local to the current command
       except :
            -  When it starts by the underscore character '_'. In that case,
       it
          becomes also accessible by any command invoked outside the current
       command
          scope (global variable).
            -  When defined in a subcommand of the current command, a variable
          becomes also accessible in the parent command. A subcommand of a
       command
          'foo' is a command whose name starts with '_foo' (e.g.
          '_foo_sub') and that is called from 'foo'.
          * If a variable name starts with two underscores '__', the global
          variable is also shared among different threads and can be read/set
       by commands
          running in parallel (see command parallel for this purpose).
       Otherwise,
          it remains local to the thread that defined it.
          * Numerical variables can be updated with the use of these special
       operators:
          '+=' (addition), '-=' (subtraction), '*=' (multiplication),
          '/=' (division), '%=' (modulo), '&=' (bitwise and),
          '|=' (bitwise or), '^=' (power), '<<=' and '>>'
          (bitwise left and right shifts). For instance, 'foo=1' 'foo+=3'.
          * Input item 'name.=string' appends specified 'string' at the end
          of variable 'name'.
          * Input item 'name..=string' prepends specified 'string' at the
          beginning of variable 'name'.
          * Multiple variable assignments and updates are allowed, with
       expressions:
          'name1,name2,...,nameN=value' or
       'name1,name2,...,nameN=value1,value2,
          ...,valueN' where assignment operator '=' can be replaced by one of
          the allowed operators (e.g. '+=').
          * Variables usually store numbers or strings. Use command store to
          assign variables from image data (and syntax 'input $variable' to
       bring
          them back on the image list afterwards).

         6. Command Items and Selections
            ----------------------------

          * A G'MIC item that is not a filename nor a special input string
          designates a 'command' most of the time. Generally, commands perform
          image processing operations on one or several available images of
       the list.
          * Reccurent commands have two equivalent names ('regular' and
          'short'). For instance, command names 'resize' and 'r' refer
          to the same image resizing action.
          * A G'MIC command may have mandatory or optional arguments. Command
          arguments must be specified in the next item on the command line.
       Commas ',
          ' are used to separate multiple arguments of a single command, when
       required.
          * The execution of a G'MIC command may be restricted only to a
       subset of
          the image list, by appending '[selection]' to the command name.
       Examples
          of valid syntaxes for 'selection' are:
            -  'command[-2]': Apply command only on the penultimate image
          '[-2]' of the list.
            -  'command[0,1,3]': Apply command only on images '[0]',
          '[1]' and '[3]'.
            -  'command[3-6]': Apply command only on images '[3]' to
          '[6]' (i.e, '[3]', '[4]', '[5]' and '[6]').
            -  'command[50%-100%]': Apply command only on the second half of
       the
          image list.
            -  'command[0,-4--1]': Apply command only on the first image and
       the
          last four images.
            -  'command[0-9:3]': Apply command only on images '[0]' to
          '[9]', with a step of 3 (i.e. on images '[0]', '[3]',
          '[6]' and '[9]').
            -  'command[0--1:2]': Apply command only on images of the list
       with
          even indices.
            -  'command[0,2-4,50%--1]': Apply command on images '[0]',
          '[2]', '[3]', '[4]' and on the second half of the image list.
            -  'command[^0,1]': Apply command on all images except the first
       two.
            -  'command[name1,name2]': Apply command on named images 'name1'
          and 'name2'.

          * Indices in selections are always sorted in increasing order, and
       duplicate
          indices are discarded. For instance, selections '[3-1,1-3]' and
       '[1,1,
          1,3,2]' are both equivalent to '[1-3]'. If you want to repeat a
       single
          command multiple times on an image, use a 'repeat..done' loop
       instead.
          Inverting the order of images for a command is achieved by
       explicitly inverting
          the order of the images in the list, with command
       'reverse[selection]'.
          * Command selections '[-1]', '[-2]' and '[-3]' are so often
          used they have their own shortcuts, respectively '.', '..' and
          '...'. For instance, command 'blur..' is equivalent to
          'blur[-2]'. These shortcuts work also when specifying command
       arguments.
          * G'MIC commands invoked without '[selection]' are applied on all
       images
          of the list, i.e. the default selection is '[0--1]' (except for
       command
          input whose default selection is '[-1]'').
          * Prepending a single hyphen '-' to a G'MIC command is allowed. This
       may
          be useful to recognize command items more easily in a one-liner
       pipeline
          (typically invoked from a shell).
          * A G'MIC command prepended with a plus sign '+' does not act
          in-place but inserts its result as one or several new images at the
       end
          of the image list.
          * There are two different types of commands that can be run by the
       G'MIC
          interpreter:
            -  Built-in commands are the hard-coded functionalities in the
          interpreter core. They are thus compiled as binary code and run
       fast, most of
          the time. Omitting an argument when invoking a built-in command is
       not
          permitted, except if all following arguments are also omitted. For
       instance,
          invoking 'plasma 10,,5' is invalid but 'plasma 10' is correct.
            -  Custom commands, are defined as G'MIC pipelines of built-in or
          other custom commands. They are parsed by the G'MIC interpreter, and
       thus run a
          bit slower than built-in commands. Omitting arguments when invoking
       a custom
          command is permitted. For instance, expressions 'flower ,,,100,,2'
       or
          'flower ,' are correct.

          * Most of the existing commands in G'MIC are actually defined as
       custom
          commands.
          * A user can easily add its own custom commands to the G'MIC
       interpreter (see
          section  Adding Custom Commands for more details). New built-in
       commands
          cannot be added (unless you modify the G'MIC interpreter source code
       and
          recompile it).

         7. Input/Output Properties
            -----------------------

          * G'MIC is able to read/write most of the classical image file
       formats,
          including:
            -  2D grayscale/color files: '.png', '.jpeg', '.gif',
          '.pnm', '.tif', '.bmp', ...
            -  3D volumetric files: '.dcm', '.hdr', '.nii',
          '.cube', '.pan', '.inr', '.pnk', ...
            -  Video files: '.mpeg', '.avi', '.mp4', '.mov',
          '.ogg', '.flv', ...
            -  Generic text or binary data files: '.gmz', '.cimg',
          '.cimgz', 'flo', 'ggr', 'gpl', '.dlm',
          '.asc', '.pfm', '.raw', '.txt', '.h'.
            -  3D mesh files: '.off', '.obj'.

          * When dealing with color images, G'MIC generally reads, writes and
       displays
          data using the usual sRGB color space.
          * When loading a '.png' and '.tiff' file, the bit-depth of the
          input image(s) is returned to the status.
          * G'MIC is able to manage 3D mesh objects that may be read from
       files or
          generated by G'MIC commands. A 3D object is stored as a one-column
       scalar image
          containing the object data, in the following order: { magic_number;
       sizes;
          vertices; primitives; colors; opacities }. These 3D representations
       can be
          then processed as regular images (see command split3d for accessing
       each
          of these 3D object data separately).
          * Be aware that usual file formats may be sometimes not adapted to
       store all
          the available image data, since G'MIC uses float-valued image
       buffers. For
          instance, saving an image that was initially loaded as a
       16bits/channel image,
          as a '.jpg' file will result in a loss of information. Use the
          G'MIC-specific file extension '.gmz' to ensure that all data
       precision is
          preserved when saving images.
          * Sometimes, file options may/must be set for file formats:
            -  Video files: Only sub-frames of an image sequence may be
       loaded,
          using the input expression 'filename.ext,[first_frame[,last_frame[,
          step]]]'. Set 'last_frame==-1' to tell it must be the last frame of
          the video. Set 'step' to '0' to force an opened video file to be
          opened/closed. Output framerate and codec can be also set by using
       the output
          expression 'filename.avi,_fps,_codec,_keep_open' where 'keep_open'
          can be { 0 | 1 }. 'codec' is a 4-char string (see
          http://www.fourcc.org/codecs.php ) or '0' for the default codec.
          'keep_open' tells if the output video file must be kept open for
          appending new frames afterwards.
            -  '.cimg[z]' files: Only crops and sub-images of .cimg files
          can be loaded, using the input expressions 'filename.cimg,N0,N1',
          'filename.cimg,N0,N1,x0,x1', 'filename.cimg,N0,N1,x0,y0,x1,y1',
          'filename.cimg,N0,N1,x0,y0,z0,x1,y1,z1' or
       'filename.cimg,N0,N1,x0,y0,
          z0,c0,x1,y1,z1,c1'. Specifying '-1' for one coordinates stands for
       the
          maximum possible value. Output expression
       'filename.cimg[z][,datatype]'
          can be used to force the output pixel type. 'datatype' can be { auto
       |
          bool | uint8 | int8 | uint16 | int16 | uint32 | int32 | uint64 |
       int64 |
          float32 | float64 }.
            -  '.raw' binary files: Image dimensions and input pixel type
          may be specified when loading '.raw' files with input expression
          'filename.raw[,datatype][,width][,height[,depth[,dim[,offset]]]]]'.
       If no
          dimensions are specified, the resulting image is a one-column vector
       with
          maximum possible height. Pixel type can also be specified with the
       output
          expression 'filename.raw[,datatype]'. 'datatype' can be the same as
          for '.cimg[z]' files.
            -  '.yuv' files: Image dimensions must be specified when loading,
           and only sub-frames of an image sequence may be loaded, using the
       input
          expression
       'filename.yuv,width,height[,chroma_subsampling[,first_frame[,
          last_frame[,step]]]'. 'chroma_subsampling' can be { 420 | 422 | 444
          }. When saving, chroma subsampling mode can be specified with output
          expression 'filename.yuv[,chroma_subsampling]'.
            -  '.tiff' files: Only sub-images of multi-pages tiff files can
          be loaded, using the input expression
       'filename.tif,_first_frame,_last_frame,
          _step'. Output expression 'filename.tiff,_datatype,_compression,
          _force_multipage,_use_bigtiff' can be used to specify the output
       pixel type,
          as well as the compression method. 'datatype' can be the same as for
          '.cimg[z]' files. 'compression' can be  { none (default) | lzw |
          jpeg }. 'force_multipage' can be { 0:no (default) | 1:yes }.
          'use_bigtiff' can be { 0:no | 1:yes (default) }.
            -  '.pdf' files: When loading a file, the rendering resolution
          can be specified using the input expression
       'filename.pdf,resolution',
          where 'resolution' is an unsigned integer value.
            -  '.gif' files: Animated gif files can be saved, using the
          input expression 'filename.gif,fps>0,nb_loops'. Specify
          'nb_loops=0' to get an infinite number of animation loops (this is
       the
          default behavior).
            -  '.jpeg' files: The output quality may be specified (in %),
          using the output expression 'filename.jpg,30' (here, to get a 30%
       quality
          output). '100' is the default.
            -  '.mnc' files: The output header can set from another file,
          using the output expression 'filename.mnc,header_template.mnc'.
            -  '.pan', '.cpp', '.hpp', '.c' and '.h'
          files: The output datatype can be selected with output expression
          'filename[,datatype]'. 'datatype' can be the same as for
          '.cimg[z]' files.
            -  '.gmic' files: These filenames are assumed to be G'MIC custom
          commands files. Loading such a file will add the commands it defines
       to the
          interpreter. Debug information can be enabled/disabled by the input
       expression
          'filename.gmic[,add_debug_info]' where 'debug_info' can be {
          0:false | 1:true }.
            -  Inserting 'ext:' on the beginning of a filename (e.g.
          'jpg:filename') forces G'MIC to read/write the file as it would have
       been
          done if it had the specified extension '.ext'.

          * Some input/output formats and options may not be supported,
       depending on the
          configuration flags that have been set during the build of the G'MIC
       software.

         8. Substitution Rules
            ------------------

          * G'MIC items containing '$' or '{}' are substituted before
          being interpreted. Use these substituting expressions to access
       various data
          from the interpreter environment.
          * '$name' and '${name}' are both substituted by the value of the
          specified named variable (set previously by the item 'name=value').
       If
          this variable has not been already set, the expression is
       substituted by the
          highest positive index of the named image '[name]'. If no image has
       this
          name, the expression is substituted by the value of the OS
       environment variable
          with same name (it may be thus an empty string if it is not
       defined).
          * The following reserved variables are predefined by the G'MIC
       interpreter:
            -  '$!': The current number of images in the list.
            -  '$>' and '$<': The increasing/decreasing index of the latest
          (currently running) 'repeat...done' loop. '$>' goes from '0'
          (first loop iteration) to 'nb_iterations - 1' (last iteration).
          '$<' does the opposite.
            -  '$/': The current call stack. Stack items are separated by
       slashes
          '/'.
            -  '$|': The current value (expressed in seconds) of a millisecond
          precision timer.
            -  '$^': The current verbosity level.
            -  '$_cpus': The number of computation cores available on your
       machine.
            -  '$_flags': The list of enabled flags when G'MIC interpreter has
          been compiled.
            -  '$_host': A string telling about the host running the G'MIC
          interpreter (e.g. 'cli' or 'gimp').
            -  '$_os': A string describing the running operating system.
            -  '$_path_rc': The path to the G'MIC folder used to store
          configuration files (its value is OS-dependent).
            -  '$_path_user': The path to the G'MIC user file '.gmic' or
          'user.gmic' (its value is OS-dependent).
            -  '$_path_commands': A list of all imported command files (stored
       as
          an image list).
            -  '$_pid': The current process identifier, as an integer.
            -  '$_pixeltype': The type of image pixels (default: 'float32').
            -  '$_prerelease': For pre-releases, the date of the pre-release
       as
          'yymmdd'. For stable releases, this variable is set to '0'.
            -  '$_version': A 3-digits number telling about the current
       version of
          the G'MIC interpreter  (e.g. '335').
            -  '$_vt100': Set to '1' if colored text output is allowed on
          the console. Otherwise, set to '0'.

          * '$$name' and '$${name}' are both substituted by the G'MIC script
          code of the specified named 'custom command', or by an empty string
       if no
          custom command with specified name exists.
          * '${"-pipeline"}' is substituted by the status value after the
          execution of the specified G'MIC pipeline (see command status).
          Expression '${}' thus stands for the current status value.
          * '{``string}' (starting with two backquotes) is substituted by a
          double-quoted version of the specified string.
          * '{/string}' is substituted by the escaped version of the specified
          string.
          * '{'string'[:delimiter]}' (between single quotes) is substituted by
       the
          sequence of character codes that composes the specified string,
       separated by
          specified delimiter. Possible delimiters are ',' (default), ';',
          '/', '^' or ' '. For instance, item '{'foo'}' is substituted
          by '102,111,111' and '{'foo':;}' by '102;111;111'.
          * '{image,feature[:delimiter]}' is substituted by a specific feature
       of
          the image '[image]'. 'image' can be either an image number or an
          image name. It can be also eluded, in which case, the last image
       '[-1]'
          of the list is considered for the requested feature. Specified
       'feature'
          can be one of:
            -  'b': The image basename (i.e. filename without the folder path
       nor
          extension).
            -  'f': The image folder name.
            -  'n': The image name or filename (if the image has been read
       from a
          file).
            -  't': The text string from the image values regarded as
       character
          codes.
            -  'x': The image extension (i.e the characters after the last
          '.' in the image name).
            -  '^': The sequence of all image values, separated by commas ',
          '.
            -  '@subset': The sequence of image values corresponding to the
          specified subset, and separated by commas ','.
            -  Any other 'feature' is considered as a mathematical
          expression associated to the image '[image]' and is substituted by
       the
          result of its evaluation (float value). For instance, expression
       '{0,
          w+h}' is substituted by the sum of the width and height of the first
       image
          (see section Mathematical Expressions for more details). If a
          mathematical expression starts with an underscore '_', the resulting
          value is truncated to a readable format. For instance, item '{_pi}'
       is
          substituted by '3.14159' (while '{pi}' is substituted by
          '3.141592653589793').
            -  A 'feature' delimited by backquotes is replaced by a string
       whose
          character codes correspond to the list of values resulting from the
       evaluation
          of the specified mathematical expression. For instance, item
       '{`[102,111,
          111]`}' is substituted by 'foo' and item '{`vector8(65)`}' by
          'AAAAAAAA'.

          * '{*}' is substituted by the visibility state of the instant
       display
          window '#0' (can be { 0:closed | 1:visible }.
          * '{*[index],feature1,...,featureN[:delimiter]}' is substituted by a
          specific set of features of the instant display window '#0' (or
          '#index', if specified). Requested 'features' can be:
            -  'u': screen width (actually independent on the window size).
            -  'v': screen height (actually independent on the window size).
            -  'uv': screen width*screen height.
            -  'd': window width (i.e. width of the window widget).
            -  'e': window height (i.e. height of the window widget).
            -  'de': window width*window height.
            -  'w': display width (i.e. width of the display area managed by
       the
          window).
            -  'h': display height (i.e. height of the display area managed by
       the
          window).
            -  'wh': display width*display height.
            -  'i': X-coordinate of the display window.
            -  'j': Y-coordinate of the display window.
            -  'f': current fullscreen state of the instant display.
            -  'n': current normalization type of the instant display.
            -  't': window title of the instant display.
            -  'x': X-coordinate of the mouse position (or -1, if outside the
          display area).
            -  'y': Y-coordinate of the mouse position (or -1, if outside the
          display area).
            -  'b': state of the mouse buttons { 1:left-but. | 2:right-but. |
          4:middle-but. }.
            -  'o': state of the mouse wheel.
            -  'k': decimal code of the pressed key if any, 0 otherwise.
            -  'c': boolean (0 or 1) telling if the instant display has been
          closed recently.
            -  'r': boolean telling if the instant display has been resized
          recently.
            -  'm': boolean telling if the instant display has been moved
       recently.
            -  Any other 'feature' stands for a keycode name (in capital
       letters),
          and is substituted by a boolean describing the current key state {
       0:pressed
          | 1:released }.
            -  You can also prepend a hyphen '-' to a 'feature' (that
          supports it) to flush the corresponding event immediately after
       reading its
          state (works for keys, mouse and window events).

          * Item substitution is never performed in items between double
       quotes.
          One must break the quotes to enable substitution if needed, as in
       '"3+8 kg =
          "{3+8}" kg"'. Using double quotes is then a convenient way to
       disable the
          substitutions mechanism in items, when necessary.
          * One can also disable the substitution mechanism on items outside
       double
          quotes, by escaping the '{', '}' or '$' characters, as in
          '3+4 doesn't evaluate'.

         9. Mathematical Expressions
            ------------------------

          * G'MIC has an embedded mathematical parser, used to evaluate
          (possibly complex) math expressions specified inside braces '{}', or
          formulas in commands that may take one as an argument (e.g. fill or
          eval).
          * When the context allows it, a formula is evaluated for each pixel
       of
          the selected images (e.g. fill or eval).
          * A math expression may return or take as an argument a scalar or a
          vector-valued result (with a fixed number of components).
         The mathematical parser understands the following set of functions,
       operators
          and variables:

         ## Usual math operators:

         '||' (logical or), '&&' (logical and), '|' (bitwise or),
          '&' (bitwise and), '!=', '==', '<=', '>=',
          '<', '>', '<<' (left bitwise shift), '>>' (right
          bitwise shift), '-', '+', '*', '/', '%' (modulo),
          '^' (power), '!' (logical not), '~' (bitwise not), '++',
           '--', '+=', '-=', '*=', '/=', '%=',
          '&=', '|=', '^=', '>>', '<<=' (in-place
          operators).

         ## Usual math functions:

         'abs()', 'acos()', 'acosh()', 'arg()', 'arg0()',
          'argkth()', 'argmax()', 'argmaxabs()', 'argmin()',
          'argminabs()', 'asin()', 'asinh()', 'atan()',
          'atan2()', 'atanh()', 'avg()', 'bool()', 'cbrt()',
           'ceil()', 'cos()', 'cosh()', 'cut()',
          'deg2rad()', 'erf()', 'erfinv()', 'exp()',
          'fact()', 'fibo()', 'floor()', 'gamma()',
          'gauss()', 'gcd()', 'hypot()', 'int()',
          'isconst()', 'isnan()', 'isnum()', 'isinf()',
          'isint()', 'isbool()', 'isexpr()', 'isfile()',
          'isdir()', 'isin()', 'kth()', 'lcm()', 'log()',
          'log2()', 'log10()', 'max()', 'maxabs()', 'med()',
           'min()', 'minabs()', 'narg()', 'prod()',
          'rad2deg()', 'rol()' (left bit rotation), 'ror()' (right bit
          rotation), 'round()', 'sign()', 'sin()', 'sinc()',
          'sinh()', 'sqrt()', 'std()', 'srand(_seed)',
          'sum()', 'tan()', 'tanh()', 'var()', 'xor()'.

          * 'cov(A,B,_avgA,_avgB)' estimates the covariance between vectors
          'A' and 'B' (estimated averages of these vectors may be specified
          as arguments).
          * 'mse(A,B)' returns the mean-squared error between vectors 'A'
          and 'B'.
          * 'atan2(y,x)' is the version of 'atan()' with two arguments
          'y' and 'x' (as in C/C++).
          * 'perm(k,n,_with_order)' computes the number of permutations of
          'k' objects from a set of 'n' objects.
          * 'gauss(x,_sigma,_is_normalized)' returns
          'exp(-x^2/(2*s^2))/(is_normalized?sqrt(2*pi*sigma^2):1)'.
          * 'cut(value,min,max)' returns 'value' if it is in range '[min,
          max]', or 'min' or 'max' otherwise.
          * 'narg(a_1,...,a_N)' returns the number of specified arguments
       (here,
          'N').
          * 'arg(i,a_1,..,a_N)' returns the 'i'-th argument 'a_i'.
          * 'isnum()', 'isnan()', 'isinf()', 'isint()',
          'isbool()' test the type of the given number or expression, and
       return
          '0' (false) or '1' (true).
          * 'isfile('path')' (resp. 'isdir('path')') returns '0'
          (false) or '1' (true) whether its string argument is a path to an
          existing file (resp. to a directory) or not.
          * 'ispercentage(arg)' returns '1' (true) or '0' (false)
          whether 'arg' ends with a '%' or not.
          * 'isvarname('str')' returns '0' (false) or '1' (true)
          whether its string argument would be a valid to name a variable or
       not.
          * 'isin(v,a_1,...,a_n)' returns '0' (false) or '1' (true)
          whether the first argument 'v' appears in the set of other argument
          'a_i'.
          * 'isint(x,_xmin,_xmax)' returns '1' (true), if 'x' is an
          integer in range '[xmin,xmax]', otherwise '0' (false).
          * 'inrange(value,m,M,include_m,include_M)' returns '0' (false) or
          '1' (true) whether the specified value lies in range '[m,M]' or not
          ('include_m' and 'includeM' tells how boundaries 'm' and
          'M' are considered).
          * 'argkth()', 'argmin()', 'argmax()', 'argminabs()',
          'argmaxabs()'', 'avg()', 'kth()', 'min()',
          'max()', 'minabs()', 'maxabs()', 'med()',
          'prod()', 'std()', 'sum()' and 'var()' can be called
          with an arbitrary number of scalar/vector arguments.
          * 'vargkth()', 'vargmin()', 'vargmax()',
          'vargminabs()', 'vargmaxabs()', 'vavg()', 'vkth()',
          'vmin()', 'vmax()', 'vminabs()', 'vmaxabs()',
          'vmed()', 'vprod()', 'vstd()', 'vsum()' and
          'vvar()' are the versions of the previous function with vector-
       valued
          arguments.
          * 'round(value,rounding_value,direction)' returns a rounded value.
          'direction' can be { -1:to-lowest | 0:to-nearest | 1:to-highest }.
          * 'lerp(a,b,t)' returns 'a*(1-t)+b*t'.
          * 'swap(a,b)' swaps the values of the given arguments.

         ## Predefined variable names:

         Variable names below are pre-defined. They can be overridden though.
          * 'l': length of the associated list of images.
          * 'k': index of the associated image, in '[0,l-1]'.
          * 'w': width of the associated image, if any ('0' otherwise).
          * 'h': height of the associated image, if any ('0' otherwise).
          * 'd': depth of the associated image, if any ('0' otherwise).
          * 's': spectrum of the associated image, if any ('0' otherwise).
          * 'r': shared state of the associated image, if any ('0'
          otherwise).
          * 'wh': shortcut for 'width*height'.
          * 'whd': shortcut for 'width*height*depth'.
          * 'whds': shortcut for 'width*height*depth*spectrum' (i.e. number
          of image values).
          * 'im', 'iM', 'ia', 'iv', 'id', 'is',
          'ip', 'ic', 'in': Respectively the minimum, maximum, average,
          variance, standard deviation, sum, product, median value and L2-norm
       of the
          associated image, if any ('0' otherwise).
          * 'xm', 'ym', 'zm', 'cm': The pixel coordinates of the
          minimum value in the associated image, if any ('0' otherwise).
          * 'xM', 'yM', 'zM', 'cM': The pixel coordinates of the
          maximum value in the associated image, if any ('0' otherwise).
          * All these variables are considered as constant values by the math
          parser (for optimization purposes) which is indeed the case most of
       the time.
          Anyway, this might not be the case, if function 'resize(#ind,..)' is
       used
          in the math expression. If so, it is safer to invoke functions
       'l()',
          'w(_#ind)', 'h(_#ind)', ... 's(_#ind)' and 'in(_#ind)'
          instead of the corresponding named variables.
          * 'i': current processed pixel value (i.e. value located at '(x,y,z,
          c)') in the associated image, if any ('0' otherwise).
          * 'iN': N-th channel value of current processed pixel (i.e. value
          located at '(x,y,z,N)' in the associated image, if any ('0'
          otherwise). 'N' must be an integer in range '[0,9]'.
          * 'R', 'G', 'B' and 'A' are equivalent to 'i0',
          'i1', 'i2' and 'i3' respectively.
          * 'I': current vector-valued processed pixel in the associated
       image, if
          any ('0' otherwise). The number of vector components is equal to the
          number of image channels (e.g. 'I' = '[ R,G,B ]' for a 'RGB'
          image).
          * You may add '#ind' to any of the variable name above to retrieve
       the
          information for any numbered image '[ind]' of the list (when this
       makes
          sense). For instance 'ia#0' denotes the average value of the first
       image
          of the list).
          * 'x': current processed column of the associated image, if any
          ('0' otherwise).
          * 'y': current processed row of the associated image, if any ('0'
          otherwise).
          * 'z': current processed slice of the associated image, if any
          ('0' otherwise).
          * 'c': current processed channel of the associated image, if any
          ('0' otherwise).
          * 't': thread id when an expression is evaluated with multiple
       threads
          ('0' means master thread).
          * 'n': maximum number of threads when expression is evaluated in
          parallel (so that 't' goes from '0' to 'n-1').
          * 'e': value of e, i.e. '2.71828...'.
          * 'pi': value of pi, i.e. '3.1415926...'.
          * 'eps': value of machine epsilon, that is the difference between
       1.0
          and the next value representable by a double.
          * 'u': a random value between '[0,1]', following a uniform
          distribution.
          * 'g': a random value, following a gaussian distribution of variance
       1
          (roughly in '[-6,6]').
          * 'interpolation': value of the default interpolation mode used when
          reading pixel values with the pixel access operators (i.e. when the
          interpolation argument is not explicitly specified, see below for
       more details
          on pixel access operators). Its initial default value is '0'.
          * 'boundary': value of the default boundary conditions used when
       reading
          pixel values with the pixel access operators (i.e. when the boundary
       condition
          argument is not explicitly specified, see below for more details on
       pixel
          access operators). Its initial default value is '0'.
          * The last image of the list is always associated to the evaluations
       of
          'expressions', e.g. G'MIC sequence

           256,128 fill {w}

          will create a 256x128 image filled with value 256.

         ## Vector-valued functions and operators:

         The math evaluator is able to work with vector-valued elements. A
       math function
          applied on a vector-valued argument usually returns a vector with
       same
          dimension, where each element of the input vector has been passed to
       the
          specified function (e.g. 'abs([-1,2,-3])' returns '[1,2,3]').

         There are specific functions and operators to define or compute
       vector-valued
          elements though :
          * '[a0,a1,...,aN-1]' defines a 'N'-dimensional vector with scalar
          coefficients 'ak'.
          * 'vectorN(a0,a1,,...,aN-1)' does the same, with the 'ak' being
          repeated periodically if only a few are specified.
          * 'vector(#N,a0,a1,,...,aN-1)' does the same, and can be used for
       any
          constant expression 'N'.
          * In previous expressions, the 'ak' can be vectors themselves, to be
          concatenated into a single vector.
          * The scalar element 'ak' of a vector 'X' is retrieved by
          'X[k]'.
          * The sub-vector '[X[p],X[p+s]...X[p+s*(q-1)]]' (of size 'q') of a
          vector 'X' is retrieved by 'X[p,q,s]'.
          * Equality/inequality comparisons between two vectors is done with
       operators
          '==' and '!='.
          * Some vector-specific functions can be used on vector values:
       'cross(X,
          Y)' (cross product), 'dot(X,Y)' (dot product), 'size(X)' (vector
          dimension), 'sort(X,_is_increasing,_nb_elts,_size_elt)' (sorted
       values),
          'reverse(A)' (reverse order of components), 'map(X,P,_nb_channelsX,
          _nb_channelsP,_boundary_conditions)', 'shift(A,_length,
          _boundary_conditions)' and 'same(A,B,_nb_vals,_is_case_sensitive)'
          (vector equality test).
          * Function 'normP(u1,...,un)' computes the LP-norm of the specified
          vector ('P' being a constant or 'inf', as in e.g. 'norm1()').
          * Function 'normp(V,_p)' computes the Lp-norm of the specified
       vector
          'V'. Here, 'p' can be variable. Default value for 'p' is 2.
          * Function 'unitnorm(V,_p)' returns a normalized version
          'V/normp(V)' of specified vector 'V'. Default value for 'p'
          is 2.
          * Function 'resize(A,size,_interpolation,_boundary_conditions)'
       returns
          a resized version of a vector 'A' with specified interpolation mode.
          'interpolation' can be { -1:none (memory content) | 0:none |
       1:nearest
          | 2:average | 3:linear | 4:grid | 5:bicubic | 6:lanczos }, and
          'boundary_conditions' can be { 0:dirichlet | 1:neumann | 2:periodic
       |
          3:mirror }.
          * Function 'find(A,B,_starting_index,_search_step)' returns the
       index
          where sub-vector 'B' appears in vector 'A', (or '-1' if
          'B' is not contained in 'A'). Argument 'A' can be also
          replaced by an image index '#ind'.
          * Specifying a vector-valued math expression as an argument of a
       command that
          operates on image values (e.g. 'fill') modifies the whole spectrum
       range
          of the processed image(s), for each spatial coordinates '(x,y,z)'.
       The
          command does not loop over the 'c'-axis in this case.

         ## Complex-valued functions:

         A '2'-dimensional vector may be seen as a complex number and used in
          those particular functions/operators: '**' (complex multiplication),
          '//' (complex division), '^^' (complex exponentiation), '**='
          (complex self-multiplication), '//=' (complex self-division), '^^='
          (complex self-exponentiation), 'cabs()' (complex modulus), 'carg()'
          (complex argument), 'cconj()' (complex conjugate), 'cexp()'
          (complex exponential), 'clog()' (complex logarithm),  'ccos()'
          (complex cosine), 'csin()' (complex sine), 'csqr()' (complex
          square), 'csqrt()' (complex square root), 'ctan()' (complex
          tangent), 'ccosh()' (complex hyperpolic cosine), 'csinh()' (complex
          hyperbolic sine) and 'ctanh()' (complex hyperbolic tangent).

         ## Matrix-valued functions:

         A 'MN'-dimensional vector may be seen as a 'M' x 'N' matrix
          and used in those particular functions/operators: '*' (matrix-vector
          multiplication), 'det(A)' (determinant), 'diag(V)' (diagonal matrix
          from a vector), 'eig(A)' (eigenvalues/eigenvectors), 'eye(n)' (n x
          n identity matrix), 'invert(A,_nb_colsA,_use_LU,_lambda)' (matrix
          inverse), 'mul(A,B,_nb_colsB)' (matrix-matrix multiplication),
       'rot(u,
          v,w,angle)' (3D rotation matrix), 'rot(angle)' (2D rotation matrix),
          'solve(A,B,_nb_colsB,_use_LU)' (solver of linear system A.X = B),
          'svd(A,_nb_colsA)' (singular value decomposition), 'trace(A)'
          (matrix trace) and 'transpose(A,nb_colsA)' (matrix transpose).
       Argument
          'nb_colsB' may be omitted if it is equal to '1'.

         ## Image-valued functions:

         Some functions takes vector-valued arguments that represent image
       data :
          * Function 'expr(formula,_w,_h,_d,_s)' outputs a vector of size
          'w*h*d*s' with values generated from the specified formula, as if
       one
          were filling an image with dimensions '(w,h,d,s)'.
          * Function 'resize(A,wA,hA,dA,sA,nwA,_nhA,_ndA,_nsA,_interpolation,
          _boundary_conditions,_ax,_ay,_az,_ac)' is an extended version of the
          'resize()' function. It allows to resize the vector 'A', seen as an
          image of size '(ow,oh,od,os)' as a new image of size '(nw,nh,nd,
          ns)', with specified resizing options.
          * Function 'warp(A,wA,hA,dA,sA,B,wB,hB,dB,sB,_mode,_interpolation,
          _boundary_conditions)' returns the warped version of the image 'A'
       (of
          size '(wA,hA,dA,sA)', viewed as a vector of size 'wA*hA*dA*sA') by
          the warping field 'B' (of size '(wB,hB,dB,sB)'). The resulting
          image has size '(wB,hB,dB,sA)'. This is the math evaluator analog to
          command warp.
          * Function 'index(A,P,nb_channelsP,_dithering,_map_colors)' returns
       the
          indexed version of the image 'A' by the colormap 'P'. This is the
          math evaluator analog to command index.
          * Function 'permute(A,wA,hA,dA,sA,permutation_string)' returns a
          permuted version of the image 'A' (of size '(wA,hA,dA,sA)', viewed
          as a vector of size 'wA*hA*dA*sA'). This is the math evaluator
       analog to
          command permute.
          * Function 'mirror(A,wA,hA,dA,sA,axes_string)' returns a mirrored
          version of the image 'A' (of size '(wA,hA,dA,sA)', viewed as a
          vector of size 'wA*hA*dA*sA'). This is the math evaluator analog to
          command mirror.
          * Function 'cumulate(A,wA,hA,dA,sA,_axes_string)' returns a
       cumulated
          version of the image 'A' (of size '(wA,hA,dA,sA)', viewed as a
          vector of size 'wA*hA*dA*sA'). This is the math evaluator analog to
          command cumulate.
          * Function 'histogram(A,nb_levels,_min_value,_max_value)' returns
       the
          histogram of the vector 'A'. This is the math evaluator analog to
       command
          histogram.
          * Function 'equalize(A,nb_levels,_min_value,_max_value)' returns the
          equalized version of the vector 'A'. This is the math evaluator
       analog to
          command equalize.
          * Function 'normalize(A,_min_value,_max_value)' returns the
       normalized
          version of the vector 'A'. This is the math evaluator analog to
       command
          normalize.
          * 'mproj(S,nb_colsS,D,nb_colsD,method,max_iter,max_residual)'
       projects a
          matrix 'S' onto a dictionary (matrix) 'D'. This is the math
          evaluator analog to command mproj.
          * Function 'noise(A,amplitude,_noise_type)' returns the noisy
       version of
          the vector 'A'. This is the math evaluator analog to command noise.
          * Function 'rand(#size,_min_value,_max_value,_pdf,_precision)'
       returns
          the a vector of 'size' random values. This is the math evaluator
       analog
          to command rand.

         ## String manipulation:

         Character strings are defined as vectors objects and can be then
       managed as is.
          Dedicated functions and initializers to manage strings exist:
          * '['string']' and ''string'' define a vector whose values are the
          character codes of the specified 'character string' (e.g. ''foo''
          is equal to '[ 102,111,111 ]').
          * '_'character'' returns the (scalar) byte code of the specified
          character (e.g. '_'A'' is equal to '65').
          * A special case happens for empty strings: Values of both
       expressions
          '['']' and '''' are '0'.
          * Functions 'lowercase()' and 'uppercase()' return string with all
          string characters lowercased or uppercased.
          * Function 's2v(str,_starting_index,_is_strict)' parses specified
       string
          'str' and returns the value contained in it.
          * Function 'v2s(expr,_nb_digits,_siz)' returns a vector of size
          'siz' which contains the character representation of values
       described by
          expression 'expr'. 'nb_digits' can be { <-1:0-padding of
          integers | -1:auto-reduced | 0:all | >0:max number of digits }.
          * Function 'echo(str1,str2,...,strN)' prints the concatenation of
       given
          string arguments on the console.
          * Function 'string(_#siz,str1,str2,...,strN)' generates a vector
          corresponding to the concatenation of given string/number arguments.

         ## Dynamic arrays:

         A dynamic array is defined as a one-column (or empty) image '[ind]'
       in
          the image list. It allows elements to be added or removed, each
       element having
          the same dimension (which is actually the number of channels of
       image
          '[ind]'). Dynamic arrays adapt their size to the number of elements
       they
          contain.

         A dynamic array can be manipulated in a math expression, with the
       following
          functions:
          * 'da_size(_#ind)': Return the number of elements in dynamic array
          '[ind]'.
          * 'da_back(_#ind)': Return the last element of the dynamic array
          '[ind]'.
          * 'da_insert(_#ind,pos,elt_1,_elt_2,...,_elt_N)': Insert 'N' new
          elements 'elt_k' starting from index 'pos' in dynamic array
          '[ind]'.
          * 'da_push(_#ind,elt1,_elt2,...,_eltN)': Insert 'N' new elements
          'elt_k' at the end of dynamic array '[ind]'.
          * 'da_pop(_#ind)': Same as 'da_back()' but also remove last
          element from the dynamic array '[ind]'.
          * 'da_push_heap(_#ind,elt1,_elt2,...,_eltN)' and
          'da_pop_heap(_#ind)' does the same but for a dynamic array viewed as
       a
          min-heap structure.
          * 'da_remove(_#ind,_start,_end)': Remove elements located between
          indices 'start' and 'end' (included) in dynamic array '[ind]'.
          * 'da_freeze(_#ind)': Convert a dynamic array into a 1-column image
       with
          height 'da_size(#ind)'.
          * The value of the k-th element of dynamic array '[ind]' is
       retrieved
          with 'i[_#ind,k]' (if the element is a scalar value), or 'I[_#ind,
          k]' (if the element is a vector).

         In the functions above, argument '#ind' may be omitted in which case
       it
          is assumed to be '#-1'.

         ## Special operators:

          * ';': expression separator. The returned value is always the last
          encountered expression. For instance expression '1;2;pi' is
       evaluated as
          'pi'.
          * '=': variable assignment. Variables in mathematical parser can
       only
          refer to numerical values (vectors or scalars). Variable names are
          case-sensitive. Use this operator in conjunction with ';' to define
       more
          complex evaluable expressions, such as

           t = cos(x); 3*t^2 + 2*t + 1

         These variables remain local to the mathematical parser and cannot be
          accessed outside the evaluated expression.
          * Variables defined in math parser may have a constant property, by
          specifying keyword 'const' before the variable name (e.g. 'const foo
       =
          pi/4;'). The value set to such a variable must be indeed a constant
          scalar. Constant variables allows certain types of optimizations in
       the math
          JIT compiler.

         ## Specific functions:

          * 'addr(expr)': return the pointer address to the specified
       expression
          'expr'.
          * 'o2c(_#ind,offset)' and 'c2o(_#ind,x,_y,_z,_c)': Convert image
          offset to image coordinates and vice-versa.
          * 'fill(target,expr)' or 'fill(target,index_name,expr)' fill the
          content of the specified target (often vector-valued) using a given
       expression,
          e.g. 'V = vector16(); fill(V,k,k^2 + k + 1);'. For a vector-valued
       target,
           it is basically equivalent to: 'for (index_name = 0,
          index_name<size(target), ++index_name, target[index_name] = expr);'.
          * 'u(max)' or 'u(min,max,_include_min,_include_max)': return a
          random value in range '0...max' or 'min...max', following a uniform
          distribution. Each range extremum can be included (default) in the
       distribution
          or not.
          * 'v(max)' or 'v(min,max,_include_min,_include_max)' do the same
          but returns an integer in specified range.
          * 'f2ui(value)' and 'ui2f(value)': Convert a large unsigned
          integer as a negative floating point value (and vice-versa), so that
       32bits
          floats can be used to store large integers while keeping a unitary
       precision.
          * 'i(_a,_b,_c,_d,_interpolation_type,_boundary_conditions)': return
       the
          value of the pixel located at position '(a,b,c,d)' in the associated
          image, if any ('0' otherwise). 'interpolation_type' can be {
          0:nearest neighbor | 1:linear | 2:cubic }. 'boundary_conditions' can
          be { 0:dirichlet | 1:neumann | 2:periodic | 3:mirror }. Omitted
          coordinates are replaced by their default values which are
       respectively
          'x', 'y', 'z', 'c', 'interpolation' and
          'boundary'. For instance command

           fill 0.5*(i(x+1)-i(x-1))

          will estimate the X-derivative of an image with a classical finite
       difference
          scheme.
          * 'j(_dx,_dy,_dz,_dc,_interpolation_type,_boundary_conditions)' does
       the
          same for the pixel located at position '(x+dx,y+dy,z+dz,c+dc)'
       (pixel
          access relative to the current coordinates).
          * 'i[offset,_boundary_conditions]' returns the value of the pixel
          located at specified 'offset' in the associated image buffer (or
          '0' if offset is out-of-bounds).
          * 'j[offset,_boundary_conditions]' does the same for an offset
       relative
          to the current pixel coordinates '(x,y,z,c)'.
          * 'i(#ind,_x,_y,_z,_c,_interpolation,_boundary_conditions)',
       'j(#ind,
          _dx,_dy,_dz,_dc,_interpolation,_boundary_conditions)',
       'i[#ind,offset,
          _boundary_conditions]' and 'i[offset,_boundary_conditions]' are
          similar expressions used to access pixel values for any numbered
       image
          '[ind]' of the list.
          * 'I/J[_#ind,offset,_boundary_conditions]' and 'I/J(_#ind,_x,_y,_z,
          _interpolation,_boundary_conditions)' do the same as
       'i/j[_#ind,offset,
          _boundary_conditions]' and 'i/j(_#ind,_x,_y,_z,_c,_interpolation,
          _boundary_conditions)' but return a vector instead of a scalar (e.g.
       a
          vector '[ R,G,B ]' for a pixel at '(a,b,c)' in a color image).
          * 'crop(_#ind,_x,_y,_z,_c,_dx,_dy,_dz,_dc,_boundary_conditions)'
       returns
          a vector whose values come from the cropped region of image '[ind]'
       (or
          from default image selected if 'ind' is not specified). Cropped
       region
          starts from point '(x,y,z,c)' and has a size of '(dx,dy,dz,dc)'.
          Arguments for coordinates and sizes can be omitted if they are not
       ambiguous
          (e.g. 'crop(#ind,x,y,dx,dy)' is a valid invocation of this
       function).
          * 'crop(S,w,h,d,s,_x,_y,_z,_c,_dx,_dy,_dz,_dc,_boundary_conditions)'
          does the same but extracts the cropped data from a vector 'S',
       viewed as
          an image of size '(w,h,d,s)'.
          * 'draw(_#ind,S,_x,_y,_z,_c,_dx,_dy,_dz,_dc,_opacity,_opacity_mask,
          _max_opacity_mask)' draws a sprite 'S' in image '[ind]' (or in
          default image selected if 'ind' is not specified) at coordinates
       '(x,y,
          z,c)'.
          * 'draw(D,w,h,s,d,S,_x,_y,_z,_c,_dx,_dy,_dz,_dc,_opacity,_M,_max_M)'
          does the same but draw the sprite 'S' in the vector 'D', viewed as
          an image of size '(w,h,d,s)'.
          * 'polygon(_#ind,nb_vertices,coords,_opacity,_color)' draws a filled
          polygon in image '[ind]' (or in default image selected if 'ind' is
          not specified) at specified coordinates. It draws a single line if
          'nb_vertices' is set to 2.
          * 'polygon(_#ind,-nb_vertices,coords,_opacity,_pattern,_color)'
       draws a
          outlined polygon in image '[ind]' (or in default image selected if
          'ind' is not specified) at specified coordinates and with specified
       line
          pattern. It draws a single line if 'nb_vertices' is set to 2.
          * 'ellipse(_#ind,xc,yc,radius1,_radius2,_angle,_opacity,_color)'
       draws a
          filled ellipse in image '[ind]' (or in default image selected if
          'ind' is not specified) with specified coordinates.
          * 'ellipse(_#ind,xc,yc,-radius1,-_radius2,_angle,_opacity,_pattern,
          _color)' draws an outlined ellipse in image '[ind]' (or in default
          image selected if 'ind' is not specified).
          * 'flood(_#ind,_x,_y,_z,_tolerance,_is_high_connectivity,_opacity,
          _color)' performs a flood fill in image '[ind]' (or in default image
          selected if 'ind' is not specified) with specified coordinates. This
       is
          the math evaluator analog to command flood.
          *
       'resize(#ind,w,_h,_d,_s,_interp,_boundary_conditions,_cx,_cy,_cz,_cc)'
          resizes an image of the associated list with specified dimension and
          interpolation method. When using this function, you should consider
       retrieving
          the (non-constant) image dimensions using the dynamic functions
          'w(_#ind)', 'h(_#ind)', 'd(_#ind)', 's(_#ind)',
          'wh(_#ind)', 'whd(_#ind)' and 'whds(_#ind)' instead of the
          corresponding constant variables.
          * 'if(condition,expr_then,_expr_else)': return value of
          'expr_then' or 'expr_else', depending on the value of
          'condition' { 0:false | other:true }. 'expr_else' can be
          omitted in which case '0' is returned if the condition does not
       hold.
          Using the ternary operator 'condition?expr_then[:expr_else]' gives
       an
          equivalent expression. For instance, G'MIC commands

           fill if(!(x%10),255,i)

          and

           fill x%10?i:255

          both draw blank vertical lines on every 10th column of an image.
          * 'do(expression,_condition)' repeats the evaluation of
          'expression' until 'condition' vanishes (or until
          'expression' vanishes if no 'condition' is specified). For instance,
           the expression:

           if(N<2,N,n=N-1;F0=0;F1=1;do(F2=F0+F1;F0=F1;F1=F2,n=n-1))

          returns the N-th value of the Fibonacci sequence, for 'N>=0' (e.g.,
          '46368' for 'N=24'). 'do(expression,condition)' always
          evaluates the specified expression at least once, then check for the
       loop
          condition. When done, it returns the last value of 'expression'.
          * 'for(init,condition,_procedure,body)' first evaluates the
       expression
          'init', then iteratively evaluates 'body' (followed by
          'procedure' if specified) while 'condition' holds (i.e. not zero).
          It may happen that no iterations are done, in which case the
       function returns
          'nan'. Otherwise, it returns the last value of 'body'. For instance,
           the expression:

           if(N<2,N,for(n=N;F0=0;F1=1,n=n-1,F2=F0+F1;F0=F1;F1=F2))

          returns the 'N'-th value of the Fibonacci sequence, for 'N>=0'
          (e.g., '46368' for 'N=24').
          * 'while(condition,expression)' is exactly the same as 'for(init,
          condition,expression)' without the specification of an initializing
          expression.
          * 'repeat(nb_iters,expr)' or 'fill(nb_iters,iter_name,expr)' run
          'nb_iters' iterations of the specified expression 'expr', e.g.
          'V = vector16(); repeat(16,k,V[k] = k^2 + k + 1);'. It is basically
          equivalent to: 'for (iter_name = 0, iter_name<nb_iters, ++iter_name,
          expr);'.
          * 'break()' and 'continue()' respectively breaks and continues the
          current running block.
          * 'fsize('filename')' returns the size of the specified 'filename'
          (or '-1' if file does not exist).
          * 'date(attr,'path')' returns the date attribute for the given
          'path' (file or directory), with 'attr' being { 0:year | 1:month
          | 2:day | 3:day of week | 4:hour | 5:minute | 6:second }, or a
       vector of
          those values.
          * 'date(_attr)' returns the specified attribute for the current
       (locale)
          date (attributes being { 0...6:same meaning as above |
       7:milliseconds }).
          * 'print(expr1,expr2,...)' or 'print(#ind)' prints the value of
          the specified expressions (or image information) on the console, and
       returns
          the value of the last expression (or 'nan' in case of an image).
       Function
          'prints(expr)' also prints the string composed of the character
       codes
          defined by the vector-valued expression (e.g. 'prints('Hello')').
          * 'debug(expression)' prints detailed debug info about the sequence
       of
          operations done by the math parser to evaluate the expression (and
       returns its
          value).
          * 'display(_X,_w,_h,_d,_s)' or 'display(#ind)' display the
          contents of the vector 'X' (or specified image) and wait for user
       events.
          if no arguments are provided, a memory snapshot of the math parser
       environment
          is displayed instead.
          * 'begin(expression)' and 'end(expression)' evaluates the
          specified expressions only once, respectively at the beginning and
       end of the
          evaluation procedure, and this, even when multiple evaluations are
       required
          (e.g. in 'fill ">begin(foo = 0); ++foo"').
          * 'copy(dest,src,_nb_elts,_inc_d,_inc_s,_opacity)' copies an entire
          memory block of 'nb_elts' elements starting from a source value
          'src' to a specified destination 'dest', with increments defined by
          'inc_d' and 'inc_s' respectively for the destination and source
          pointers.
          * 'stats(_#ind)' returns the statistics vector of the running image
          '[ind]', i.e the vector '[ im,iM,ia,iv,xm,ym,zm,cm,xM,yM,zM,cM,is,ip
          ]' (14 values).
          * 'ref(expr,a)' references specified expression 'expr' as variable
          name 'a'.
          * 'unref(a,b,...)' destroys references to the named variable given
       as
          arguments.
          * 'breakpoint()' inserts a possible computation breakpoint (useless
       with
          the cli interface).
          * '_(comment) expr' just returns expression 'expr' (useful for
       inserting
          inline comments in math expressions).
          * 'run('pipeline')' executes the specified G'MIC pipeline as if it
       was
          called outside the currently evaluated expression.
          * 'set('variable_name',A)' set the G'MIC variable '$variable_name'
          with the value of expression 'A'. If 'A' is a vector-valued
          variable, it is assumed to encode a string.
          * 'store('variable_name',A,_w,_h,_d,_s,_is_compressed)' transfers
       the
          data of vector 'A' as a '(w,h,d,s)' image to the G'MIC variable
          '$variable_name'. Thus, the data becomes available outside the math
          expression (that is equivalent to using the regular command store,
       but
          directly in the math expression).
          * 'get('variable_name',_size,_return_as_string)' returns the value
       of
          the specified variable, as a vector of 'size' values, or as a scalar
       (if
          'size' is zero or not specified).
          * 'name(_#ind,size)' returns a vector of size 'size', whose values
          are the characters codes of the name of image '[ind]' (or default
       image
          selected if 'ind' is not specified).
          * 'correlate(I,wI,hI,dI,sI,K,wK,hK,dK,sK,_boundary_conditions,
          _is_normalized,_channel_mode,_xcenter,_ycenter,_zcenter,_xstart,_ystart,_zstart,
          _xend,_yend,_zend,_xstride,_ystride,_zstride,_xdilation,_ydilation,_zdilation,
          _interpolation_type)' returns the correlation, unrolled as a vector,
       of the
          '(wI,hI,dI,sI)'-sized image 'I' with the '(wK,hK,dK,
          sK)'-sized kernel 'K' (the meaning of the other arguments are the
       same
          as in command 'correlate'). Similar function 'convolve(...)' is
          also defined for computing the convolution between 'I' and 'K'.

         ## User-defined macros:

          * Custom macro functions can be defined in a math expression, using
       the
          assignment operator '=', e.g.

           foo(x,y) = cos(x + y); result = foo(1,2) + foo(2,3)

          * Trying to override a built-in function (e.g. 'abs()') has no
       effect.
          * Overloading macros with different number of arguments is possible.
          Re-defining a previously defined macro with the same number of
       arguments
          discards its previous definition.
          * Macro functions are indeed processed as macros by the mathematical
          evaluator. You should avoid invoking them with arguments that are
       themselves
          results of assignments or self-operations. For instance,

           foo(x) = x + x; z = 0; foo(++z)

          returns '4' rather than expected value '2'.
          * When substituted, macro arguments are placed inside parentheses,
       except if a
          number sign '#' is located just before or after the argument name.
       For
          instance, expression

           foo(x,y) = x*y; foo(1+2,3)

          returns '9' (being substituted as '(1+2)*(3)'), while expression

           foo(x,y) = x#*y#; foo(1+2,3)

          returns '7' (being substituted as '1+2*3').
          * Number signs appearing between macro arguments function actually
       count for
          empty separators. They may be used to force the substitution of
       macro
          arguments in unusual places, e.g. as in

           str(N) = ['I like N#'];

          * Macros with variadic arguments can be defined, by specifying a
       single
          argument name followed by '...'. For instance,

           foo(args...) = sum([ args ]^2);

          defines a macro that returns the sum of its squared arguments, so
       'foo(1,2,
          3)' returns '14' and 'foo(4,5)' returns '41'.

         ## Multi-threaded and in-place evaluation:

          * If your image data are large enough and you have several CPUs
       available, it
          is likely that the math expression passed to a 'fill', 'eval' or
          'input' commands is evaluated in parallel, using multiple
       computation
          threads.
          * Starting an expression with ':' or '*' forces the evaluations
          required for an image to be run in parallel, even if the amount of
       data to
          process is small (beware, it may be slower to evaluate in this
       case!). Specify
          ':' (rather than '*') to avoid possible image copy done before
          evaluating the expression (this saves memory, but do this only if
       you are sure
          this step is not required!)
          * Expression starting with '+' are evaluated in a single-threaded
       way,
          with possible image copy.
          * If the specified expression starts with '>' or '<', the pixel
          access operators 'i()', 'i[]', 'j()' and 'j[]' return
          values of the image being currently modified, in forward ('>') or
          backward ('<') order. The multi-threading evaluation of the
       expression is
          disabled in this case.
          * Function 'critical(expr)' forces the execution of the given
       expression
          in a single thread at a time.
          * 'begin_t(expr)' and 'end_t(expr)' evaluates the specified
          expression once for each running thread (so possibly several times)
       at the
          beginning and the end of the evaluation procedure.
          * 'merge(variable,operator)' tells to merge the local variable value
          computed by threads, with the specified operator, when all threads
       have
          finished computing.
          * Expressions 'i(_#ind,x,_y,_z,_c)=value', 'j(_#ind,x,_y,_z,
          _c)=value', 'i[_#ind,offset]=value' and 'j[_#ind,offset]=value'
          set a pixel value at a different location than the running one in
       the image
          '[ind]' (or in the associated image if argument '#ind' is omitted),
          either with global coordinates/offsets (with 'i(...)' and 'i[...]'),
           or relatively to the current position '(x,y,z,c)' (with 'j(...)'
          and 'j[...]'). These expressions always return 'value'.

         10. Adding Custom Commands
             ----------------------

          * New custom commands can be added by the user, through the use of
       G'MIC
          custom commands files.
          * A command file is a simple text file, where each line starts
       either by

           command_name: command_definition

          or

           command_definition (continuation)

          * At startup, G'MIC automatically includes user's command file
          '$HOME/.gmic' (on Unix) or '%USERPROFILE%ser.gmic' (on
          Windows). The CLI tool 'gmic' automatically runs the command
          'cli_start' if defined.
          * Custom command names must use character set '[a-zA-Z0-9_]' and
       cannot
          start with a number.
          * Any '# comment' expression found in a custom commands file is
          discarded by the G'MIC parser, wherever it is located in a line.
          * In a custom command, the following '$-expressions' are recognized
       and
          substituted:
            -  '$*' is substituted by a verbatim copy of the specified string
       of
          arguments (do not include arguments set to default values).
            -  '$"*"' is substituted by the sequence of specified arguments,
          separated by commas ',', each being double-quoted (include arguments
       set
          to default values).
            -  '$#' is substituted by the maximum index of known arguments
       (either
          specified by the user or set to a default value in the custom
       command).
            -  '$[]' is substituted by the list of selected image indices that
          have been specified in the command invocation.
            -  '$?' is substituted by a printable version of '$[]' to be
          used in command descriptions.
            -  '$i' and '${i}' are both substituted by the 'i'-th
          specified argument. Negative indices such as '${-j}' are allowed and
          refer to the 'j'-th latest argument. '$0' is substituted by the
          custom command name.
            -  '${i=default}' is substituted by the value of '$i' (if
          defined) or by its new value set to 'default' otherwise ('default'
          may be a '$-expression' as well).
            -  '${subset}' is substituted by the argument values (separated by
          commas ',') of a specified argument subset. For instance expression
          '${2--2}' is substituted by all specified command arguments except
       the
          first and the last one. Expression '${^0}' is then substituted by
       all
          arguments of the invoked command (eq. to '$*' if all arguments have
       been
          indeed specified).
            -  '$=var' is substituted by the set of instructions that will
       assign
          each argument '$i' to the named variable 'var$i' (for i in
          '[0...$#]'. This is particularly useful when a custom command want
       to
          manage variable numbers of arguments. Variables names must use
       character set
          '[a-zA-Z0-9_]' and cannot start with a number.

          * These particular '$-expressions' for custom commands are always
          substituted, even in double-quoted items or when the dollar sign '$'
          is escaped with a backslash '$'. To avoid substitution, place an
       empty
          double quoted string just after the '$' (as in '$""1').
          * Specifying arguments may be skipped when invoking a custom
       command, by
          replacing them by commas ',' as in expression

           flower ,,3

          Omitted arguments are set to their default values, which must be
       thus
          explicitly defined in the code of the corresponding custom command
       (using
          default argument expressions as '${1=default}').
          * If one numbered argument required by a custom command misses a
       value, an
          error is thrown by the G'MIC interpreter.
          * It is possible to specialize the invocation of a '+command' by
          defining it as

           +command_name: command_definition

          * A +-specialization takes priority over the regular command
       definition when
          the command is invoked with a prepended '+'.
          * When only a +-specialization of a command is defined, invoking
          'command' is actually equivalent to '+command'.

         11. List of Commands
             ----------------

         All available G'MIC commands are listed below, by categories. An
       argument
          specified between '[]' or starting by '_' is optional except when
          standing for an existing image '[image]', where 'image' can be
          either an index number or an image name. In this case, the '[]'
          characters are mandatory when writing the item. Note that all images
       that serve
          as illustrations in this reference documentation are normalized in
       range '[0,
          255]' before being displayed. You may need to do this explicitly
       (command
          'normalize 0,255') if you want to save and view images with the same
          aspect than those illustrated in the example codes.
         The examples accompanying this 'List of Commands' illustrate the use
       of the
          G'MIC language and are written as they would appear in a custom
       command.
          While some examples may work if entered directly at a shell prompt,
       there is no
          guarantee. No attempt has been made to escape special characters in
       these
          examples, which many shells reserve.

         11.1. Global Options
               --------------

         debug (+):

           Activate debug mode.
           When activated, the G'MIC interpreter becomes very verbose and
       outputs
           additional log
           messages about its internal state on the standard output (stdout).
           This option is useful for developers or to report possible bugs of
       the
           interpreter.

         h:
             Shortcut for command 'help'.

         help:
             command |
             (no arg)

           Display help (optionally for specified command only) and exit.
           (equivalent to shortcut command 'h').

         version:

           Display current version number on stdout.

         11.2. Input / Output
               --------------

         camera (+):
             _camera_index>=0,_nb_frames>0,_skip_frames>=0,_capture_width>=0,
               _capture_height>=0

           Insert one or several frames from specified camera.
           When 'nb_frames==0', the camera stream is released instead of
           capturing new images.
           This command requires features from the OpenCV library (not enabled
       in
           G'MIC by default).

           Default values: 'camera_index=0' (default camera),
            'nb_frames=1', 'skip_frames=0' and
            'capture_width=capture_height=0' (default size).

         m (+):
             Shortcut for command 'command'.

         command (+):
             _add_debug_info={ 0 | 1 },{ filename | http[s]://URL | "string" }

           Import G'MIC custom commands from specified file, URL or string.
           (equivalent to shortcut command 'm').

           Imported commands are available directly after the 'command'
           invocation.
           Specified filename is not allowed to contain colons ':'.

           Default value: 'add_debug_info=1' (except for a "string"
            argument, in which case 'add_debug_info=0').

           Example:
             [#1] image.jpg command "foo : mirror y deform $""1" +foo[0] 5
       +foo[0] 15

         compress_to_keypoints:
             _method,_max_keypoints>=0,_err_avg[%]>=0,_err_max[%]>=0,_"err_command"

           Compress each of the selected images into a set of keypoints that
       can be
           further decompressed using command decompress_from_keypoints.
           Beware: This type of compression is effective only for images with
           very smooth content.
           'method' can be { 0:PDE | 1:RBF }. Add '2' to
           'method' to enable removal step.
            * 'max_keypoints' is the maximal number of keypoints generated by
           the compression method. If 'max_keypoints<0', the removal step is
       not
           done when number of maximal keypoints has been reached.
           'max_keypoints=0' means 'no limits'.
            * 'err_avg' is the desired average compression error.
            * 'err_max' is the desired pointwise max compression error.
            * 'err_command' is the code of a command that inputs the two
       images
           '[reference]' and '[compressed]' and compute a single error map
           as a last image.
           Defaults values: 'method=3', 'max_keypoints=0',
           'err_avg=1%', 'err_max=5%' and 'err_command=-. [0] norm.'

         cursor (+):
             _mode = { 0:hide | 1:show }

           Show or hide mouse cursor for selected instant display windows.
           Command selection (if any) stands for instant display window
       indices
           instead of image indices.

           Default value: 'mode=1'.

         delete (+):
             filename1[,filename2,...]

           Delete specified filenames on disk. Multiple filenames must be
       separated
           by commas.

         d:
             Shortcut for command 'display'.

         display:

           Display selected images in an interactive window.
           (equivalent to shortcut command 'd').

           When invoked with a '+' prefix (i.e. '+display'), the command
           outputs its log messages on 'stdout' rather than on 'stderr'.
           Display window #0 is used as the default window for the display, if
           already opened.

           Available controls are shown below (where 'LMB' = Left mouse
       button,
           'RMB' = Right mouse button, 'MMB' = Middle mouse button and
           'MW' = Mouse wheel).

            * Thumbnail navigation bar:
           'TAB': Show/hide thumbnails - 'LMB': Select thumbnail or shift
           thumbnail bar - '0'-'9','ARROWS' (opt. '+SHIFT'),
           'B','BACKSPACE','C','E','END','H',
           'HOME','SPACE': Navigate and select thumbnails (add
           'CTRL' if mouse pointer is outside thumbnail bar).

            * Image view:
           'LMB' or 'MMB': Image pan - 'RMB' or 'MW': Image
           zoom - 'ARROWS' (opt. '+SHIFT'),'HOME','END': Shift
           view - 'A': Switch alpha rendering - 'C': Center view -
           'E': Go to lower-right corner - 'ENTER': Reset view -
           'G': Toggle grid - 'H': Go to upper-left corner - 'K':
           Switch background - 'M': Toggle 3D view - 'N': Switch
           normalization - 'P': Print info about current image pixel on
           'stdout' - 'PAGEUP' or 'PAGEDOWN': Raise/lower base
           channel - 'R': Rotate image - 'V': Crop image - 'Z':
           Switch zoom factor - '0'-'9': Set zoom factor.

            * 3D mesh view:
           'LMB': Mesh rotation - 'CTRL+LMB' or 'MMB': Mesh pan -
           'RMB': Mesh zoom -  'A': Toggle axes - 'D': Switch face
           side mode - 'F': Change focale - 'J': Start/stop animation -
           'K': Switch background - 'O': Switch outline mode - 'P':
           Print 3D pose matrix on 'stdout' - 'R': Switch rendering mode -
           'T': Switch motion rendering mode - 'X': Show/hide bounding-box
           - 'U': Switch animation mode - 'Z': Toggle z-buffer.

            * 2D images specific:
           'CTRL+LMB': Rectangular selection.

            * 3D volumetric images specific:
           'CTRL+MW': Pan along orthogonal axis - 'X': Reset area layout.

            * Window size, decoration and data I/O:
           'CTRL+C': Decrease window size - 'CTRL+D': Increase window
           size - 'CTRL+F': Toggle fullscreen - 'CTRL+I': Toggle info
           label - 'CTRL+O': Save copy of image as a '.gmz' file -
           'CTRL+L': Save copy of image list as '.gmz' file - 'CTRL+S':
           Save screenshot as a '.png' file - 'CTRL+W': Start/stop window
           recording - 'CTRL+X': Toggle cursor.

            * Configuration variables:
           The viewer configuration can be tuned by assigning the following
       variables:
              -  '_display_selected' is an integer or an image name that tells
           which image is selected by default.
              -  '_display_alpha' can be { 0:off | 1:on | 2:over black |
           3:over gray | 4:over white } (default value: '0').
              -  '_display_background', an integer in range [ 0,9 ] (default
           value: '3').
              -  '_display_cursor' can be { 0:off | 1:on (2D only) | 2:on
           (+3D volumetric images) } (default value: '1').
              -  '_display_is_grid' can be { 0:off | 1:on } (default
           value: '1').
              -  '_display_is_info' can be { 0:off | 1:on } (default
           value: '1').
              -  '_display_normalization' can be { -1:auto | 0:off | 1:cut |
           2:stretch channelwise | 3:stretch global | 4: stretch (global once)
       }
           (default value: '-1').
              -  '_display_print_images' can be { 0:off | N>0 } (default
           value: '5'). It sets the max number 'N' of images whose
           information is initially printed on 'stderr' or 'stdout'.
              -  '_display_3d_is_rendered' can be { 0:off | 1:on }
           (default value: '1').
              -  '_display_3d_rendering_mode' can be { 0:dots | 1:wireframe
           | 2:flat | 3:flat-shaded | 4:gouraud-shaded | 5=phong-shaded }
       (default
           value: '4').
              -  '_display_3d_outline_mode' can be { 0:no-outline |
           1:black-outline | 2:gray-outline | 3:red-outline | 4:green-outline
       |
           5:blue-outline | 6:white-outline } (default value: '0').
              -  '_display_3d_motion_rendering_mode' can be {
           -1:bounding-box | 0:dots | 1:wireframe | 2:flat | 3:flat-shaded |
           4:gouraud-shaded | 5=phong-shaded } (default value: '3').
              -  '_display_3d_motion_time_limit' is specified in ms. Above
       this
           time, motion rendering toggle to 'bounding-box' mode (default
       value:
           '300').
              -  '_display_3d_side_mode' can be { 0:single-sided |
           1:double-sided | 2:single-sided (flipped) } (default value: '0').
              -  '_display_3d_is_zbuffer' can be { 0:off | 1:on }
           (default value: '1').
              -  '_display_3d_focale' can be { <0: perspective projection
           w/o sprite zooming, 0: parallel projection | >0: perspective
       projection
           } (default value: 1.5).
              -  '_display_3d_is_axes' can be { 0:off | 1:on } (default
           value: '1').
              -  '_display_3d_is_bounding_box' can be { 0:off | 1:on }
           (default value: '0').
              -  '_display_3d_background' is an unsigned integer in range [0,
           11] (default value: '11').
              -  '_display_3d_pose' is a sequence of 12 values that defines
       the
           current 3D pose matrix (read/write).
              -  '_display_3d_animation' can be { 0:off | 1:forward |
           2:backward } (default value: '0').
              -  '_display_3d_animation_mode' can be { 0-3:X-axis |
           4-7:Y-axis | 8-11:Z-axis | 12-15:XYZ-axes } (default value: '4').

         d0:
             Shortcut for command 'display0'.

         display0:

           Display selected images in an interactive window, without
       normalization
           and alpha mode activated.

         da:
             Shortcut for command 'display_array'.

         display_array:
             _width>0,_height>0

           Display images in interactive windows where pixel neighborhoods can
       be
           explored.

           Default values: 'width=13' and 'height=width'.

         dc:
             Shortcut for command 'display_camera'.

         display_camera:

           Open camera viewer.
           This command requires features from the OpenCV library (not enabled
       in
           G'MIC by default).

         dclut:
             Shortcut for command 'display_clut'.

         display_clut:
             _image_resolution>0,_clut_resolution>0

           Display selected 3D color LUTs.

           Default values: 'image_resolution=320' and
            'clut_resolution=33'.

           Example:
             [#1] clut tealorange clut summer clut 60s display_clut 400

         dfft:
             Shortcut for command 'display_fft'.

         display_fft:

           Display fourier transform of selected images, with centered log-
       module and
           argument.
           (equivalent to shortcut command 'dfft').

           Example:
             [#1] image.jpg +display_fft

         dg:
             Shortcut for command 'display_graph'.

         display_graph:
             _width>=0,_height>=0,_plot_type,_vertex_type,_xmin,_xmax,_ymin,_ymax,
               _xlabel,_ylabel

           Render graph plot from selected image data.
           'plot_type' can be { 0:none | 1:lines | 2:splines | 3:bar }.
           'vertex_type' can be { 0:none | 1:points | 2,3:crosses | 4,
           5:circles | 6,7:squares }.
           'xmin','xmax','ymin','ymax' set the coordinates of
           the displayed xy-axes.
           if specified 'width' or 'height' is '0', then image size
           is set to half the screen size.

           Default values: 'width=0', 'height=0',
            'plot_type=1', 'vertex_type=1', 'xmin=xmax=ymin=ymax=0
            (auto)', 'xlabel="x-axis"' and 'ylabel="y-axis"'.

           Example:
             [#1] 128,1,1,1,'cos(x/10+u)' +display_graph 400,300,3

         dh:
             Shortcut for command 'display_histogram'.

         display_histogram:
             _width>=0,_height>=0,_clusters>0,_min_value[%],_max_value[%],_show_axes={
               0 | 1 },_expression.

           Render a channel-by-channel histogram.
           If selected images have several slices, the rendering is performed
       for all
           input slices.
           'expression' is a mathematical expression used to transform the
           histogram data for visualization purpose.
           (equivalent to shortcut command 'dh').

           if specified 'width' or 'height' is '0', then image size
           is set to half the screen size.

           Default values: 'width=0', 'height=0',
            'clusters=256', 'min_value=0%', 'max_value=100%',
            'show_axes=1' and 'expression=i'.

           Example:
             [#1] image.jpg +display_histogram 512,300

         display_parametric:
             _width>0,_height>0,_outline_opacity,_vertex_radius>=0,_is_antialiased={
       0
               | 1 },_is_decorated={ 0 | 1 },_xlabel,_ylabel

           Render 2D or 3D parametric curve or point clouds from selected
       image data.
           Curve points are defined as pixels of a 2 or 3-channel image.
           If the point image contains more than 3 channels, additional
       channels
           define the (R,G,B) color for each vertex.
           If 'outline_opacity>1', the outline is colored according to the
           specified vertex colors and
           'outline_opacity-1' is used as the actual drawing opacity.

           Default values: 'width=512', 'height=width',
            'outline_opacity=3', 'vertex_radius=0',
            'is_antialiased=1','is_decorated=1',
            'xlabel="x-axis"' and 'ylabel="y-axis"'.

           Example:
             [#1]
       1024,1,1,2,'t=x/40;(!c?sin(t):cos(t))*(exp(cos(t))-2*cos(4*t)-sin(t
              /12)^5)' display_parametric 512,512
             [#2] 1000,1,1,2,u(-100,100) quantize 4,1 noise 12 channels 0,2
              +normalize 0,255 append c display_parametric 512,512,0.1,8

         display_polar:
             _width>32,_height>32,_outline_type,_fill_R,_fill_G,_fill_B,_theta_start,
               _theta_end,_xlabel,_ylabel

           Render polar curve from selected image data.
           'outline_type' can be { r<0:dots with radius -r | 0:no outline |
           r>0:lines+dots with radius r }.
           'fill_color' can be { -1:no fill | R,G,B:fill with specified
           color }.

           Default values: 'width=500', 'height=width',
            'outline_type=1', 'fill_R=fill_G=fill_B=200',
            'theta_start=0', 'theta_end=360', 'xlabel="x-axis"'
            and 'ylabel="y-axis"'.

           Example:
             [#1] 300,1,1,1,'0.3+abs(cos(10*pi*x/w))+u(0.4)' display_polar
       512,512,4,
              200,255,200
             [#2] 3000,1,1,1,'x^3/1e10' display_polar
       400,400,1,-1,,,0,{15*360}

         dq:
             Shortcut for command 'display_quiver'.

         display_quiver:
             _size_factor>0,_arrow_size>=0,_color_mode={ 0:monochrome |
       1:grayscale |
               2:color }

           Render selected images of 2D vectors as a field of 2D arrows.
           (equivalent to shortcut command 'dq').

           Default values: 'size_factor=16', 'arrow_size=1.5' and
            'color_mode=1'.

           Example:
             [#1] image.jpg +luminance gradient[-1] xy rv[-2,-1] *[-2] -1
       a[-2,-1] c
              crop 60,10,90,30 +display_quiver[1] ,

         drgba:
             Shortcut for command 'display_rgba'.

         display_rgba:
             _background_RGB_color

           Render selected RGBA images over a checkerboard or colored
       background.
           (equivalent to shortcut command 'drgba').

           Default values: 'background_RGB_color=undefined'
            (checkerboard).

           Example:
             [#1] image.jpg +norm threshold[-1] 40% blur[-1] 3 normalize[-1]
       0,255
              append c display_rgba

         dt:
             Shortcut for command 'display_tensors'.

         display_tensors:
             _size_factor>0,_ellipse_size>=0,_color_mode={ 0:monochrome |
       1:grayscale |
               2:color },_outline>=0

           Render selected images of tensors as a field of 2D ellipses.
           (equivalent to shortcut command 'dt').

           Default values: 'size_factor=16', 'ellipse_size=1.5',
            'color_mode=2' and 'outline=2'.

           Example:
             [#1] image.jpg +diffusiontensors 0.1,0.9 rescale2d. 64
              +display_tensors. 16,2

           Tutorial: https://gmic.eu/oldtutorial/_display_tensors

         dv3d:
             Shortcut for command 'display_voxels3d'.

         display_voxels3d:

           Display selected images as set of 3D voxels.
           (equivalent to shortcut command 'dv3d').

         dw:
             Shortcut for command 'display_warp'.

         display_warp:
             _cell_size>0

           Render selected 2D warping fields.
           (equivalent to shortcut command 'dw').

           Default value: 'cell_size=15'.

           Example:
             [#1] 400,400,1,2,'x=x-w/2;y=y-h/2;r=sqrt(x*x+y*y);a=atan2(y,
              x);5*sin(r/10)*[cos(a),sin(a)]' +display_warp 10

         e (+):
             Shortcut for command 'echo'.

         echo (+):
             message

           Output specified message on the error output.
           (equivalent to shortcut command 'e').

           Command selection (if any) stands for displayed call stack subset
       instead
           of image indices.
           When invoked with a '+' prefix (i.e. '+echo'), the command
           output its message on stdout rather than stderr.

         echo_file:
             filename,message

           Output specified message, appending it to specified output file.
           (similar to 'echo' for specified output file stream).

         font:
             { 'Font_name' | font_number | font.gmz
       },_font_height[%]>0,_is_bold={ 0 |
               1 }

           Return font identifier (variable name) that can be further used in
       command
           'text' as a custom font.
           'Font_name' can be { Acme | Arial | Arial Black | Black Ops One |
           BlackChancery | Cabin Sketch | Caprasimo | Carnevalee Freakshow |
       Cheese
           Burger | Cheque | Cheque-Black | Chlorinar | Comic Sans MS |
       Courier New |
           Creepster | Georgia | Impact | Lobster | Luckiest Guy | Macondo |
           MedievalSharp | Odin Rounded | Oswald | Palatino Linotype |
       Playfair
           Display | Roboto | Sacramento | Satisfy | Sofia | Tex Gyre Adventor
       | Times
           New Roman | Titan One | Verdana }.
           If a filename 'font.gmz' is specified, it must be a file converted
           with command 'font2gmz'.

           Default values: 'font_height=64' and 'is_bold=0'.

           Example:
             [#1] 400,300,1,3 text "Hello World!",0.5~,0.5~,${"font
              Burger

         font2gmz:
             _font_name,_font_size>0,_font_qualifier

           Convert specified font to G'MIC format, so that it can be used as a
       custom
           font for command 'text'.
           'font_name' can be either a filename as 'font.ttf', or a
           'Google Font Name'.
           This command requires the command line tool 'cutycapt' to be
       installed
           on your system.
           Beware, 'font_size' is the size of font used for the rendering, it
           does not correspond to the font height.

           Default values: 'font_name=Sofia', 'font_size=24' and
            'font_qualifier=""'.

         function1d:
             0<=smoothness<=1,x0>=0,y0,x1>=0,y1,...,xn>=0,yn

           Insert continuous 1D function from specified list of keypoints
       (xk,yk)
           in range [0,max(xk)] (xk are positive integers).

           Example:
             [#1] function1d 1,0,0,10,30,40,20,70,30,80,0 +display_graph
       400,300

         identity:
             _width>=0,_height>=0,_depth>=0

           Insert an identity map of given size at the end of the image list.

           Default values: 'height=width' and 'depth=1'.

           Example:
             [#1] identity 5,1 identity 8,8

         i (+):
             Shortcut for command 'input'.

         input (+):
             [type:]filename |
             [type:]http://URL |
             [selection]x_nb_copies>0 |
             { width>0[%] | [image_w] },{ _height>0[%] | [image_h] },{
       _depth>0[%] |
               [image_d] },{ _spectrum>0[%] | [image_s] },_{
       value1,_value2,... |
               'formula' } |
             (value1{,|;|/|^}value2{,|;|/|^}...[:{x|y|z|c|,|;|/|^}]) |
             0

           Insert a new image taken from a filename or from a copy of an
       existing
           image [index],
           or insert new image with specified dimensions and values. Single
       quotes
           may be omitted in
           'formula'. Specifying argument '0' inserts an 'empty'
           image.
           (equivalent to shortcut command 'i').

           Default values: 'nb_copies=1', 'height=depth=spectrum=1'
            and 'value1=0'.

           Example:
             [#1] input image.jpg
             [#2] input (1,2,3;4,5,6;7,8,9^9,8,7;6,5,4;3,2,1)
             [#3] image.jpg (1,2,3;4,5,6;7,8,9) (255^128^64) 400,400,1,3,
              '(x>w/2?x:y)*c'

           Tutorial: https://gmic.eu/tutorial/input

         input_565:
             filename,width>0,height>0,reverse_endianness={ 0 | 1 }

           Insert image data from a raw RGB-565 file, at the end of the list.

           Default value: 'reverse_endianness=0'.

         ib:
             Shortcut for command 'input_bytes'.

         input_bytes:
             filename

           Input specified filename as a 1D array of bytes.
           (equivalent to shortcut command 'ib').

         input_csv:
             "filename",_read_data_as={ 0:numbers | 1:strings | _variable_name
       }

           Insert number of string array from specified .csv file.
           If 'variable_name' is provided, the string of each cell is stored
       in
           a numbered variable '_variable_name_x_y', where 'x' and
           'y' are the indices of the cell column and row respectively
       (starting
           from '0').
           Otherwise, a 'WxH' image is inserted at the end of the list, with
           each vector-valued pixel 'I(x,y)' encoding the number or the string
           of each cell.
           This command returns the 'W,H' dimension of the read array, as the
           status.

           Default value: 'read_data_as=1'.

         input_cube:
             "filename",_convert_1d_cluts_to_3d={ 0 | 1 }.

           Insert CLUT data from a .cube filename (Adobe CLUT file format).

           Default value: 'convert_1d_cluts_to_3d=1'.

         input_flo:
             "filename"

           Insert optical flow data from a .flo filename
       (vision.middlebury.edu file
           format).

         ig:
             Shortcut for command 'input_glob'.

         input_glob:
             pattern

           Insert new images from several filenames that match the specified
       glob
           pattern.
           (equivalent to shortcut command 'ig').

         input_gpl:
             filename

           Input specified filename as a .gpl palette data file.

         input_cached:
             "basename.ext",_try_downloading_from_gmic_server={ 0 | 1 }

           Input specified filename, assumed to be stored in one of the G'MIC
           resource folder.
           If file not found and 'try_downloading=1', file is downloaded from
           the G'MIC server and stored
           in the '${-path_cache}' folder.

           Default value: 'try_downloading_from_gmic_server=1'.

         input_obj:
             filename

           Input specified 3D mesh from a .obj Wavefront file.

         it:
             Shortcut for command 'input_text'.

         input_text:
             filename

           Input specified text-data filename as a new image.
           (equivalent to shortcut command 'it').

         lorem:
             _width>0,_height>0

           Input random image of specified size, retrieved from Internet.

           Default values: 'width=height=800'.

         network (+):
             mode={ -1=disabled | 0:enabled w/o timeout | >0:enabled w/
       specified
               timeout in seconds }

           Enable/disable load-from-network and set corresponding timeout.
           (Default mode is 'enabled w/o timeout').

         o (+):
             Shortcut for command 'output'.

         output (+):
             [type:]filename,_format_options

           Output selected images as one or several numbered file(s).
           (equivalent to shortcut command 'o').

           Default value: 'format_options'=(undefined).

         output_565:
             "filename",reverse_endianness={ 0:false | 1:true }

           Output selected images as raw RGB-565 files.

           Default value: 'reverse_endianness=0'.

         output_cube:
             "filename"

           Output selected CLUTs as a .cube file (Adobe CLUT format).

         output_flo:
             "filename"

           Output selected optical flow as a .flo file (vision.middlebury.edu
       file
           format).

         output_ggr:
             filename,_gradient_name

           Output selected images as .ggr gradient files (GIMP).
           If no gradient name is specified, it is deduced from the filename.

         output_gmz:
             filename,_datatype

           Output selected images as .gmz files (G'MIC native file format).
           'datatype' can be { bool | uint8 | int8 | uint16 | int16 | uint32
           | int32 | uint64 | int64 | float32 | float64 }.

         output_obj:
             filename,_save_materials={ 0:no | 1:yes }

           Output selected 3D meshes as Wavefront 3D object files.
           Set 'save_materials' to '1' to produce a corresponding
           material file ('.mtl') and eventually texture files.
           Beware, the export to '.obj' files may be quite slow for large 3D
           objects.

           Default value: 'save_materials=1'.

         ot:
             Shortcut for command 'output_text'.

         output_text:
             filename

           Output selected images as text-data filenames.
           (equivalent to shortcut command 'ot').

         on:
             Shortcut for command 'outputn'.

         outputn:
             filename,_index

           Output selected images as automatically numbered filenames in
           repeat...done loops.
           (equivalent to shortcut command 'on').

         op:
             Shortcut for command 'outputp'.

         outputp:
             prefix

           Output selected images as prefixed versions of their original
       filenames.
           (equivalent to shortcut command 'op').

           Default value: 'prefix=_'.

         ow:
             Shortcut for command 'outputw'.

         outputw:

           Output selected images by overwriting their original location.
           (equivalent to shortcut command 'ow').

         ox:
             Shortcut for command 'outputx'.

         outputx:
             extension1,_extension2,_...,_extensionN,_output_at_same_location={
       0 | 1 }

           Output selected images with same base filenames but for N different
           extensions.
           (equivalent to shortcut command 'ox').

           Default value: 'output_at_same_location=0'.

         parse_cli:
             _output_mode,_{ * | command_name }

           Parse definition of '@cli'-documented commands and output info
       about
           them in specified output mode.
           'output_mode' can be { ascii | bashcompletion | html | images |
           print }.

           Default values: 'output_mode=print' and 'command_name=*'.

         parse_gmd:

           Parse and tokenize selected images, viewed as text strings
       formatted with
           the G'MIC markdown syntax.

         gmd2html:
             _include_default_header_footer={ 0:none | 1:Reference |
       2:Tutorial |
               3:News } |
             (no arg)

           Convert selected gmd-formatted text images to html format.

           Default values: 'include_default_header_footer=1'.

         gmd2ascii:
             _max_line_length>0,_indent_forced_newlines>=0 |
             (no arg)

           Convert selected gmd-formatted text images to ascii format.

           Default values: 'max_line_length=80' and
            'indent_forced_newline=0'.

         parse_gui:
             _outputmode,_{ * | filter_name}

           Parse selected filter definitions and generate info about filters
       in
           selected output mode.
           'outputmode' can be { gmicol | images | json | list | print |
           strings | update | zart }.
           It is possible to define a custom output mode, by implementing the
           following commands
           ('outputmode' must be replaced by the name of the custom user
       output
           mode):
           . 'parse_gui_outputmode' : A command that outputs the parsing
           information with a custom format.
           . 'parse_gui_parseparams_outputmode' (optional): A simple command
           that returns 0 or 1. It tells the parser whether parameters of
       matching
           filter must be analyzed (slower) or not.
           . 'parse_gui_trigger_outputmode' (optional): A command that is
           called by the parser just before parsing the set of each matching
       filters.
           Here is the list of global variables set by the parser, accessible
       in
           command 'parse_gui_outputmode':
           '$_nb_filters': Number of matching filters.
           '$_nongui' (stored as an image): All merged lines in the file that
           do not correspond to '#@gui' lines.
           For each filter '     * '$_fF_name' : Filter name.
            * '$_fF_path' : Full path.
            * '$_fF_locale' : Filter locale (empty, if not specified).
            * '$_fF_command' : Filter command.
            * '$_fF_command_preview' : Filter preview command (empty, if not
           specified).
            * '$_fF_zoom_factor' : Default zoom factor (empty, if not
           specified).
            * '$_fF_preview_accuracy' : Preview accuracy (can be { 0:does
           not support zoom in/out | 1:support zoom in/out | 2:pixel-perfect
       }).
            * '$_fF_input_mode' : Default preferred input mode (empty, if not
           specified).
            * '$_fF_hide' : Path of filter hid by current filter (for
       localized
           filters, empty if not specified).
            * '$_fF_nb_params' : Number of parameters.
           For each parameter '    $_fF_nb_params-1]'):
            * '$_fF_pP_name' : Parameter name.
            * '$_fF_pP_type' : Parameter type.
            * '$_fF_pP_responsivity' : Parameter responsivity (can be { 0 |
           1 }).
            * '$_fF_pP_visibility' : Parameter visibility.
            * '$_fF_pP_propagation' : Propagation of the parameter visibility.
            * '$_fF_pP_nb_args' : Number of parameter arguments.
           For each argument '    $_fF_pP_nb_args-1]'):
            * '$_fF_pP_aA' : Argument value
           Default parameters: 'filter_name=*' and 'output_format=print'.

         pass (+):
             _shared_state={ -1:status only | 0:non-shared (copy) | 1:shared |
               2:adaptive }

           Insert images from parent context of a custom command or a local
           environment.
           Command selection (if any) stands for a selection of images in the
       parent
           context.
           By default (adaptive shared state), selected images are inserted in
       a
           shared state if they do not belong
           to the context (selection) of the current custom command or local
           environment as well.
           Typical use of command 'pass' concerns the design of custom
       commands
           that take images as arguments.
           This commands return the list of corresponding indices in the
       status.

           Default value: 'shared_state=2'.

           Example:
             [#1] command "average : pass$""1 add[^-1] [-1] remove[-1] div 2"
       sample
              ? +mirror y +average[0] [1]

         plot (+):
             _plot_type,_vertex_type,_xmin,_xmax,_ymin,_ymax,_exit_on_anykey={
       0 | 1 } |
             'formula',_resolution>=0,_plot_type,_vertex_type,_xmin,xmax,_ymin,_ymax,
               _exit_on_anykey={ 0 | 1 }

           Display selected images or formula in an interactive viewer (use
       the
           instant display window [0] if opened).
           'plot_type' can be { 0:none | 1:lines | 2:splines | 3:bar }.
           'vertex_type' can be { 0:none | 1:points | 2,3:crosses | 4,
           5:circles | 6,7:squares }.
           'xmin', 'xmax', 'ymin', 'ymax' set the coordinates
           of the displayed xy-axes.

           Default values: 'plot_type=1', 'vertex_type=1',
            'xmin=xmax=ymin=ymax=0 (auto)' and 'exit_on_anykey=0'.

         poincare_disk:
             _size>=0,_p>2,_q>2,_angle,_tiling={ 0:triangular | 1:polygonal },
               _nb_max_iter>=0,_xmin,_ymin,_xmax,_ymax

           Return a 3-channels image of a poincare disk. Output channels are
       '[x,y,
           it]'.

           Default values: 'size=1024', 'p=5', 'q=3',
            'angle=0', 'tiling=0', 'nb_max_iter=20',
            'xmin=ymin=-1' and 'xmax=ymax=1'.
           repeat 4 { poincare_disk 1024,{3+$>} channels[-1] 2 mod[-1] 3
           neq[-1] 2 } rescale2d 50%

         portrait:
             _size>0

           Input random portrait image of specified size, retrieved from
       Internet.

           Default values: 'size=800'.

         p:
             Shortcut for command 'print'.

         print:

           Print information on selected images, on the standard error
           ('stderr').
           (equivalent to shortcut command 'p').

           When invoked with a '+' prefix (i.e. '+print'), the command
           outputs on 'stdout' rather than on 'stderr'.

         random_pattern:
             _width>0,_height>0,_min_detail_level>=0

           Insert a new RGB image of specified size at the end of the image
       list,
           rendered with a random pattern.

           Default values: 'width=height=512' and
            'min_detail_level=2'.

           Example:
             [#1] repeat 6 { random_pattern 256 }

         screen (+):
             _x0[%],_y0[%],_x1[%],_y1[%]

           Take screenshot, optionally grabbed with specified coordinates, and
       insert
           it
           at the end of the image list.

         select (+):
             feature_type,_X[%]>=0,_Y[%]>=0,_Z[%]>=0,_exit_on_anykey={ 0 | 1
       },
               _is_deep_selection={ 0 | 1 }

           Interactively select a feature from selected images (use the
       instant
           display window [0] if opened).
           'feature_type' can be { 0:point | 1:segment | 2:rectangle |
           3:ellipse }.
           Arguments 'X','Y','Z' determine the initial selection
           view, for 3D volumetric images.
           The retrieved feature is returned as a 3D vector (if
           'feature_type==0') or as a 6d vector
           (if 'feature_type!=0') containing the feature coordinates.

           Default values: 'X=Y=Z=(undefined)', 'exit_on_anykey=0'
            and 'is_deep_selection=0'.

         serialize (+):
             _datatype,_is_compressed={ 0 | 1 },_store_names={ 0 | 1 }

           Serialize selected list of images into a single image, optionally
       in a
           compressed form.
           'datatype' can be { auto | uint8 | int8 | uint16 | int16 | uint32
           | int32 | uint64 | int64 | float32 | float64 }.
           Specify 'datatype' if all selected images have a range of values
           constrained to a particular datatype,
           in order to minimize the memory footprint.
           The resulting image has only integers values in [0,255] and can
       then be
           saved as a raw image of
           unsigned chars (doing so will output a valid .cimg[z] or .gmz
       file).
           If 'store_names' is set to '1', serialization uses the .gmz
           format to store data in memory
           (otherwise the .cimg[z] format).

           Default values: 'datatype=auto', 'is_compressed=1' and
            'store_names=1'.

           Example:
             [#1] image.jpg +serialize uint8 +unserialize[-1]

         shape_circle:
             _size>=0

           Input a 2D circle binary shape with specified size.

           Default value: 'size=512'.

           Example:
             [#1] shape_circle ,

         shape_cupid:
             _size>=0

           Input a 2D cupid binary shape with specified size.

           Default value: 'size=512'.

           Example:
             [#1] shape_cupid ,

         shape_diamond:
             _size>=0

           Input a 2D diamond binary shape with specified size.

           Default value: 'size=512'.

           Example:
             [#1] shape_diamond ,

         shape_dragon:
             _size>=0,_recursion_level>=0,_angle

           Input a 2D Dragon curve with specified size.

           Default value: 'size=512', 'recursion_level=18' and
            'angle=0'.

           Example:
             [#1] shape_dragon ,

         shape_fern:
             _size>=0,_density[%]>=0,_angle,0<=_opacity<=1,_type={ 0:Asplenium
               adiantum-nigrum | 1:Thelypteridaceae }

           Input a 2D Barnsley fern with specified size.

           Default value: 'size=512', 'density=50%',
            'angle=30', 'opacity=0.3' and 'type=0'.

           Example:
             [#1] shape_fern ,

         shape_gear:
             _size>=0,_nb_teeth>0,0<=_height_teeth<=100,0<=_offset_teeth<=100,
               0<=_inner_radius<=100

           Input a 2D gear binary shape with specified size.

           Default value: 'size=512', 'nb_teeth=12',
            'height_teeth=20', 'offset_teeth=0' and
            'inner_radius=40'.

           Example:
             [#1] shape_gear ,

         shape_heart:
             _size>=0

           Input a 2D heart binary shape with specified size.

           Default value: 'size=512'.

           Example:
             [#1] shape_heart ,

         shape_menger:
             _nb_iterations>=0

           Input a 3D voxelized representation of the Menger sponge.

           Default value: 'nb_iterations=3'.

           Example:
             [#1] shape_menger 4 surfels3d , color3d 200 m3d 3

         shape_mosely:
             _nb_iterations>=0

           Input a 3D voxelized representation of the Mosely snowflake.

           Default value: 'nb_iterations=3'.

           Example:
             [#1] shape_mosely 4 surfels3d , color3d 200 m3d 3

         shape_polygon:
             _size>=0,_nb_vertices>=3,_angle

           Input a 2D polygonal binary shape with specified geometry.

           Default value: 'size=512', 'nb_vertices=5' and
            'angle=0'.

           Example:
             [#1] repeat 6 { shape_polygon 256,{3+$>} }

         shape_rays:
             _size>=0,_xcenter[%],_ycenter[%],_branches>0,_angle[%],_twist,
               0<=_perspective<=1,_is_antialias={ 0 | 1 }

           Input a 3D binary spiral with specified size and attributes.

           Default values: 'size=512', 'xcenter=50%',
            'ycenter=50%', 'branches=7', 'angle=50%',
            'twist=0', 'perspective=0.35' and 'is_antialias=0'.

           Example:
             [#1] shape_rays 400,50%,50%,7 shape_rays 400,50%,50%,3,0,3

         shape_snowflake:
             size>=0,0<=_nb_recursions<=6

           Input a 2D snowflake binary shape with specified size.

           Default values: 'size=512' and 'nb_recursions=5'.

           Example:
             [#1] repeat 6 { shape_snowflake 256,$> }

         shape_star:
             _size>=0,_nb_branches>0,0<=_thickness<=1

           Input a 2D star binary shape with specified size.

           Default values: 'size=512', 'nb_branches=5' and
            'thickness=0.38'.

           Example:
             [#1] repeat 9 { shape_star 256,{$>+2} }

         sh (+):
             Shortcut for command 'shared'.

         shared (+):
             x0[%],x1[%],y[%],z[%],c[%] |
             y0[%],y1[%],z[%],c[%] |
             z0[%],z1[%],c[%] |
             c0[%],c1[%] |
             c0[%] |
             (no arg)

           Insert shared buffers from (opt. points/rows/planes/channels of)
       selected
           images.
           Shared buffers cannot be returned by a command, nor a local
       environment.
           (equivalent to shortcut command 'sh').

           Example:
             [#1] image.jpg shared 1 blur[-1] 3 remove[-1]
             [#2] image.jpg repeat s { shared 25%,75%,0,$> mirror[-1] x
       remove[-1] }

           Tutorial: https://gmic.eu/oldtutorial/_shared

         sp:
             Shortcut for command 'sample'.

         sample:
             _name1={ ? | apples | balloons | barbara | boats | bottles |
       butterfly |
               cameraman | car | cat | cliff | chick | colorful | david | dog
       |
               duck | eagle | elephant | earth | flower | fruits | gmicky |
               gmicky_mahvin | gmicky_wilber | greece | gummy | house | inside
       |
               landscape | leaf | lena | leno | lion | mandrill | monalisa |
               monkey | parrots | pencils | peppers | portrait0 | portrait1 |
               portrait2 | portrait3 | portrait4 | portrait5 | portrait6 |
               portrait7 | portrait8 | portrait9 | roddy | rooster | rose |
       square
               | swan | teddy | tiger | tulips | wall | waterfall | zelda
       },_name2,
               ...,_nameN,_width={ >=0 | 0 (auto) },_height = { >=0 | 0 (auto)
       } |
             (no arg)

           Input a new sample RGB image (opt. with specified size).
           (equivalent to shortcut command 'sp').

           Argument 'name' can be replaced by an integer which serves as a
           sample index.

           Example:
             [#1] repeat 6 { sample }

         srand (+):
             value |
             (no arg)

           Set random generator seed.
           If no argument is specified, a random value is used as the random
           generator seed.

         store (+):
             _is_compressed={ 0 | 1 },variable_name1,_variable_name2,...

           Store selected images into one or several named variables.
           Selected images are transferred to the variables, and are so
       removed from
           the image list.
           (except if the prepended variant of the command '+store[selection]'
           is used).
           If a single variable name is specified, all images of the selection
       are
           assigned
           to the named variable. Otherwise, there must be as many variable
       names as
           images
           in the selection, and each selected image is assigned to each
       specified
           named variable.
           Use command 'input $variable_name' to bring the stored images back
       in
           the list.

           Default value: 'is_compressed=0'.

           Example:
             [#1] sample eagle,earth store img1,img2 input $img2 $img1

           Tutorial: https://gmic.eu/tutorial/store

         testimage2d:
             _width>0,_height>0,_spectrum>0

           Input a 2D synthetic image.

           Default values: 'width=512', 'height=width' and
            'spectrum=3'.

           Example:
             [#1] testimage2d 512

         um:
             Shortcut for command 'uncommand'.

         uncommand (+):
             command_name[,_command_name2,...] |
             *

           Discard definition of specified custom commands.
           Set argument to '*' for discarding all existing custom commands.
           (equivalent to shortcut command 'um').

         uniform_distribution:
             nb_levels>=1,spectrum>=1

           Input set of uniformly distributed spectrum-d points in
       [0,1]^spectrum.

           Example:
             [#1] uniform_distribution 64,3 * 255 +distribution3d
       circles3d[-1] 10

         unserialize (+):

           Recreate lists of images from serialized image buffers, obtained
       with
           command 'serialize'.

         up:
             Shortcut for command 'update'.

         update:

           Update commands from the latest definition file on the G'MIC
       server.
           (equivalent to shortcut command 'up').

         v (+):
             Shortcut for command 'verbose'.

         verbose (+):
             level |
             { + | - }

           Set or increment/decrement the verbosity level. Default level is 0.
           (equivalent to shortcut command 'v').

           When 'level>0', G'MIC log messages are displayed on the standard
           error (stderr).

           Default value: 'level=1'.

         wait (+):
             delay |
             (no arg)

           Wait for a given delay (in ms), optionally since the last call to
           'wait'.
           or wait for a user event occurring on the selected instant display
       windows.
           'delay' can be { <0:delay+flush events | 0:event | >0:delay }.
           Command selection (if any) stands for instant display window
       indices
           instead of image indices.
           If no window indices are specified and if 'delay' is positive, the
           command results
           in a 'hard' sleep during specified delay.

           Default value: 'delay=0'.

         warn (+):
             _force_visible={ 0 | 1 },_message

           Print specified warning message, on the standard error (stderr).
           Command selection (if any) stands for displayed call stack subset
       instead
           of image indices.

         w (+):
             Shortcut for command 'window'.

         window (+):
             _width[%]>=-1,_height[%]>=-1,_normalization,_fullscreen,_pos_x[%],
               _pos_y[%],_title

           Display selected images into an instant display window with
       specified size,
            normalization type,
           fullscreen mode and title.
           (equivalent to shortcut command 'w').

           If 'width' or 'height' is set to -1, the corresponding
           dimension is adjusted to the window
           or image size.
           Specify 'pos_x' and 'pos_y' arguments only if the window has
           to be moved to the specified
           coordinates. Otherwise, they can be avoided.
           'width'=0 or 'height'=0 closes the instant display window.
           'normalization' can be { -1:keep same | 0:none | 1:always |
           2:1st-time | 3:auto }.
           'fullscreen' can be { -1:keep same | 0:no | 1:yes }.
           You can manage up to 10 different instant display windows by using
       the
           numbered variants
           'w0' (default, eq. to 'w'),'w1',...,'w9' of the
           command 'w'.
           Invoke 'window' with no selection to make the window visible, if it
           has been closed by the user.

           Default values: 'width=height=normalization=fullscreen=-1' and
            'title=(undefined)'.

         11.3. List Manipulation
               -----------------

         k (+):
             Shortcut for command 'keep'.

         keep (+):

           Keep only selected images.
           (equivalent to shortcut command 'k').

           Example:
             [#1] image.jpg split x keep[0-50%:2] append x
             [#2] image.jpg split x keep[^30%-70%] append x

         kn:
             Shortcut for command 'keep_named'.

         keep_named:
             "name1","name2",...

           Keep all images with specified names from the list of images.
           Remove all images if no images with those names exist.
           (equivalent to shortcut command 'kmn').

         mv (+):
             Shortcut for command 'move'.

         move (+):
             position[%]

           Move selected images at specified position.
           Images are actually inserted between current positions 'position-1'
           and 'position'.
           (equivalent to shortcut command 'mv').

           Example:
             [#1] image.jpg split x,3 move[1] 0
             [#2] image.jpg split x move[50%--1:2] 0 append x

         nm (+):
             Shortcut for command 'name'.

         => (+):
             Shortcut for command 'name'.

         name (+):
             "name1","name2",...,"nameN"

           Set names of selected images.
            * If no explicit image selection is given, image selection is
       assumed to
           be '[-N--1]', where 'N' is the number of specified arguments.
            * If 'N' is higher than the number of images in selection, an
       error
           is thrown.
            * If 'N' is lower than the number of images in selection, image
           names are assigned in a periodic way, i.e. 'name(selection[k]) =
           arg[k%N]'.
           (equivalent to shortcut command '=>').

           Example:
             [#1] image.jpg name image blur[image] 2

           Tutorial: https://gmic.eu/tutorial/name

         rm (+):
             Shortcut for command 'remove'.

         remove (+):

           Remove selected images.
           (equivalent to shortcut command 'rm').

           Example:
             [#1] image.jpg split x remove[30%-70%] append x
             [#2] image.jpg split x remove[0-50%:2] append x

         remove_duplicates:

           Remove duplicates images in the selected images list.

           Example:
             [#1] (1,2,3,4,2,4,3,1,3,4,2,1) split x remove_duplicates append x

         remove_empty:

           Remove empty images in the selected image list.

         rmn:
             Shortcut for command 'remove_named'.

         remove_named:
             "name1","name2",...

           Remove all images with specified names from the list of images.
           Does nothing if no images with those names exist.
           (equivalent to shortcut command 'rmn').

         rv (+):
             Shortcut for command 'reverse'.

         reverse (+):

           Reverse positions of selected images.
           (equivalent to shortcut command 'rv').

           Example:
             [#1] image.jpg split x,3 reverse[-2,-1]
             [#2] image.jpg split x,-16 reverse[50%-100%] append x

         sort_list:
             _ordering={ + | - },_criterion

           Sort list of selected images according to the specified image
       criterion.

           Default values: 'ordering=+', 'criterion=i'.

           Example:
             [#1] (1;4;7;3;9;2;4;7;6;3;9;1;0;3;3;2) split y sort_list +,i
       append y

         11.4. Mathematical Operators
               ----------------------

         abs (+):

           Compute the pointwise absolute values of selected images.

           Example:
             [#1] image.jpg +sub {ia} abs[-1]
             [#2] 300,1,1,1,'cos(20*x/w)' +abs display_graph 400,300

         acos (+):

           Compute the pointwise arccosine of selected images.

           Example:
             [#1] image.jpg +normalize -1,1 acos[-1]
             [#2] 300,1,1,1,'cut(x/w+0.1*u,0,1)' +acos display_graph 400,300

           Tutorial: https://gmic.eu/oldtutorial/trigometric-and-inverse-
       trigometric-commands

         acosh (+):

           Compute the pointwise hyperbolic arccosine of selected images.

         + (+):
             Shortcut for command 'add'.

         add (+):
             value[%] |
             [image] |
             'formula' |
             (no arg)

           Add specified value, image or mathematical expression to selected
       images,
           or compute the pointwise sum of selected images.
           (equivalent to shortcut command '+').

           Example:
             [#1] image.jpg +add 30% cut 0,255
             [#2] image.jpg +blur 5 normalize 0,255 add[1] [0]
             [#3] image.jpg add '80*cos(80*(x/w-0.5)*(y/w-0.5)+c)' cut 0,255
             [#4] image.jpg repeat 9 { +rotate[0] {$>*36},1,0,50%,50% } add
       div 10

         & (+):
             Shortcut for command 'and'.

         and (+):
             value[%] |
             [image] |
             'formula' |
             (no arg)

           Compute the bitwise AND of selected images with specified value,
       image or
           mathematical expression, or compute the pointwise sequential
       bitwise AND of
           selected images.
           (equivalent to shortcut command '&').

           Example:
             [#1] image.jpg and {128+64}
             [#2] image.jpg +mirror x and

         argmax:

           Compute the argmax of selected images. Returns a single image
           with each pixel value being the index of the input image with
       maximal
           value.

           Example:
             [#1] image.jpg sample lena,lion,square +argmax

         argmaxabs:

           Compute the argmaxabs of selected images. Returns a single image
           with each pixel value being the index of the input image with
       maxabs value.

         argmin:

           Compute the argmin of selected images. Returns a single image
           with each pixel value being the index of the input image with
       minimal
           value.

           Example:
             [#1] image.jpg sample lena,lion,square +argmin

         argminabs:

           Compute the argminabs of selected images. Returns a single image
           with each pixel value being the index of the input image with
       minabs value.

         asin (+):

           Compute the pointwise arcsine of selected images.

           Example:
             [#1] image.jpg +normalize -1,1 asin[-1]
             [#2] 300,1,1,1,'cut(x/w+0.1*u,0,1)' +asin display_graph 400,300

           Tutorial: https://gmic.eu/oldtutorial/trigometric-and-inverse-
       trigometric-commands

         asinh (+):

           Compute the pointwise hyperbolic arcsine of selected images.

         atan (+):

           Compute the pointwise arctangent of selected images.

           Example:
             [#1] image.jpg +normalize 0,8 atan[-1]
             [#2] 300,1,1,1,'4*x/w+u' +atan display_graph 400,300

           Tutorial: https://gmic.eu/oldtutorial/trigometric-and-inverse-
       trigometric-commands

         atan2 (+):
             [x_argument]

           Compute the pointwise oriented arctangent of selected images.
           Each selected image is regarded as the y-argument of the arctangent
           function, while the
           specified image gives the corresponding x-argument.

           Example:
             [#1] (-1,1) (-1;1) resize 400,400,1,1,3 atan2[1] [0] keep[1] mod
       {pi/8}

           Tutorial: https://gmic.eu/oldtutorial/trigometric-and-inverse-
       trigometric-commands

         atanh (+):

           Compute the pointwise hyperbolic arctangent of selected images.

         << (+):
             Shortcut for command 'bsl'.

         bsl (+):
             value[%] |
             [image] |
             'formula' |
             (no arg)

           Compute the bitwise left shift of selected images with specified
       value,
           image or mathematical expression, or compute the pointwise
       sequential
           bitwise left shift of selected images.
           (equivalent to shortcut command '<<').

           Example:
             [#1] image.jpg bsl 'round(3*x/w,0)' cut 0,255

         >> (+):
             Shortcut for command 'bsr'.

         bsr (+):
             value[%] |
             [image] |
             'formula' |
             (no arg)

           Compute the bitwise right shift of selected images with specified
       value,
           image or mathematical expression, or compute the pointwise
       sequential
           bitwise right shift of selected images.
           (equivalent to shortcut command '>>').

           Example:
             [#1] image.jpg bsr 'round(3*x/w,0)' cut 0,255

         cos (+):

           Compute the pointwise cosine of selected images.

           Example:
             [#1] image.jpg +normalize 0,{2*pi} cos[-1]
             [#2] 300,1,1,1,'20*x/w+u' +cos display_graph 400,300

           Tutorial: https://gmic.eu/oldtutorial/trigometric-and-inverse-
       trigometric-commands

         cosh (+):

           Compute the pointwise hyperbolic cosine of selected images.

           Example:
             [#1] image.jpg +normalize -3,3 cosh[-1]
             [#2] 300,1,1,1,'4*x/w+u' +cosh display_graph 400,300

         deg2rad:

           Convert pointwise angle values of selected images, from degrees to
       radians
           (apply 'i*pi/180').

         / (+):
             Shortcut for command 'div'.

         div (+):
             value[%] |
             [image] |
             'formula' |
             (no arg)

           Divide selected images by specified value, image or mathematical
           expression, or compute the pointwise quotient of selected images.
           (equivalent to shortcut command '/').

           Example:
             [#1] image.jpg div '1+abs(cos(x/10)*sin(y/10))'
             [#2] image.jpg +norm add[-1] 1 +div

         div_complex:
             [divider_real,divider_imag],_epsilon>=0

           Perform division of the selected complex pairs
       (real1,imag1,...,realN,
           imagN) of images by
           specified complex pair of images (divider_real,divider_imag).
           In complex pairs, the real image must be always located before the
           imaginary image in the image list.

           Default value: 'epsilon=1e-8'.

         == (+):
             Shortcut for command 'eq'.

         eq (+):
             value[%] |
             [image] |
             'formula' |
             (no arg)

           Compute the boolean equality of selected images with specified
       value,
           image or mathematical expression, or compute the boolean equality
       of
           selected images.
           (equivalent to shortcut command '==').

           Example:
             [#1] image.jpg round 40 eq {round(ia,40)}
             [#2] image.jpg +mirror x eq

         erf (+):

           Compute the pointwise error function of selected images.

           Example:
             [#1] image.jpg +normalize 0,2 erf[-1]
             [#2] 300,1,1,1,'7*x/w-3.5+u' +erf display_graph 400,300

         exp (+):

           Compute the pointwise exponential of selected images.

           Example:
             [#1] image.jpg +normalize 0,2 exp[-1]
             [#2] 300,1,1,1,'7*x/w+u' +exp display_graph 400,300

         >= (+):
             Shortcut for command 'ge'.

         ge (+):
             value[%] |
             [image] |
             'formula' |
             (no arg)

           Compute the boolean 'greater or equal than' of selected images with
           specified value, image
           or mathematical expression, or compute the boolean 'greater or
       equal than'
           of selected images.
           (equivalent to shortcut command '>=').

           Example:
             [#1] image.jpg ge {ia}
             [#2] image.jpg +mirror x ge

         > (+):
             Shortcut for command 'gt'.

         gt (+):
             value[%] |
             [image] |
             'formula' |
             (no arg)

           Compute the boolean 'greater than' of selected images with
       specified value,
            image or mathematical expression, or compute the boolean 'greater
       than' of
           selected images.
           (equivalent to shortcut command '>').

           Example:
             [#1] image.jpg gt {ia}
             [#2] image.jpg +mirror x gt

         <= (+):
             Shortcut for command 'le'.

         le (+):
             value[%] |
             [image] |
             'formula' |
             (no arg)

           Compute the boolean 'less or equal than' of selected images with
       specified
           value, image or mathematical expression, or compute the boolean
       'less or
           equal than' of selected images.
           (equivalent to shortcut command '<=').

           Example:
             [#1] image.jpg le {ia}
             [#2] image.jpg +mirror x le

         < (+):
             Shortcut for command 'lt'.

         lt (+):
             value[%] |
             [image] |
             'formula' |
             (no arg)

           Compute the boolean 'less than' of selected images with specified
       value,
           image or mathematical expression, or compute the boolean 'less
       than' of
           selected images.
           (equivalent to shortcut command '<').

           Example:
             [#1] image.jpg lt {ia}
             [#2] image.jpg +mirror x lt

         log (+):

           Compute the pointwise base-e logarithm of selected images.

           Example:
             [#1] image.jpg +add 1 log[-1]
             [#2] 300,1,1,1,'7*x/w+u' +log display_graph 400,300

         log10 (+):

           Compute the pointwise base-10 logarithm of selected images.

           Example:
             [#1] image.jpg +add 1 log10[-1]
             [#2] 300,1,1,1,'7*x/w+u' +log10 display_graph 400,300

         log2 (+):

           Compute the pointwise base-2 logarithm of selected images

           Example:
             [#1] image.jpg +add 1 log2[-1]
             [#2] 300,1,1,1,'7*x/w+u' +log2 display_graph 400,300

         max (+):
             value[%] |
             [image] |
             'formula' |
             (no arg)

           Compute the maximum between selected images and specified value,
       image or
           mathematical expression, or compute the pointwise maxima between
       selected
           images.

           Example:
             [#1] image.jpg +mirror x max
             [#2] image.jpg max 'R=((x/w-0.5)^2+(y/h-0.5)^2)^0.5;255*R'

         maxabs (+):
             value[%] |
             [image] |
             'formula' |
             (no arg)

           Compute the maxabs between selected images and specified value,
       image or
           mathematical expression, or compute the pointwise maxabs between
       selected
           images.

         m/ (+):
             Shortcut for command 'mdiv'.

         mdiv (+):
             value[%] |
             [image] |
             'formula' |
             (no arg)

           Compute the matrix division of selected matrices/vectors by
       specified
           value, image or mathematical expression, or compute the matrix
       division of
           selected images.
           (equivalent to shortcut command 'm/').

         med:

           Compute the median of selected images.

           Example:
             [#1] image.jpg sample lena,lion,square +med

         min (+):
             value[%] |
             [image] |
             'formula' |
             (no arg)

           Compute the minimum between selected images and specified value,
       image or
           mathematical expression, or compute the pointwise minima between
       selected
           images.

           Example:
             [#1] image.jpg +mirror x min
             [#2] image.jpg min 'R=((x/w-0.5)^2+(y/h-0.5)^2)^0.5;255*R'

         minabs (+):
             value[%] |
             [image] |
             'formula' |
             (no arg)

           Compute the minabs between selected images and specified value,
       image or
           mathematical expression, or compute the pointwise minabs between
       selected
           images.

         % (+):
             Shortcut for command 'mod'.

         mod (+):
             value[%] |
             [image] |
             'formula' |
             (no arg)

           Compute the modulo of selected images with specified value, image
       or
           mathematical expression, or compute the pointwise sequential modulo
       of
           selected images.
           (equivalent to shortcut command '%').

           Example:
             [#1] image.jpg +mirror x n. 1,255 round. mod
             [#2] image.jpg mod 'R=((x/w-0.5)^2+(y/h-0.5)^2)^0.5;255*R'

         m* (+):
             Shortcut for command 'mmul'.

         mmul (+):
             value[%] |
             [image] |
             'formula' |
             (no arg)

           Compute the matrix right multiplication of selected
       matrices/vectors by
           specified value, image or mathematical expression, or compute the
       matrix
           right multiplication of selected images.
           (equivalent to shortcut command 'm*').

           Example:
             [#1] (0,1,0;0,0,1;1,0,0) (1;2;3) +mmul

         * (+):
             Shortcut for command 'mul'.

         mul (+):
             value[%] |
             [image] |
             'formula' |
             (no arg)

           Multiply selected images by specified value, image or mathematical
           expression, or compute the pointwise product of selected images.
           (equivalent to shortcut command '*').

           See also: add, sub, div.

           Example:
             [#1] image.jpg +mul 2 cut 0,255
             [#2] image.jpg (1,2,3,4,5,6,7,8) ri[-1] [0] mul[0] [-1]
             [#3] image.jpg mul '1-3*abs(x/w-0.5)' cut 0,255
             [#4] image.jpg +luminance negate[-1] +mul

         mul_channels:
             value1,_value2,...,_valueN

           Multiply channels of selected images by specified sequence of
       values.

           Example:
             [#1] image.jpg +mul_channels 1,0.5,0.8

         mul_complex:
             [multiplier_real,multiplier_imag]

           Perform multiplication of the selected complex pairs
       (real1,imag1,...,
           realN,imagN) of images by
           specified complex pair of images (multiplier_real,multiplier_imag).
           In complex pairs, the real image must be always located before the
           imaginary image in the image list.

         != (+):
             Shortcut for command 'neq'.

         neq (+):
             value[%] |
             [image] |
             'formula' |
             (no arg)

           Compute the boolean inequality of selected images with specified
       value,
           image or mathematical expression, or compute the boolean inequality
       of
           selected images.
           (equivalent to shortcut command '!=').

           Example:
             [#1] image.jpg round 40 neq {round(ia,40)}

         | (+):
             Shortcut for command 'or'.

         or (+):
             value[%] |
             [image] |
             'formula' |
             (no arg)

           Compute the bitwise OR of selected images with specified value,
       image or
           mathematical expression, or compute the pointwise sequential
       bitwise OR of
           selected images.
           (equivalent to shortcut command '|').

           Example:
             [#1] image.jpg or 128
             [#2] image.jpg +mirror x or

         ^ (+):
             Shortcut for command 'pow'.

         pow (+):
             value[%] |
             [image] |
             'formula' |
             (no arg)

           Raise selected images to the power of specified value, image or
           mathematical expression, or compute the pointwise sequential powers
       of
           selected images.
           (equivalent to shortcut command '^').

           Example:
             [#1] image.jpg div 255 +pow 0.5 mul 255
             [#2] image.jpg gradient pow 2 add pow 0.2

         rad2deg:

           Convert pointwise angle values of selected images, from radians to
       degrees
           (apply 'i*180/pi').

         rol (+):
             value[%] |
             [image] |
             'formula' |
             (no arg)

           Compute the bitwise left rotation of selected images with specified
       value,
           image or mathematical expression, or compute the pointwise
       sequential
           bitwise left rotation of selected images.

           Example:
             [#1] image.jpg rol 'round(3*x/w,0)' cut 0,255

         ror (+):
             value[%] |
             [image] |
             'formula' |
             (no arg)

           Compute the bitwise right rotation of selected images with
       specified value,
            image or mathematical expression, or compute the pointwise
       sequential
           bitwise right rotation of selected images.

           Example:
             [#1] image.jpg ror 'round(3*x/w,0)' cut 0,255

         sign (+):

           Compute the pointwise sign of selected images.

           Example:
             [#1] image.jpg +sub {ia} sign[-1]
             [#2] 300,1,1,1,'cos(20*x/w+u)' +sign display_graph 400,300

         sin (+):

           Compute the pointwise sine of selected images.

           Example:
             [#1] image.jpg +normalize 0,{2*pi} sin[-1]
             [#2] 300,1,1,1,'20*x/w+u' +sin display_graph 400,300

           Tutorial: https://gmic.eu/oldtutorial/trigometric-and-inverse-
       trigometric-commands

         sinc (+):

           Compute the pointwise sinc function of selected images.

           Example:
             [#1] image.jpg +normalize {-2*pi},{2*pi} sinc[-1]
             [#2] 300,1,1,1,'20*x/w+u' +sinc display_graph 400,300

         sinh (+):

           Compute the pointwise hyperbolic sine of selected images.

           Example:
             [#1] image.jpg +normalize -3,3 sinh[-1]
             [#2] 300,1,1,1,'4*x/w+u' +sinh display_graph 400,300

         sqr (+):

           Compute the pointwise square function of selected images.

           Example:
             [#1] image.jpg +sqr
             [#2] 300,1,1,1,'40*x/w+u' +sqr display_graph 400,300

         sqrt (+):

           Compute the pointwise square root of selected images.

           Example:
             [#1] image.jpg +sqrt
             [#2] 300,1,1,1,'40*x/w+u' +sqrt display_graph 400,300

         - (+):
             Shortcut for command 'sub'.

         sub (+):
             value[%] |
             [image] |
             'formula' |
             (no arg)

           Subtract specified value, image or mathematical expression to
       selected
           images, or compute the pointwise difference of selected images.
           (equivalent to shortcut command '-').

           Example:
             [#1] image.jpg +sub 30% cut 0,255
             [#2] image.jpg +mirror x sub[-1] [0]
             [#3] image.jpg sub 'i(w/2+0.9*(x-w/2),y)'
             [#4] image.jpg +mirror x sub

         tan (+):

           Compute the pointwise tangent of selected images.

           Example:
             [#1] image.jpg +normalize {-0.47*pi},{0.47*pi} tan[-1]
             [#2] 300,1,1,1,'20*x/w+u' +tan display_graph 400,300

           Tutorial: https://gmic.eu/oldtutorial/trigometric-and-inverse-
       trigometric-commands

         tanh (+):

           Compute the pointwise hyperbolic tangent of selected images.

           Example:
             [#1] image.jpg +normalize -3,3 tanh[-1]
             [#2] 300,1,1,1,'4*x/w+u' +tanh display_graph 400,300

         xor (+):
             value[%] |
             [image] |
             'formula' |
             (no arg)

           Compute the bitwise XOR of selected images with specified value,
       image or
           mathematical expression, or compute the pointwise sequential
       bitwise XOR of
           selected images.

           Example:
             [#1] image.jpg xor 128
             [#2] image.jpg +mirror x xor

         11.5. Values Manipulation
               -------------------

         apply_curve:
             0<=smoothness<=1,x0,y0,x1,y1,x2,y2,...,xN,yN

           Apply curve transformation to image values.

           Default values: 'smoothness=1', 'x0=0', 'y0=100'.

           Example:
             [#1] image.jpg +apply_curve 1,0,0,128,255,255,0

         apply_gamma:
             gamma>=0

           Apply gamma correction to selected images.

           Example:
             [#1] image.jpg +apply_gamma 2

         balance_gamma:
             _ref_color1,...

           Compute gamma-corrected color balance of selected image, with
       respect to
           specified reference color.

           Default value: 'ref_color1=128'.

           Example:
             [#1] image.jpg +balance_gamma 128,64,64

         cast:
             datatype_source,datatype_target

           Cast datatype of image buffer from specified source type to
       specified
           target type.
           'datatype_source' and 'datatype_target' can be { uint8 |
           int8 | uint16 | int16 | uint32 | int32 | uint64 | int64 | float32 |
       float64
           }.

         complex2polar:

           Compute complex to polar transforms of selected images.

           Example:
             [#1] image.jpg +fft complex2polar[-2,-1] log[-2] shift[-2]
       50%,50%,0,0,
              2 remove[-1]

         compress_clut:

           Compress selected color LUTs as sequences of colored keypoints.

         compress_huffman:
             [huffman_tree],_max_leaf_value

           Compress selected images with Huffman coding.
           See also: decompress_huffman, huffman_tree.

         huffman_tree:

           Generate Huffman coding tree from the statistics of all selected
       images.
           Huffman tree is returned as a 1xN image inserted at the end of the
       image
           list, representing the 'N' vector-valued leafs/nodes of the tree,
           encoded as '[ value,parent,child0,child1 ]'.
           Last row of the returned image corresponds to the tree root.
           Selected images must contain only positive integer values.
           Return maximal value of the input data in the status.
           See also: compress_huffman, decompress_huffman.

         compress_rle:
             _is_binary_data={ 0 | 1 },_maximum_sequence_length>=0

           Compress selected images as 2xN data matrices, using RLE algorithm.
           Set 'maximum_sequence_length=0' to disable maximum length
       constraint.

           Default values: 'is_binary_data=0' and
            'maximum_sequence_length=0'.

           Example:
             [#1] image.jpg rescale2d ,100 quantize 4 round +compress_rle ,
              +decompress_rle[-1]

         cumulate (+):
             { x | y | z | c }...{ x | y | z | c } |
             (no arg)

           Compute the cumulative function of specified image data, optionally
       along
           the specified axes.

           Example:
             [#1] image.jpg +histogram 256 +cumulate[-1] display_graph[-2,-1]
       400,
              300,3

         c (+):
             Shortcut for command 'cut'.

         cut (+):
             { value0[%] | [image0] },{ value1[%] | [image1] } |
             [image]

           Cut values of selected images in specified range.
           (equivalent to shortcut command 'c').

           Example:
             [#1] image.jpg +add 30% cut[-1] 0,255
             [#2] image.jpg +cut 25%,75%

         decompress_clut:
             _width>0,_height>0,_depth>0

           Decompress selected colored keypoints into 3D CLUTs, using a mixed
       RBF/PDE
           approach.

           Default values: 'width=height=depth=33' and
            'reconstruction_colorspace=0'.

         decompress_from_keypoints:
             _width>0,_height>0,_depth>0 |
             (no arg)

           Decompress selected sets of keypoints as images (opt. of specified
       size).
           A set of keypoints is defined as a vector-valued image, such that:
            * The first pixel is a vector which encodes the '[
       Width,Height,Depth
           ]' of the decompressed image.
            * The second pixel is a vector which encodes '[ Min,Max,Use_RBF
       ]',
           where 'Min' and 'Max' defines the value range of the
           decompressed image, and 'Use_RBF' tells is the decompression scheme
           must use RBFs ('Use_RBF=1') or Multiscale Diffusion PDE's
           ('Use_RBF=0').
            * The remaining pixels define the keypoint coordinates and values,
       as:
              -  '[ x_k,y_k,z_k, v1_k,...,vN_k ]' for a 3D target image of
           N-valued vectors.
              -  '[ x_k,y_k, v1_k,...,vN_k ]' for a 2D target image of N-
       valued
           vectors.
              -  '[ x_k, v1_k,...,vN_k ]' for a 1D target image of N-valued
           vectors.
           where the coordinates 'x_k', 'y_k' and 'z_k' are defined
           respectively in ranges '[0,Width-1]', '[0,Height-1]' and '[0,
           Depth-1]'.
           If the 'width', 'height' and 'depth' arguments are
           provided, they define the size of the decompressed image, :
       overriding then
           the original image size '[ Width,Height,Depth ]' defined in the
           keypoints header.

         decompress_huffman:
             [huffman_tree]

           Decompress selected images with Huffman decoding.
           See also: compress_huffman, huffman_tree.

           Example:
             [#1] image.jpg huffman_tree compress_huffman.. .
       +decompress_huffman.. .

         decompress_rle:

           Decompress selected data vectors, using RLE algorithm.

         discard (+):
             _value1,_value2,... |
             { x | y | z | c}...{ x | y | z | c},_value1,_value2,... |
             (no arg)

           Discard specified values in selected images or discard neighboring
           duplicate values,
           optionally only for the values along the first of a specified axis.
           If no arguments are specified, neighboring duplicate values are
       discarded.
           If all pixels of a selected image are discarded, an empty image is
           returned.

           Example:
             [#1] (1;2;3;4;3;2;1) +discard 2
             [#2] (1,2,2,3,3,3,4,4,4,4) +discard x

         eigen2tensor:

           Recompose selected pairs of eigenvalues/eigenvectors as 2x2 or 3x3
       tensor
           fields.

           Tutorial: https://gmic.eu/tutorial/eigen2tensor

         endian (+):
             _datatype

           Reverse data endianness of selected images, eventually considering
       the
           pixel being of the specified datatype.
           'datatype' can be { bool | uint8 | int8 | uint16 | int16 | uint32
           | int32 | uint64 | int64 | float32 | float64 }.
           This command does nothing for 'bool', 'uint8' and 'int8'
           datatypes.

         equalize (+):
             _nb_levels>0[%],_value_min[%],_value_max[%] |
             (no arg)

           Equalize histograms of selected images.
           If value range is specified, the equalization is done only for
       pixels in
           the specified
           value range.

           Default values: 'nb_levels=256', 'value_min=0%' and
            'value_max=100%'.

           Example:
             [#1] image.jpg +equalize
             [#2] image.jpg +equalize 4,0,128

         f (+):
             Shortcut for command 'fill'.

         fill (+):
             value1,_value2,... |
             [image] |
             'formula'

           Fill selected images with values read from the specified value
       list,
           existing image
           or mathematical expression. Single quotes may be omitted in
           'formula'.
           (equivalent to shortcut command 'f').

           Example:
             [#1] 4,4 fill 1,2,3,4,5,6,7
             [#2] 4,4 (1,2,3,4,5,6,7) fill[-2] [-1]
             [#3] 400,400,1,3 fill "X=x-w/2; Y=y-h/2; R=sqrt(X^2+Y^2);
       a=atan2(Y,X);
              R<=180?255*abs(cos(c+200*(x/w-0.5)*(y/h-0.5))):850*(a%(0.1*(c
              +1)))"

           Tutorial: https://gmic.eu/tutorial/fill

         index (+):
             { [palette] | palette_name },0<=_dithering<=1,_map_colors={ 0 | 1
       }

           Index selected vector-valued images by specified vector-valued
       palette.
           'palette_name' can be { default | hsv | lines | hot | cool | jet
           | flag | cube | rainbow | algae | amp |balance | curl | deep |
       delta |
           dense | diff | haline | ice | matter | oxy | phase | rain | solar |
       speed |
           tarn |tempo | thermal | topo | turbid | aurora | hocuspocus | srb2
       | uzebox
           }

           Default values: 'dithering=0' and 'map_colors=0'.

           Example:
             [#1] image.jpg +index 1,1,1
             [#2] image.jpg (0;255;255^0;128;255^0;0;255) +index[-2] [-1],1,1

           Tutorial: https://gmic.eu/tutorial/gindex

         ir:
             Shortcut for command 'inrange'.

         inrange:
             min[%],max[%],_include_min_boundary={ 0:no | 1:yes },
               _include_max_boundary={ 0:no | 1:yes }

           Detect pixels whose values are in specified range '[min,max]', in
           selected images.
           (equivalent to shortcut command 'ir').

           Default value: 'include_min_boundary=include_max_boundary=1'.

           Example:
             [#1] image.jpg +inrange 25%,75%

         map (+):
             [palette],_boundary_conditions |
             palette_name,_boundary_conditions

           Map specified vector-valued palette to selected indexed images.
           Each output image has 'M*N' channels, where 'M' and 'N'
           are the numbers of channels of, respectively, the corresponding
       input image
           and the 'palette' image.
           'palette_name' can be { default | hsv | lines | hot | cool | jet
           | flag | cube | rainbow | algae | amp | balance | curl | deep |
       delta |
           dense | diff | gray | haline | ice | matter | oxy | phase | rain |
       solar |
           speed | tarn | tempo | thermal | topo | turbid | aurora |
       hocuspocus | srb2
           | uzebox }
           'boundary_conditions' can be { 0:dirichlet | 1:neumann |
           2:periodic | 3:mirror }.

           Default value: 'boundary_conditions=0'.

           Example:
             [#1] image.jpg +luminance map[-1] 3
             [#2] image.jpg +rgb2ycbcr split[-1] c (0,255,0) resize[-1]
       256,1,1,1,3
              map[-4] [-1] remove[-1] append[-3--1] c ycbcr2rgb[-1]

           Tutorial: https://gmic.eu/tutorial/map

         mix_channels:
             (a00,...,aMN) |
             [matrix]

           Apply specified matrix to channels of selected images.

           Example:
             [#1] image.jpg +mix_channels (0,1,0;1,0,0;0,0,1)

         negate:
             base_value |
             (no arg)

           Negate image values.

           Default value: 'base_value=(undefined)'.

           Example:
             [#1] image.jpg +negate

         noise (+):
             amplitude>=0[%],_noise_type

           Add random noise to selected images.
           'noise_type' can be { 0:gaussian | 1:uniform | 2:salt&pepper |
           3:poisson | 4:rice }.

           Default value: 'noise_type=0'.

           Example:
             [#1] image.jpg +noise[0] 50,0 +noise[0] 50,1 +noise[0] 10,2 cut
       0,255
             [#2] 300,300,1,3 [0] noise[0] 20,0 noise[1] 20,1 +histogram 100
              display_graph[-2,-1] 400,300,3

         noise_perlin:
             _scale_x[%]>0,_scale_y[%]>0,_scale_z[%]>0,_seed_x,_seed_y,_seed_z

           Render 2D or 3D Perlin noise on selected images, from specified
           coordinates.
           The Perlin noise is a specific type of smooth noise,
           described here : https://en.wikipedia.org/wiki/Perlin_noise.

           Default values: 'scale_x=scale_y=scale_z=16' and
            'seed_x=seed_y=seed_z=0'.

           Example:
             [#1] 500,500,1,3 noise_perlin ,

         noise_poissondisk:
             _radius[%]>0,_max_sample_attempts>0,_p_norm>0

           Add poisson disk sampling noise to selected images.
           Implements the algorithm from the article "Fast Poisson Disk
       Sampling in
           Arbitrary Dimensions",
           by Robert Bridson (SIGGRAPH'2007).

           Default values: 'radius=8', 'max_sample_attempts=30' and
            'p_norm=2'.

           Example:
             [#1] 300,300 noise_poissondisk 8

         normp:
             p>=0

           Compute the pointwise Lp-norm norm of vector-valued pixels in
       selected
           images.

           Default value: 'p=2'.

           Example:
             [#1] image.jpg +normp[0] 0 +normp[0] 1 +normp[0] 2 +normp[0] inf

         norm1:

           Compute the pointwise L1-norm of vector-valued pixels in selected
       images.

           Example:
             [#1] image.jpg +norm1

           Tutorial: https://gmic.eu/tutorial/norm1

         norm:
             Shortcut for command 'norm2'.

         norm2:

           Compute the pointwise L2-norm (euclidean norm) of vector-valued
       pixels in
           selected images.

           Example:
             [#1] image.jpg +norm

           Tutorial: https://gmic.eu/tutorial/norm2

         n (+):
             Shortcut for command 'normalize'.

         normalize (+):
             { value0[%] | [image0] },{ value1[%] | [image1]
       },_constant_case_ratio |
             [image]

           Linearly normalize values of selected images in specified range.
           (equivalent to shortcut command 'n').

           Example:
             [#1] image.jpg split x,2 normalize[-1] 64,196 append x

           Tutorial: https://gmic.eu/tutorial/normalize

         normalize_l2:

           Normalize selected images such that they have a unit L2 norm.

         normalize_sum:

           Normalize selected images such that they have a unit sum.

           Example:
             [#1] image.jpg +histogram 256 normalize_sum[-1] display_graph[-1]
       400,
              300

         not:

           Apply boolean not operation on selected images.

           Example:
             [#1] image.jpg +ge 50% +not[-1]

         orientation:

           Compute the pointwise orientation of vector-valued pixels in
       selected
           images.

           Example:
             [#1] image.jpg +orientation +norm[-2] negate[-1] mul[-2] [-1]
              reverse[-2,-1]

           Tutorial: https://gmic.eu/tutorial/orientation

         oneminus:

           For each selected image, compute one minus image.

           Example:
             [#1] image.jpg normalize 0,1 +oneminus

         otsu:
             _nb_levels>0

           Hard-threshold selected images using Otsu's method.
           The computed thresholds are returned as a list of values in the
       status.

           Default value: 'nb_levels=256'.

           Example:
             [#1] image.jpg luminance +otsu ,

         polar2complex:

           Compute polar to complex transforms of selected images.

         quantize:
             nb_levels>=1,_keep_values={ 0 | 1 },_quantization_type={
       -1:median-cut |
               0:k-means | 1:uniform }

           Quantize selected images.

           Default value: 'keep_values=1' and 'quantization_type=0'.

           Example:
             [#1] image.jpg luminance +quantize 3
             [#2] 200,200,1,1,'cos(x/10)*sin(y/10)' +quantize[0] 6
       +quantize[0] 4
              +quantize[0] 3 +quantize[0] 2

         quantize_area:
             _min_area>0

           Quantize selected images such that each flat region has an area
       greater or
           equal to 'min_area'.

           Default value: 'min_area=10'.

           Example:
             [#1] image.jpg quantize 3 +blur 1 round[-1] +quantize_area[-1] 2

         rand (+):
             { value0[%] | [image0] },_{ value1[%] | [image1]
       },_[pdf],_precision |
             [image]

           Fill selected images with random values in the specified range.
           If no '[pdf]' (probability density function) is specified, random
           values follow a uniform distribution.
           Argument 'precision' tells about the number of distinct values that
           can be generated when a '[pdf]' is specified.

           Example:
             [#1] 400,400,1,3 rand -10,10 +blur 10 sign[-1]
             [#2] (8,2,1) 50,50 rand[-1] 0,255,[-2]
             [#3] 256 gaussian[-1] 30 line[-1] 47%,0,53%,0,1,0 500,500
       rand[-1] 0,
              255,[-2] +histogram[-1] 256 display_graph[0,2] 640,480,3,0

         rand_sum:
             sum>0,_random_function

           Fill selected images with strictly positive, random, integer
       values, that
           sums to 'sum'.
           For each image, 'sum' must be greater or equal than
           'width*height*depth*spectrum'.

           Default value: 'random_function=u'.

           Example:
             [#1] 100 rand_sum 1000

         replace:
             source,target

           Replace pixel values in selected images.

           Example:
             [#1] (1;2;3;4) +replace 2,3

         replace_inf:
             _expression

           Replace all infinite values in selected images by specified
       expression.

           Example:
             [#1] (0;1;2) log +replace_inf 2

         replace_infnan:
             _expression

           Replace all NaN and infinite values in selected images by specified
           expression.

         replace_nan:
             _expression

           Replace all NaN values in selected images by specified expression.

           Example:
             [#1] (-1;0;2) sqrt +replace_nan 2

         replace_seq:
             "search_seq","replace_seq"

           Search and replace a sequence of values in selected images.

           Example:
             [#1] (1;2;3;4;5) +replace_seq "2,3,4","7,8"

         replace_str:
             "search_str","replace_str"

           Search and replace a string in selected images (viewed as strings,
       i.e.
           sequences of character codes).

           Example:
             [#1] ('"Hello there, how are you ?"') +replace_str "Hello
       there","Hi
              David"

         round (+):
             rounding_value>=0,_rounding_type |
             (no arg)

           Round values of selected images.
           'rounding_type' can be { -1:backward | 0:nearest | 1:forward }.

           Default value: 'rounding_type=0'.

           Example:
             [#1] image.jpg +round 100
             [#2] image.jpg mul {pi/180} sin +round

         roundify:
             gamma>=0

           Apply roundify transformation on float-valued data, with specified
       gamma.

           Default value: 'gamma=0'.

           Example:
             [#1] 1000 fill '4*x/w' repeat 5 { +roundify[0] {$>*0.2} } append
       c
              display_graph 400,300

         = (+):
             Shortcut for command 'set'.

         set (+):
             value,_x[%],_y[%],_z[%],_c[%]

           Set pixel value in selected images, at specified coordinates.
           (equivalent to shortcut command '=').

           If specified coordinates are outside the image bounds, no action is
           performed.

           Default values: 'x=y=z=c=0'.

           Example:
             [#1] 2,2 set 1,0,0 set 2,1,0 set 3,0,1 set 4,1,1
             [#2] image.jpg repeat 10000 { set
       255,{u(100)}%,{u(100)}%,0,{u(100)}% }

         threshold:
             value[%],_is_soft={ 0 | 1 } :

           Threshold values of selected images.
           'soft' can be { 0:hard-thresholding | 1:soft-thresholding }.

           Default value: 'is_soft=0'.

           Example:
             [#1] image.jpg +threshold[0] 50% +threshold[0] 50%,1

           Tutorial: https://gmic.eu/tutorial/threshold

         vector2tensor:

           Convert selected vector fields to corresponding tensor fields.

         11.6. Colors
               ------

         adjust_colors:
             -100<=_brightness<=100,-100<=_contrast<=100,-100<=_gamma<=100,
               -100<=_hue_shift<=100,-100<=_saturation<=100,_value_min,_value_max

           Perform a global adjustment of colors on selected images.
           Range of correct image values are considered to be in [value_min,
           value_max] (e.g. [0,255]).
           If 'value_min==value_max==0', value range is estimated from min/max
           values of selected images.
           Processed images have pixel values constrained in
       [value_min,value_max].

           Default values: 'brightness=0', 'contrast=0',
            'gamma=0', 'hue_shift=0', 'saturation=0',
            'value_min=value_max=0'.

           Example:
             [#1] image.jpg +adjust_colors 0,30,0,0,30

         ac:
             Shortcut for command 'apply_channels'.

         apply_channels:
             "command",color_channels,_value_action={ 0:none | 1:cut |
       2:normalize }

           Apply specified command on the chosen color channel(s) of each
       selected
           images.
           (equivalent to shortcut command 'ac').

           Argument 'color_channels' refers to a colorspace, and can be
           basically one of
           { all | rgba | [s]rgb | ryb | lrgb | ycbcr | lab | lch | hsv | hsi
       |
           hsl | cmy | cmyk | yiq }.
           You can also make the processing focus on a few particular channels
       of
           this colorspace,
           by setting 'color_channels' as 'colorspace_channel' (e.g.
           'hsv_h' for the hue).
           All channel values are considered to be provided in the [0,255]
       range.

           Default value: 'value_action=0'.

           Example:
             [#1] image.jpg +apply_channels "equalize blur 2",ycbcr_cbcr

         autoindex:
             nb_colors>0,0<=_dithering<=1,_method={ 0:median-cut | 1:k-means }

           Index selected vector-valued images by adapted colormaps.

           Default values: 'dithering=0' and 'method=1'.

           Example:
             [#1] image.jpg +autoindex[0] 4 +autoindex[0] 8 +autoindex[0] 16

         bayer2rgb:
             _GM_smoothness,_RB_smoothness1,_RB_smoothness2

           Transform selected RGB-Bayer sampled images to color images.

           Default values: 'GM_smoothness=RB_smoothness=1' and
            'RB_smoothness2=0.5'.

           Example:
             [#1] image.jpg rgb2bayer 0 +bayer2rgb 1,1,0.5

         clut:
             "clut_name",_resolution>0,_cut_and_round={ 0:no | 1:yes }

           Insert one of the 1149 pre-defined CLUTs at the end of the image
       list.
           'clut_name' can be { 12_years_a_slave | 1917 | 2-strip-process |
           60s | 60s_faded | 60s_faded_alt | 7drk_21 | action_magenta_01 |
           action_red_01 | ad_astra | adventure_1453 | agfa_apx_100 |
       agfa_apx_25 |
           agfa_precisa_100 | agfa_ultra_color_100 | agfa_vista_200 |
           agressive_highligjtes_recovery_5 | aladdin | alberto_street |
       alien_green |
           ampio | amstragram | amstragram+ | analog_film_1 |
       analogfx_anno_1870_color
           | analogfx_old_style_i | analogfx_old_style_ii |
       analogfx_old_style_iii |
           analogfx_sepia_color | analogfx_soft_sepia_i |
       analogfx_soft_sepia_ii |
           anime | ant-man | apocalypse_this_very_moment | aqua |
       aqua_and_orange_dark
           | aquaman | arabica_12 | asistas | atomic_pink | atusa | autumn |
           autumn_leaves | ava_614 | avalanche | avengers_endgame | azrael_93
       |
           baby_driver | bad_boys_for_life | basuco | bboyz_2 | bc_darkum |
           beach_aqua_orange | beach_faded_analog | beati |
       beauty_and_the_beast |
           berlin_sky | bisogno | black_and_white | black_panther | black_star
       |
           black_white_01 | black_white_02 | black_white_03 | black_white_04 |
           black_white_05 | black_white_06 | blade_runner | bleach_bypass |
           bleachbypass_1 | bleachbypass_2 | bleachbypass_3 | bleachbypass_4 |
           bleech_bypass_green | bleech_bypass_yellow_01 | blue_cold_fade |
       blue_dark
           | blue_house | blue_ice | blue_love_39 | blue_mono |
       blue_shadows_01 |
           bluearchitecture | bluehour | blues | bob_ford | bohemian_rhapsody
       |
           bombshell | bourbon_64 | boyado | bright_green_01 |
       bright_teal_orange |
           bright_warm | brightgreen | brown_mobster | brownbm | brownish |
       bw_1 |
           bw_10 | bw_2 | bw_3 | bw_4 | bw_5 | bw_6 | bw_7 | bw_8 | bw_9 |
           bw_but_yellow | byers_11 | calidum | candlelight | captain_marvel |
       caribe
           | chemical_168 | chrome_01 | cineblue | cinebm_4k | cinema |
       cinema_2 |
           cinema_3 | cinema_4 | cinema_5 | cinema_noir | cinematic-1 |
       cinematic-10 |
           cinematic-2 | cinematic-3 | cinematic-4 | cinematic-5 | cinematic-6
       |
           cinematic-7 | cinematic-8 | cinematic-9 | cinematic_01 |
       cinematic_02 |
           cinematic_03 | cinematic_04 | cinematic_05 | cinematic_06 |
       cinematic_07 |
           cinematic_for_flog | cinematic_forest | cinematic_lady_bird |
           cinematic_mexico | city | city_7 | city_dust | city_of_god |
           classic_films_01 | classic_films_02 | classic_films_03 |
       classic_films_04 |
           classic_films_05 | classic_teal_and_orange | clayton_33 | clear |
           clear_teal_fade | clouseau_54 | cobi_3 | coffee_44 |
       cold_clear_blue |
           cold_clear_blue_1 | cold_ice | cold_simplicity_2 | coldchrome |
       color_rich
           | colore | colorful_0209 | colornegative | conflict_01 |
       contrail_35 |
           contrast_with_highlights_protection | contrasty_afternoon |
       contrasty_green
           | convold | cosa | creed_2 | crispautumn | crispromance | crispwarm
       |
           crispwinter | cross_process_cp_130 | cross_process_cp_14 |
           cross_process_cp_15 | cross_process_cp_16 | cross_process_cp_18 |
           cross_process_cp_3 | cross_process_cp_4 | cross_process_cp_6 |
       crushin |
           cubicle_99 | culor | d_o_1 | dark_blues_in_sunlight | dark_green_02
       |
           dark_green_1 | dark_man_x | dark_orange_teal | dark_place_01 |
           darkandsomber | darkness | date_39 | day_4nite | day_for_night |
           day_to_night_kings_blue | deep | deep_blue | deep_dark_warm |
           deep_high_contrast | deep_teal_fade | deep_warm_fade |
       deepskintones_2 |
           deepskintones_3 | delicatessen | denoiser_simple_40 |
       desert_gold_37 |
           dimension | dimmer | directions_23 | django_25 | doctor_strange |
           domingo_145 | dream_1 | dream_85 | drop_green_tint_14 | dropblues |
       dunkirk
           | duotone_blue_red | earth_tone_boost | eda_0_2 | edgyember |
       elegance_38 |
           enchanted | ensaya | eterna_for_flog | expired_69 | expired_fade |
           expired_polaroid | extreme | fade | fade_to_green | faded |
       faded_47 |
           faded_alt | faded_analog | faded_extreme | faded_green |
       faded_pink-ish |
           faded_print | faded_retro_01 | faded_retro_02 | faded_vivid |
       fadedlook |
           fallcolors | falua | farkling | fatos | faux_infrared |
       faux_infrared_bw_1
           | faux_infrared_color_p_2 | faux_infrared_color_p_3 |
           faux_infrared_color_r_0a | faux_infrared_color_r_0b |
           faux_infrared_color_yp_1 | fezzle | fg_cinebasic | fg_cinebright |
           fg_cinecold | fg_cinedrama | fg_cinetealorange_1 |
       fg_cinetealorange_2 |
           fg_cinevibrant | fg_cinewarm | fgcinebasic | fgcinebright |
       fgcinecold |
           fgcinedrama | fgcinetealorange_1 | fgcinetealorange_2 |
       fgcinevibrant |
           fgcinewarm | fight_club | film_0987 | film_9879 | film_gb-19 |
           film_high_contrast | film_print_01 | film_print_02 | filmic | filo
       |
           flat_30 | flat_blue_moon | flavin | flog_to_rec_709 | foggynight |
           folger_50 | ford_v_ferrari | foresta | formula_b | french_comedy |
       frosted
           | frostedbeachpicnic | fuji_160c | fuji_160c_+ | fuji_160c_++ |
       fuji_160c_-
           | fuji_3510_constlclip | fuji_3510_constlmap | fuji_3510_cuspclip |
           fuji_3513_constlclip | fuji_3513_constlmap | fuji_3513_cuspclip |
       fuji_400h
           | fuji_400h_+ | fuji_400h_++ | fuji_400h_- | fuji_800z |
       fuji_800z_+ |
           fuji_800z_++ | fuji_800z_- | fuji_astia_100_generic |
       fuji_astia_100f |
           fuji_fp-100c | fuji_fp-100c_+ | fuji_fp-100c_++ | fuji_fp-100c_+++
       |
           fuji_fp-100c_++_alt | fuji_fp-100c_- | fuji_fp-100c_-- |
       fuji_fp-100c_alt |
           fuji_fp-100c_cool | fuji_fp-100c_cool_+ | fuji_fp-100c_cool_++ |
           fuji_fp-100c_cool_- | fuji_fp-100c_cool_-- | fuji_fp-100c_negative
       |
           fuji_fp-100c_negative_+ | fuji_fp-100c_negative_++ |
           fuji_fp-100c_negative_+++ | fuji_fp-100c_negative_++_alt |
           fuji_fp-100c_negative_- | fuji_fp-100c_negative_-- | fuji_fp-3000b
       |
           fuji_fp-3000b_+ | fuji_fp-3000b_++ | fuji_fp-3000b_+++ |
       fuji_fp-3000b_- |
           fuji_fp-3000b_-- | fuji_fp-3000b_hc | fuji_fp-3000b_negative |
           fuji_fp-3000b_negative_+ | fuji_fp-3000b_negative_++ |
           fuji_fp-3000b_negative_+++ | fuji_fp-3000b_negative_- |
           fuji_fp-3000b_negative_-- | fuji_fp-3000b_negative_early |
       fuji_fp_100c |
           fuji_hdr | fuji_neopan_1600 | fuji_neopan_1600_+ |
       fuji_neopan_1600_++ |
           fuji_neopan_1600_- | fuji_neopan_acros_100 |
       fuji_provia_100_generic |
           fuji_provia_100f | fuji_provia_400f | fuji_provia_400x |
       fuji_sensia_100 |
           fuji_superia_100 | fuji_superia_100_+ | fuji_superia_100_++ |
           fuji_superia_100_- | fuji_superia_1600 | fuji_superia_1600_+ |
           fuji_superia_1600_++ | fuji_superia_1600_- | fuji_superia_200 |
           fuji_superia_200_xpro | fuji_superia_400 | fuji_superia_400_+ |
           fuji_superia_400_++ | fuji_superia_400_- | fuji_superia_800 |
           fuji_superia_800_+ | fuji_superia_800_++ | fuji_superia_800_- |
           fuji_superia_hg_1600 | fuji_superia_reala_100 | fuji_superia_x-
       tra_800 |
           fuji_velvia_100_generic | fuji_velvia_50 | fuji_xtrans_iii_acros |
           fuji_xtrans_iii_acros+g | fuji_xtrans_iii_acros+r |
           fuji_xtrans_iii_acros+ye | fuji_xtrans_iii_astia |
           fuji_xtrans_iii_classic_chrome | fuji_xtrans_iii_mono |
           fuji_xtrans_iii_mono+g | fuji_xtrans_iii_mono+r |
       fuji_xtrans_iii_mono+ye |
           fuji_xtrans_iii_pro_neg_hi | fuji_xtrans_iii_pro_neg_std |
           fuji_xtrans_iii_provia | fuji_xtrans_iii_sepia |
       fuji_xtrans_iii_velvia |
           fusion_88 | futuristicbleak_1 | futuristicbleak_2 |
       futuristicbleak_3 |
           futuristicbleak_4 | going_for_a_walk | golden | golden_bright |
       golden_fade
           | golden_mono | golden_night_softner_43 | golden_sony_37 |
       golden_vibrant |
           goldengate | goldentime | goldfx_bright_spring_breeze |
           goldfx_bright_summer_heat | goldfx_hot_summer_heat |
           goldfx_perfect_sunset_01min | goldfx_perfect_sunset_05min |
           goldfx_perfect_sunset_10min | goldfx_spring_breeze |
       goldfx_summer_heat |
           good_morning | green_15 | green_2025 | green_action |
       green_afternoon |
           green_and_orange | green_blues | green_book | green_conflict |
       green_day_01
           | green_day_02 | green_g_09 | green_indoor | green_light |
       green_mono |
           green_yellow | greenish_contrasty | greenish_fade | greenish_fade_1
       |
           gremerta | greyhound | hackmanite | hallowen_dark | happyness_133 |
           hard_teal_orange | hardboost | harsh_day | harsh_sunset | helios |
           herderite | heulandite | hiddenite | highlights_protection |
       hilutite |
           hitman | hlg_1_1 | honey_light | hong_kong | horrorblue | howlite |
       huesio
           | husmes | huyan | hydracore | hyla_68 | hypersthene | hypnosis |
       hypressen
           | i_tonya | ideo | ilford_delta_100 | ilford_delta_3200 |
           ilford_delta_3200_+ | ilford_delta_3200_++ | ilford_delta_3200_- |
           ilford_delta_400 | ilford_fp_4_plus_125 | ilford_hp_5 |
       ilford_hp_5_+ |
           ilford_hp_5_++ | ilford_hp_5_- | ilford_hp_5_plus_400 |
       ilford_hps_800 |
           ilford_pan_f_plus_50 | ilford_xp_2 | inception | indoor_blue |
           industrial_33 | infrared_-_dust_pink | instantc | j | jarklin |
       jojo_rabbit
           | joker | jumanji_the_next_level | jurassic_world_fallen_kingdom |
           justice_league | justpeachy | jwick_21 | k_tone_vintage_kodachrome
       |
           kahve_3 | kh_1 | kh_10 | kh_2 | kh_3 | kh_4 | kh_5 | kh_6 | kh_7 |
       kh_8 |
           kh_9 | killstreak | kingsman_the_golden_circle | knives_out |
           kodak_2383_constlclip | kodak_2383_constlmap | kodak_2383_cuspclip
       |
           kodak_2393_constlclip | kodak_2393_constlmap | kodak_2393_cuspclip
       |
           kodak_bw_400_cn | kodak_e-100_gx_ektachrome_100 |
       kodak_ektachrome_100_vs |
           kodak_ektachrome_100_vs_generic | kodak_ektar_100 |
       kodak_elite_100_xpro |
           kodak_elite_chrome_200 | kodak_elite_chrome_400 |
       kodak_elite_color_200 |
           kodak_elite_color_400 | kodak_elite_extracolor_100 |
       kodak_hie_hs_infra |
           kodak_kodachrome_200 | kodak_kodachrome_25 | kodak_kodachrome_64 |
           kodak_kodachrome_64_generic | kodak_portra_160 | kodak_portra_160_+
       |
           kodak_portra_160_++ | kodak_portra_160_- | kodak_portra_160_nc |
           kodak_portra_160_nc_+ | kodak_portra_160_nc_++ |
       kodak_portra_160_nc_- |
           kodak_portra_160_vc | kodak_portra_160_vc_+ |
       kodak_portra_160_vc_++ |
           kodak_portra_160_vc_- | kodak_portra_400 | kodak_portra_400_+ |
           kodak_portra_400_++ | kodak_portra_400_- | kodak_portra_400_nc |
           kodak_portra_400_nc_+ | kodak_portra_400_nc_++ |
       kodak_portra_400_nc_- |
           kodak_portra_400_uc | kodak_portra_400_uc_+ |
       kodak_portra_400_uc_++ |
           kodak_portra_400_uc_- | kodak_portra_400_vc | kodak_portra_400_vc_+
       |
           kodak_portra_400_vc_++ | kodak_portra_400_vc_- | kodak_portra_800 |
           kodak_portra_800_+ | kodak_portra_800_++ | kodak_portra_800_- |
           kodak_portra_800_hc | kodak_t-max_100 | kodak_t-max_3200 | kodak_t-
       max_400
           | kodak_tmax_3200 | kodak_tmax_3200_+ | kodak_tmax_3200_++ |
           kodak_tmax_3200_- | kodak_tmax_3200_alt | kodak_tri-x_400 |
           kodak_tri-x_400_+ | kodak_tri-x_400_++ | kodak_tri-x_400_- |
           kodak_tri-x_400_alt | korben_214 | la_la_land | landscape |
       landscape_01 |
           landscape_02 | landscape_03 | landscape_04 | landscape_05 |
       landscape_1 |
           landscape_10 | landscape_2 | landscape_3 | landscape_4 |
       landscape_5 |
           landscape_6 | landscape_7 | landscape_8 | landscape_9 |
           lateafternoonwanderlust | latesunset | lavark | lc_1 | lc_10 | lc_2
       | lc_3
           | lc_4 | lc_5 | lc_6 | lc_7 | lc_8 | lc_9 | lenox_340 | levex |
           life_giving_tree | light | light_blown | litore | little_women |
       logan |
           lomo | lomography_redscale_100 | lomography_x-pro_slide_200 |
       london_nights
           | longbeachmorning | loro | lotta | louetta | low_contrast_blue |
           low_key_01 | lucky_64 | lushgreen | lushgreensummer |
       mad_max_fury_road |
           maesky | magenta_day | magenta_day_01 | magenta_dream |
       magenta_yellow |
           magentacoffee | magichour | marriage_story | matrix | mckinnon_75 |
           memories | mercato | metropolis | milo_5 | minimalistcaffeination |
           modern_film | modern_films_01 | modern_films_02 | modern_films_03 |
           modern_films_04 | modern_films_05 | modern_films_06 |
       modern_films_07 |
           molti | mono_2 | mono_tinted | monochrome | monochrome_1 |
       monochrome_2 |
           moody_1 | moody_10 | moody_2 | moody_3 | moody_4 | moody_5 |
       moody_6 |
           moody_7 | moody_8 | moody_9 | moonlight | moonlight_01 |
       moonlight_2 |
           moonrise | morning_6 | morroco_16 | mostly_blue | mother! | motus |
       moviz_1
           | moviz_10 | moviz_11 | moviz_12 | moviz_13 | moviz_14 | moviz_15 |
           moviz_16 | moviz_17 | moviz_18 | moviz_19 | moviz_2 | moviz_20 |
       moviz_21 |
           moviz_22 | moviz_23 | moviz_24 | moviz_25 | moviz_26 | moviz_27 |
       moviz_28
           | moviz_29 | moviz_3 | moviz_30 | moviz_31 | moviz_32 | moviz_33 |
       moviz_34
           | moviz_35 | moviz_36 | moviz_37 | moviz_38 | moviz_39 | moviz_4 |
       moviz_40
           | moviz_41 | moviz_42 | moviz_43 | moviz_44 | moviz_45 | moviz_46 |
           moviz_47 | moviz_48 | moviz_5 | moviz_6 | moviz_7 | moviz_8 |
       moviz_9 |
           mucca | mute_shift | muted_01 | muted_fade | mysticpurplesunset |
       nah |
           natural_vivid | naturalboost | negative | nemesis | neon_770 |
       neutral |
           neutral_pump | neutral_teal_orange | neutral_warm_fade | newspaper
       |
           night_01 | night_02 | night_03 | night_04 | night_05 |
       night_blade_4 |
           night_king_141 | night_spy | night_view | nightfromday | nightlife
       | nigrum
           | no_time_to_die | nostalgiahoney | nostalgic | nw-1 | nw-10 | nw-2
       | nw-3
           | nw-4 | nw-5 | nw-6 | nw-7 | nw-8 | nw-9 | old_west |
       once_upon_a_time |
           once_upon_a_time_in_hollywood | onda | only_red | only_red_and_blue
       |
           operation_yellow | orange_dark_4 | orange_dark_7 | orange_dark_look
       |
           orange_tone | orange_underexposed | orangeandblue | oranges | padre
       |
           paladin | paladin_1875 | parasite | partia | pasadena_21 |
       passing_by |
           perso | picola | pink_fade | pirates_of_the_caribbean | pitaya_15 |
           pmcinematic_01 | pmcinematic_02 | pmcinematic_03 | pmcinematic_04 |
           pmcinematic_05 | pmcinematic_06 | pmcinematic_07 | pmnight_01 |
       pmnight_02
           | pmnight_03 | pmnight_04 | pmnight_05 | polaroid_664 |
       polaroid_665 |
           polaroid_665_+ | polaroid_665_++ | polaroid_665_- | polaroid_665_--
       |
           polaroid_665_negative | polaroid_665_negative_+ |
       polaroid_665_negative_- |
           polaroid_665_negative_hc | polaroid_667 | polaroid_669 |
       polaroid_669_+ |
           polaroid_669_++ | polaroid_669_+++ | polaroid_669_- |
       polaroid_669_-- |
           polaroid_669_cold | polaroid_669_cold_+ | polaroid_669_cold_- |
           polaroid_669_cold_-- | polaroid_672 | polaroid_690 | polaroid_690_+
       |
           polaroid_690_++ | polaroid_690_- | polaroid_690_-- |
       polaroid_690_cold |
           polaroid_690_cold_+ | polaroid_690_cold_++ | polaroid_690_cold_- |
           polaroid_690_cold_-- | polaroid_690_warm | polaroid_690_warm_+ |
           polaroid_690_warm_++ | polaroid_690_warm_- | polaroid_690_warm_-- |
           polaroid_polachrome | polaroid_px-100uv+_cold |
       polaroid_px-100uv+_cold_+ |
           polaroid_px-100uv+_cold_++ | polaroid_px-100uv+_cold_+++ |
           polaroid_px-100uv+_cold_- | polaroid_px-100uv+_cold_-- |
           polaroid_px-100uv+_warm | polaroid_px-100uv+_warm_+ |
           polaroid_px-100uv+_warm_++ | polaroid_px-100uv+_warm_+++ |
           polaroid_px-100uv+_warm_- | polaroid_px-100uv+_warm_-- |
       polaroid_px-680 |
           polaroid_px-680_+ | polaroid_px-680_++ | polaroid_px-680_- |
           polaroid_px-680_-- | polaroid_px-680_cold | polaroid_px-680_cold_+
       |
           polaroid_px-680_cold_++ | polaroid_px-680_cold_++_alt |
           polaroid_px-680_cold_- | polaroid_px-680_cold_-- |
       polaroid_px-680_warm |
           polaroid_px-680_warm_+ | polaroid_px-680_warm_++ |
       polaroid_px-680_warm_- |
           polaroid_px-680_warm_-- | polaroid_px-70 | polaroid_px-70_+ |
           polaroid_px-70_++ | polaroid_px-70_+++ | polaroid_px-70_- |
           polaroid_px-70_-- | polaroid_px-70_cold | polaroid_px-70_cold_+ |
           polaroid_px-70_cold_++ | polaroid_px-70_cold_- |
       polaroid_px-70_cold_-- |
           polaroid_px-70_warm | polaroid_px-70_warm_+ |
       polaroid_px-70_warm_++ |
           polaroid_px-70_warm_- | polaroid_px-70_warm_-- |
       polaroid_time_zero_expired
           | polaroid_time_zero_expired_+ | polaroid_time_zero_expired_++ |
           polaroid_time_zero_expired_- | polaroid_time_zero_expired_-- |
           polaroid_time_zero_expired_--- | polaroid_time_zero_expired_cold |
           polaroid_time_zero_expired_cold_- |
       polaroid_time_zero_expired_cold_-- |
           polaroid_time_zero_expired_cold_--- | portrait | portrait_1 |
       portrait_10 |
           portrait_2 | portrait_3 | portrait_4 | portrait_5 | portrait_6 |
       portrait_7
           | portrait_8 | portrait_9 | progressen | protect_highlights_01 |
           prussian_blue | pseudogrey | purple | purple_2 | quraqqq_12 |
       randas |
           red_afternoon_01 | red_day_01 | red_dream_01 | redblueyellow | reds
       |
           reds_oranges_yellows | reeve_38 | remy_24 | rest_33 | retro |
           retro_brown_01 | retro_magenta_01 | retro_summer_3 |
       retro_yellow_01 |
           rocketman | rollei_ir_400 | rollei_ortho_25 |
       rollei_retro_100_tonal |
           rollei_retro_80s | rotate_muted | rotate_vibrant | rotated |
       rotated_crush
           | satid | saturated_blue | saving_private_damon | scala |
       science_fiction |
           scrittle | sea | seges | selor | sensum | separation | serenity |
       seringe_4
           | serpent | seventies_magazine | sevsuz | shade_kings_ink |
       shadow_king_39
           | shine | sicario | sino | skin_tones | slog_to_rec709_basic |
           slog_to_rec709_contrasty | slog_to_rec709_crush_shadows |
           slog_to_rec709_green_correction | smart_contrast | smokey |
       smooth_clear |
           smooth_cromeish | smooth_fade | smooth_green_orange |
       smooth_sailing |
           smooth_teal_orange | soft_fade | softblackandwhite | softwarming |
           solarized_color | solarized_color_2 | soldi | spider-
       man_far_from_home |
           spotlight | springmorning | sprocket_231 | spy_29 | standard |
           star_wars_the_rise_of_skywalker | strano | street | stringa |
           studio_skin_tone_shaper | subtle_blue | subtle_green |
       subtle_yellow |
           sully | summer | summer_alt | sunlight_love_11 | sunlightlove |
       sunny |
           sunny_alt | sunny_rich | sunny_warm | sunset | sunset_aqua_orange |
           sunset_intense_violet_blue | sunset_violet_mood | super_warm |
           super_warm_rich | sutro_fx | sweet_bubblegum | sweet_gelatto |
           tasdemirrr_1 | taiga | tarraco | teal-orange_for_flog | teal_fade |
           teal_moonlight | tealmagentagold | tealorange | tealorange_1 |
       tealorange_2
           | tealorange_3 | technicalfx_backlight_filter | teigen_28 | tenet |
           tensiongreen_1 | tensiongreen_2 | tensiongreen_3 | tensiongreen_4 |
       terra_4
           | the_dark_knight | the_darkest_hour | the_gentelmen |
           the_grand_budapest_hotel | the_hurt_locker | the_irishman |
       the_lighthouse
           | the_lobster | the_martian | the_matrices | the_revenant |
           the_shape_of_water | the_social_network | the_two_popes |
       the_way_back |
           thor_ragnarok | thriller_2 | tirare | toastedgarden |
       top_gun_maverick |
           trent_18 | true_colors_8 | turkiest_42 | tutto | tweed_71 |
       ultra_water |
           uncut_gems | undeniable | undeniable_2 | underwater | unknown |
       upglow |
           urban_01 | urban_02 | urban_03 | urban_04 | urban_05 | urban_cowboy
       |
           uzbek_bukhara | uzbek_marriage | uzbek_samarcande | valize | valsky
       |
           velvetia | venom | very_warm_greenish | vfb_21 | vibrant |
       vibrant_alien |
           vibrant_contrast | vibrant_cromeish | victory | vintage |
       vintage_01 |
           vintage_02 | vintage_03 | vintage_04 | vintage_05 | vintage_163 |
           vintage_alt | vintage_brighter | vintage_chrome | vintage_mob |
           vintage_warmth_1 | violet_taste | vireo_37 | vita | vivid | vubes |
           war_for_the_planet_of_the_apes | warm | warm_dark_contrasty |
       warm_fade |
           warm_fade_1 | warm_highlight | warm_neutral | warm_sunset_red |
       warm_teal |
           warm_vintage | warm_yellow | wavefire | waves | well_see | western
       |
           western_6 | westernlut_2 | westernlut_2_13 | whiter_whites |
           winterlighthouse | wipe | wolf_of_wall_street | wonder_woman |
           wooden_gold_20 | x-men_dark_phoenix | yangabuz_8 | yellow_55b |
           yellow_film_01 | yellowstone | you_can_do_it | zed_32 | zeke_39 |
           zilverfx_bw_solarization | zilverfx_infrared | zilverfx_vintage_bw
       |
           zombieland_double_tap }

           Default values: 'resolution=33' and 'cut_and_round=1'.

           Example:
             [#1] clut summer clut alien_green,17 clut orange_dark4,48

         clut2hald:

           Convert selected 3D CLUTs to 2D HaldCLUTs.

           Example:
             [#1] clut summer +clut2hald

         hald2clut:

           Convert selected 2D HaldCLUTs to 3D CLUTs.

         cmy2rgb:

           Convert color representation of selected images from CMY to RGB.

         cmyk2rgb:

           Convert color representation of selected images from CMYK to RGB.

         colorblind:
             type={ 0:protanopia | 1:protanomaly | 2:deuteranopia |
       3:deuteranomaly |
               4:tritanopia | 5:tritanomaly | 6:achromatopsia |
       7:achromatomaly }

           Simulate color blindness vision.
           Simulation method of Vienot, Brettel & Mollon 1999, "Digital video
           colourmaps for checking the legibility of displays by dichromats".
           The dichromacy matrices of the paper were adapted to sRGB
       (RGB->XYZ).
           Anomalous trichromacy simulated via linear interpolation with the
       identity
           and a factor of 0.6.

           Example:
             [#1] image.jpg +colorblind 0

         colormap:
             nb_levels>=0,_method={ 0:median-cut | 1:k-means },_sort_vectors

           Estimate best-fitting colormap with 'nb_colors' entries, to index
           selected images.
           Set 'nb_levels==0' to extract all existing colors of an image.
           'sort_vectors' can be { 0:unsorted | 1:by increasing norm | 2:by
           decreasing occurrence }.

           Default value: 'method=1' and 'sort_vectors=1'.

           Example:
             [#1] image.jpg +colormap[0] 4 +colormap[0] 8 +colormap[0] 16

           Tutorial: https://gmic.eu/oldtutorial/_colormap

         compose_channels:

           Compose all channels of each selected image, using specified
       arithmetic
           operator (+,-,or,min,...).

           Default value: '1=+'.

           Example:
             [#1] image.jpg +compose_channels and

           Tutorial: https://gmic.eu/tutorial/compose_channels

         count_colors:
             _count_until={ 0 |
             none | >0 |
             max number of counted colors }

           Count number of distinct colors in selected images until it reaches
       the
           specified max number of counted colors.
           Set 'count_until' to '0' to disable limit on counted colors.
           This command returns the number of distinct colors for each image
           (separated by commas).

         deltaE:
             [image],_metric={ 0:deltaE_1976 | 1:deltaE_2000
       },"_to_Lab_command"

           Compute the CIE DeltaE color difference between selected images and
           specified [image].
           Argument 'to_Lab_command' is a command able to convert colors of
           [image] into a Lab representation.

           Default values: 'metric=1' and 'to_Lab_command="srgb2lab"
            '.

           Example:
             [#1] image.jpg +blur 2 +deltaE[0] [1],1,srgb2lab

         direction2rgb:

           Compute RGB representation of selected 2D direction fields.

           Example:
             [#1] image.jpg luminance gradient append c blur 2 orientation
              +direction2rgb

         ditheredbw:

           Create dithered B&W version of selected images.

           Example:
             [#1] image.jpg +equalize ditheredbw[-1]

         fc:
             Shortcut for command 'fill_color'.

         fill_color:
             col1,...,colN

           Fill selected images with specified color.
           (equivalent to shortcut command 'fc').

           Example:
             [#1] image.jpg +fill_color 255,0,255

           Tutorial: https://gmic.eu/oldtutorial/_fill_color

         gradient2rgb:
             _is_orientation={ 0 | 1 }

           Compute RGB representation of 2D gradient of selected images.

           Default value: 'is_orientation=0'.

           Example:
             [#1] image.jpg +gradient2rgb 0 equalize[-1]

         hcy2rgb:

           Convert color representation of selected images from HCY to RGB.

         hsi2rgb:

           Convert color representation of selected images from HSI to RGB.

         hsi82rgb:

           Convert color representation of selected images from HSI8 to RGB.

         hsl2rgb:

           Convert color representation of selected images from HSL to RGB.

         hsl82rgb:

           Convert color representation of selected images from HSL8 to RGB.

         hsv2rgb:

           Convert color representation of selected images from HSV to RGB.

           Example:
             [#1] (0,360;0,360^0,0;1,1^1,1;1,1) resize 400,400,1,3,3 hsv2rgb

         hsv82rgb:

           Convert color representation of selected images from HSV8 to RGB.

         int2rgb:

           Convert color representation of selected images from INT24 to RGB.

         ipremula:

           Convert selected images with premultiplied alpha colors to normal
       colors.
           See also: premula.

         jzazbz2rgb:
             illuminant={ 0:D50 | 1:D65 | 2:E } |
             (no arg)

           Convert color representation of selected images from RGB to Jzazbz.

           Default value: 'illuminant=2'.

         jzazbz2xyz:

           Convert color representation of selected images from RGB to XYZ.

         lab2lch:

           Convert color representation of selected images from Lab to Lch.

         lab2rgb:
             illuminant={ 0:D50 | 1:D65 | 2:E } |
             (no arg)

           Convert color representation of selected images from Lab to RGB.

           Default value: 'illuminant=2'.

           Example:
             [#1] (50,50;50,50^-3,3;-3,3^-3,-3;3,3) resize 400,400,1,3,3
       lab2rgb

         lab2srgb:
             illuminant={ 0:D50 | 1:D65 | 2:E } |
             (no arg)

           Convert color representation of selected images from Lab to sRGB.

           Default value: 'illuminant=2'.

           Example:
             [#1] (50,50;50,50^-3,3;-3,3^-3,-3;3,3) resize 400,400,1,3,3
       lab2rgb

         lab82srgb:
             illuminant={ 0:D50 | 1:D65 | 2:E } |
             (no arg)

           Convert color representation of selected images from Lab8 to sRGB.

           Default value: 'illuminant=2'.

           Example:
             [#1] (50,50;50,50^-3,3;-3,3^-3,-3;3,3) resize 400,400,1,3,3
       lab2rgb

         lab2xyz:
             illuminant={ 0:D50 | 1:D65 | 2:E } |
             (no arg)

           Convert color representation of selected images from Lab to XYZ.

           Default value: 'illuminant=2'.

         lab82rgb:
             illuminant={ 0:D50 | 1:D65 | 2:E } |
             (no arg)

           Convert color representation of selected images from Lab8 to RGB.

           Default value: 'illuminant=2'.

         lch2lab:

           Convert color representation of selected images from Lch to Lab.

         lch2rgb:
             illuminant={ 0:D50 | 1:D65 | 2:E } |
             (no arg)

           Convert color representation of selected images from Lch to RGB.

           Default value: 'illuminant=2'.

         lch82rgb:
             illuminant={ 0:D50 | 1:D65 | 2:E } |
             (no arg)

           Convert color representation of selected images from Lch8 to RGB.

           Default value: 'illuminant=2'.

         luminance:

           Compute luminance of selected sRGB images.

           Example:
             [#1] image.jpg +luminance

           Tutorial: https://gmic.eu/tutorial/luminance

         lightness:

           Compute lightness of selected sRGB images.

           Example:
             [#1] image.jpg +lightness

         lut_contrast:
             _nb_colors>1,_min_rgb_value

           Generate a RGB colormap where consecutive colors have high
       contrast.
           This function performs a specific score maximization to generate
       the
           result, so
           it may take some time when 'nb_colors' is high.

           Default values: 'nb_colors=256' and 'min_rgb_value=64'.

         map_clut:
             [clut] | "clut_name"

           Map specified RGB color LUT to selected images.

           Example:
             [#1] image.jpg uniform_distribution {2^6},3 mirror[-1] x
       +map_clut[0]
              [1]

         match_histogram:
             [reference_image],_nb_levels>0,_color_channels

           Transfer histogram of the specified reference image to selected
       images.
           Argument 'color channels' is the same as with command
           'apply_channels'.

           Default value: 'nb_levels=256' and 'color_channels=all'.

           Example:
             [#1] image.jpg 100,100,1,3,"u([256,200,100])" +match_histogram[0]
       [1]

         match_icp:
             [reference_image],_precision>0,_transformation_variable

           Transform selected set of d-dimensional vectors to match specified
       set of
           reference vectors, using ICP (Iterative Closest Point) algorithm.
           A description of ICP is available at
       https://en.wikipedia.org/wiki/Itera
           tive_closest_point.
           Return the L2 alignment error.

           Default values: 'precision=1e-2' and
            'transformation_variable=(undefined)'.
           sample lena,earth +match_icp[0] [1]

         match_pca:
             [reference_image],_color_channels

           Transfer mean and covariance matrix of specified vector-valued
       reference
           image to selected images.
           Argument 'color channels' is the same as with command
           'apply_channels'.

           Default value: 'color_channels=all'.

           Example:
             [#1] sample lena,earth +match_pca[0] [1]

         match_rgb:
             [target],_gamma>=0,_regularization>=0,_luminosity_constraints>=0,
               _rgb_resolution>=0,_is_constraints={ 0 | 1 }

           Transfer colors from selected source images to selected reference
       image
           (given as argument).
           'gamma' determines the importance of color occurrences in the
           matching process (0:none to 1:huge).
           'regularization' determines the number of guided filter iterations
           to remove quantization effects.
           'luminosity_constraints' tells if luminosity constraints must be
           applied on non-confident matched colors.
           'is_constraints' tells if additional hard color constraints must be
           set (opens an interactive window).

           Default values: 'gamma=0.3','regularization=8',
            'luminosity_constraints=0.1', 'rgb_resolution=64' and
            'is_constraints=0'.

           Example:
             [#1] sample pencils,wall +match_rgb[0] [1],0,0.01

         mix_rgb:
             a11,a12,a13,a21,a22,a23,a31,a32,a33

           Apply 3x3 specified matrix to RGB colors of selected images.

           Default values: 'a11=1', 'a12=a13=a21=0', 'a22=1',
            'a23=a31=a32=0' and 'a33=1'.

           Example:
             [#1] image.jpg +mix_rgb 0,1,0,1,0,0,0,0,1

           Tutorial: https://gmic.eu/tutorial/mix_rgb

         oklab2rgb:

           Convert color representation of selected images from OKlab to RGB.
           (see colorspace definition at:
       https://bottosson.github.io/posts/oklab/    fR ).
           See also: rgb2oklab.

         palette:
             palette_name | palette_number

           Input specified color palette at the end of the image list.
           'palette_name' can be { default | hsv | lines | hot | cool | jet
           | flag | cube | rainbow | parula | spring | summer | autumn |
       winter | bone
           | copper | pink | vga | algae | amp | balance | curl | deep | delta
       | dense
           | diff | gray | haline | ice | matter | oxy | phase | rain | solar
       | speed
           | tarn | tempo | thermal | topo | turbid | aurora | hocuspocus |
       srb2 |
           uzebox | amiga7800 | amiga7800mess | fornaxvoid1 }

           Example:
             [#1] palette hsv

         premula:

           Convert selected images with normal colors to premultiplied alpha
       colors.
           After conversion, alpha channel of resulting images has value in
       [0,1]
           range.
           See also: ipremula.

         pseudogray:
             _max_increment>=0,_JND_threshold>=0,_bits_depth>0

           Generate pseudogray colormap with specified increment and
       perceptual
           threshold.
           If 'JND_threshold' is 0, no perceptual constraints are applied.

           Default values: 'max_increment=5', 'JND_threshold=2.3'
            and 'bits_depth=8'.

           Example:
             [#1] pseudogray 5

         random_clut:

           Generate a 33x33x33 random 3D color LUT.

           Example:
             [#1] image.jpg random_clut +map_clut.. .

         random_clut:
             _seed = { >=0 | -1 }

           Generate a 33x33x33 random 3D color LUT.
           If specified 'seed' is positive, it is used as a seed for the
       random
           number generator @cli : (so that using the same seed will return
       the same
           CLUT).

           Example:
             [#1] image.jpg random_clut +map_clut.. .

         replace_color:
             tolerance[%]>=0,smoothness[%]>=0,src1,src2,...,dest1,dest2,...

           Replace pixels from/to specified colors in selected images.

           Example:
             [#1] image.jpg +replace_color 40,3,204,153,110,255,0,0

         retinex:
             _value_offset>0,_colorspace={ hsi | hsv | lab | lrgb | rgb |
       ycbcr },
               0<=_min_cut<=100,0<=_max_cut<=100,_sigma_low>0,_sigma_mid>0,
               _sigma_high>0

           Apply multi-scale retinex algorithm on selected images to improve
       color
           consistency.
           (as described in the page http://www.ipol.im/pub/art/2014/107/).

           Default values: 'offset=1', 'colorspace=hsv',
            'min_cut=1', 'max_cut=1', 'sigma_low=15',
            'sigma_mid=80' and 'sigma_high=250'.

         rgb2bayer:
             _start_pattern=0,_color_grid=0

           Transform selected color images to RGB-Bayer sampled images.

           Default values: 'start_pattern=0' and 'color_grid=0'.

           Example:
             [#1] image.jpg +rgb2bayer 0

         rgb2cmy:

           Convert color representation of selected images from RGB to CMY.

           Example:
             [#1] image.jpg rgb2cmy split c

         rgb2cmyk:

           Convert color representation of selected images from RGB to CMYK.

           Example:
             [#1] image.jpg rgb2cmyk split c
             [#2] image.jpg rgb2cmyk split c fill[3] 0 append c cmyk2rgb

         rgb2hcy:

           Convert color representation of selected images from RGB to HCY.

           Example:
             [#1] image.jpg rgb2hcy split c

         rgb2hsi:

           Convert color representation of selected images from RGB to HSI.

           Example:
             [#1] image.jpg rgb2hsi split c

         rgb2hsi8:

           Convert color representation of selected images from RGB to HSI8.

           Example:
             [#1] image.jpg rgb2hsi8 split c

         rgb2hsl:

           Convert color representation of selected images from RGB to HSL.

           Example:
             [#1] image.jpg rgb2hsl split c
             [#2] image.jpg rgb2hsl +split c add[-3] 100 mod[-3] 360
       append[-3--1] c
              hsl2rgb

         rgb2hsl8:

           Convert color representation of selected images from RGB to HSL8.

           Example:
             [#1] image.jpg rgb2hsl8 split c

         rgb2hsv:

           Convert color representation of selected images from RGB to HSV.

           Example:
             [#1] image.jpg rgb2hsv split c
             [#2] image.jpg rgb2hsv +split c add[-2] 0.3 cut[-2] 0,1
       append[-3--1] c
              hsv2rgb

         rgb2hsv8:

           Convert color representation of selected images from RGB to HSV8.

           Example:
             [#1] image.jpg rgb2hsv8 split c

         rgb2int:

           Convert color representation of selected images from RGB to INT24
       scalars.

           Example:
             [#1] image.jpg rgb2int

         rgb2jzazbz:
             illuminant={ 0:D50 | 1:D65 | 2:E } |
             (no arg)

           Convert color representation of selected images from RGB to Jzazbz.

           Default value: 'illuminant=2'.

         rgb2lab:
             illuminant={ 0:D50 | 1:D65 | 2:E } |
             (no arg)

           Convert color representation of selected images from RGB to Lab.

           Default value: 'illuminant=2'.

         rgb2lab8:
             illuminant={ 0:D50 | 1:D65 | 2:E } |
             (no arg)

           Convert color representation of selected images from RGB to Lab8.

           Default value: 'illuminant=2'.

           Example:
             [#1] image.jpg rgb2lab8 split c

         rgb2lch:
             illuminant={ 0:D50 | 1:D65 | 2:E } |
             (no arg)

           Convert color representation of selected images from RGB to Lch.

           Default value: 'illuminant=2'.

           Example:
             [#1] image.jpg rgb2lch split c

         rgb2lch8:
             illuminant={ 0:D50 | 1:D65 | 2:E } |
             (no arg)

           Convert color representation of selected images from RGB to Lch8.

           Default value: 'illuminant=2'.

           Example:
             [#1] image.jpg rgb2lch8 split c

         rgb2luv:

           Convert color representation of selected images from RGB to LUV.

           Example:
             [#1] image.jpg rgb2luv split c

         rgb2oklab:

           Convert color representation of selected images from RGB to Oklab.
           (see colorspace definition at:
       https://bottosson.github.io/posts/oklab/    fR ).
           See also: oklab2rgb.

         rgb2ryb:

           Convert color representation of selected images from RGB to RYB.

           Example:
             [#1] image.jpg rgb2ryb split c

         rgb2srgb:

           Convert color representation of selected images from linear RGB to
       sRGB.

         rgb2xyz:
             illuminant={ 0:D50 | 1:D65 | 2:E } |
             (no arg)

           Convert color representation of selected images from RGB to XYZ.

           Default value: 'illuminant=2'.

           Example:
             [#1] image.jpg rgb2xyz split c

         rgb2xyz8:
             illuminant={ 0:D50 | 1:D65 | 2:E } |
             (no arg)

           Convert color representation of selected images from RGB to XYZ8.

           Default value: 'illuminant=2'.

           Example:
             [#1] image.jpg rgb2xyz8 split c

         rgb2yiq:

           Convert color representation of selected images from RGB to YIQ.

           Example:
             [#1] image.jpg rgb2yiq split c

         rgb2yiq8:

           Convert color representation of selected images from RGB to YIQ8.

           Example:
             [#1] image.jpg rgb2yiq8 split c

         rgb2ycbcr:

           Convert color representation of selected images from RGB to YCbCr.

           Example:
             [#1] image.jpg rgb2ycbcr split c

         rgb2yuv:

           Convert color representation of selected images from RGB to YUV.

           Example:
             [#1] image.jpg rgb2yuv split c

         rgb2yuv8:

           Convert color representation of selected images from RGB to YUV8.

           Example:
             [#1] image.jpg rgb2yuv8 split c

         remove_opacity:

           Remove opacity channel of selected images.

         ryb2rgb:

           Convert color representation of selected images from RYB to RGB.

         select_color:
             tolerance[%]>=0,col1,...,colN

           Select pixels with specified color in selected images.

           Example:
             [#1] image.jpg +select_color 40,204,153,110

           Tutorial: https://gmic.eu/oldtutorial/_select_color

         sepia:

           Apply sepia tones effect on selected images.

           Example:
             [#1] image.jpg sepia

         solarize:

           Solarize selected images.

           Example:
             [#1] image.jpg solarize

         split_colors:
             _tolerance>=0,_max_nb_outputs>0,_min_area>0

           Split selected images as several image containing a single color.
           One selected image can be split as at most 'max_nb_outputs' images.
           Output images are sorted by decreasing area of extracted color
       regions and
           have an additional alpha-channel.

           Default values: 'tolerance=0', 'max_nb_outputs=256' and
            'min_area=8'.

           Example:
             [#1] image.jpg quantize 5 +split_colors , display_rgba

         split_opacity:

           Split color and opacity parts of selected images.
           This command returns 1 or 2 images for each selected image, whether
       it has
           an opacity channel or not.

         split_vector:
             keep_splitting_values={ + | - },value1,_value2,...

           Split selected images into multiple parts, where specified vector
           '[value1,_value2,...]' is the separator.

         srgb2lab:
             illuminant={ 0:D50 | 1:D65 | 2:E } |
             (no arg)

           Convert color representation of selected images from sRGB to Lab.

           Default value: 'illuminant=2'.

           Example:
             [#1] image.jpg srgb2lab split c
             [#2] image.jpg srgb2lab +split c mul[-2,-1] 2.5 append[-3--1] c
       lab2srgb

         srgb2lab8:
             illuminant={ 0:D50 | 1:D65 | 2:E } |
             (no arg)

           Convert color representation of selected images from sRGB to Lab8.

           Default value: 'illuminant=2'.

         srgb2rgb:

           Convert color representation of selected images from sRGB to linear
       RGB.

         to_a:

           Force selected images to have an alpha channel.

         to_color:

           Force selected images to be in color mode (RGB or RGBA).

         to_colormode:
             mode={ 0:adaptive | 1:G | 2:GA | 3:RGB | 4:RGBA }

           Force selected images to be in a given color mode.

           Default value: 'mode=0'.

         to_gray:

           Force selected images to be in GRAY mode.

           Example:
             [#1] image.jpg +to_gray

         to_graya:

           Force selected images to be in GRAYA mode.

         to_pseudogray:
             _max_step>=0,_is_perceptual_constraint={ 0 | 1 },_bits_depth>0

           Convert selected scalar images ([0-255]-valued) to pseudo-gray
       color
           images.

           Default values: 'max_step=5', 'is_perceptual_constraint=1
            ' and 'bits_depth=8'.
           The original pseudo-gray technique has been introduced by Rich
       Franzen
           http://r0k.us/graphics/pseudoGrey.html.
           Extension of this technique to arbitrary increments for more tones,
       has
           been done by David Tschumperle.

         to_rgb:

           Force selected images to be in RGB mode.

         to_rgba:

           Force selected images to be in RGBA mode.

         to_automode:

           Force selected images to be in the most significant color mode.
           This commands checks for useless alpha channel (all values equal to
       255),
           as well as
           detects grayscale images encoded as color images.

         xyz2jzazbz:

           Convert color representation of selected images from XYZ to RGB.

         xyz2lab:
             illuminant={ 0:D50 | 1:D65 | 2:E } |
             (no arg)

           Convert color representation of selected images from XYZ to Lab.

           Default value: 'illuminant=2'.

         xyz2rgb:
             illuminant={ 0:D50 | 1:D65 | 2:E } |
             (no arg)

           Convert color representation of selected images from XYZ to RGB.

           Default value: 'illuminant=2'.

         xyz82rgb:
             illuminant={ 0:D50 | 1:D65 | 2:E } |
             (no arg)

           Convert color representation of selected images from XYZ8 to RGB.

           Default value: 'illuminant=2'.

         ycbcr2rgb:

           Convert color representation of selected images from YCbCr to RGB.

         yiq2rgb:

           Convert color representation of selected images from YIQ to RGB.

         yiq82rgb:

           Convert color representation of selected images from YIQ8 to RGB.

         yuv2rgb:

           Convert color representation of selected images from YUV to RGB.

         yuv82rgb:

           Convert selected images from YUV8 to RGB color bases.

         11.7. Geometry Manipulation
               ---------------------

         a (+):
             Shortcut for command 'append'.

         append (+):
             [image],axis,_centering |
             axis,_centering

           Append specified image to selected images, or all selected images
       together,
            along specified axis.
           (equivalent to shortcut command 'a').

           'axis' can be { x | y | z | c }.
           Usual 'centering' values are { 0:left-justified | 0.5:centered |
           1:right-justified }.

           Default value: 'centering=0'.

           Example:
             [#1] image.jpg split y,10 reverse append y
             [#2] image.jpg repeat 5 { +rows[0] 0,{10+18*$>}% } remove[0]
       append x,
              0.5
             [#3] image.jpg append[0] [0],y

         append_tiles:
             _M>=0,_N>=0,0<=_centering_x<=1,0<=_centering_y<=1

           Append MxN selected tiles as new images.
           If 'N' is set to 0, number of rows is estimated automatically.
           If 'M' is set to 0, number of columns is estimated automatically.
           If 'M' and 'N' are both set to '0', auto-mode is used.
           If 'M' or 'N' is set to 0, only a single image is produced.
           'centering_x' and 'centering_y' tells about the centering of
           tiles when they have different sizes.

           Default values: 'M=0', 'N=0',
            'centering_x=centering_y=0.5'.

           Example:
             [#1] image.jpg split xy,4 append_tiles ,

         apply_scales:
             "command",number_of_scales>0,_min_scale[%]>=0,_max_scale[%]>=0,
               _scale_gamma>0,_interpolation

           Apply specified command on different scales of selected images.
           'interpolation' can be { 0:none | 1:nearest | 2:average |
           3:linear | 4:grid | 5:bicubic | 6:lanczos }.

           Default value: 'min_scale=25%', 'max_scale=100%' and
            'interpolation=3'.

           Example:
             [#1] image.jpg apply_scales "blur 5 sharpen 1000",4

         autocrop (+):
             value1,value2,... |
             (no arg)

           Autocrop selected images by specified vector-valued intensity.
           If no arguments are provided, cropping value is guessed.

           Example:
             [#1] 400,400,1,3 fill_color 64,128,255 ellipse
       50%,50%,120,120,0,1,255
              +autocrop

         autocrop_components:
             _threshold[%],_min_area[%]>=0,_is_high_connectivity={ 0 | 1 },
               _output_type={ 0:crop | 1:segmentation | 2:coordinates }

           Autocrop and extract connected components in selected images,
       according to
           a mask given as the last channel of
           each of the selected image (e.g. alpha-channel).

           Default values: 'threshold=0%', 'min_area=0.1%',
            'is_high_connectivity=0' and 'output_type=1'.

           Example:
             [#1] 256,256 noise 0.1,2 eq 1 dilate_circ 20 label_fg 0,1
       normalize 0,
              255 +neq 0 *[-1] 255 append c +autocrop_components ,

         autocrop_seq:
             value1,value2,... | auto

           Autocrop selected images using the crop geometry of the last one by
           specified vector-valued intensity,
           or by automatic guessing the cropping value.

           Default value: auto mode.

           Example:
             [#1] image.jpg +fill[-1] 0 ellipse[-1] 50%,50%,30%,20%,0,1,1
              autocrop_seq 0

         channels:
             c0[%],_c1[%]

           Keep only specified channels of selected images.
           Dirichlet boundary is used when specified channels are out of
       range.

           Default value: 'c1=c0'.

           Example:
             [#1] image.jpg channels 0,1
             [#2] image.jpg luminance channels 0,2

         columns:
             x0[%],_x1[%]

           Keep only specified columns of selected images.
           Dirichlet boundary is used when specified columns are out of range.

           Default value: 'x1=x0'.

           Example:
             [#1] image.jpg columns -25%,50%

         z (+):
             Shortcut for command 'crop'.

         crop (+):
             x0[%],x1[%],_boundary_conditions |
             x0[%],y0[%],x1[%],y1[%],_boundary_conditions |
             x0[%],y0[%],z0[%],x1[%],y1[%],z1[%],_boundary_conditions |
             x0[%],y0[%],z0[%],c0[%],x1[%],y1[%],z1[%],c1[%],_boundary_conditions

           Crop selected images with specified region coordinates.
           (equivalent to shortcut command 'z').

           'boundary_conditions' can be { 0:dirichlet | 1:neumann |
           2:periodic | 3:mirror }.

           Default value: 'boundary_conditions=0'.

           Example:
             [#1] image.jpg +crop -230,-230,280,280,1 crop[0]
       -230,-230,280,280,0
             [#2] image.jpg crop 25%,25%,75%,75%

         diagonal:

           Transform selected vectors as diagonal matrices.

           Example:
             [#1] 1,10,1,1,'y' +diagonal

         edgels:
             x0,y0,_n0,_is_high_connectivity={ 0 | 1 }

           Extract one or several lists of edgels (and their normals) that
       defines a
           2D binary silhouette.
           When specified (i.e. '!=-1'), arguments 'x0,y0,n0' are the
           coordinates of the starting edgel, which must be located on an edge
       of the
           binary silhouette.
            * If 'x0,y0' and 'n0' are specified, only a single list of
           edgels is returned.
            * If only 'x0,y0' are specified (meaning 'n0=-1'), up to 4
           lists of edgels can be returned, all starting from the same point
       (x0,y0).
            * If no arguments are specified (meaning 'x0=y0=n0=-1'), all
           possible lists of edgels are returned.
           A list of edgels is returned as an image with 3 channels '[x,y,n]'
           where 'x' and 'y' are the 2D coordinates of the edgel pixel,
           and 'n' is the orientation of its associated canonical normal
       (which
           can be { 0:[1,0] | 1:[0,1] | 2:[-1,0] | 3:[0,-1] }.

           Default values: 'x0=y0=n0=-1' and
            'is_high_connectivity=1'.

         elevate:
             _depth,_is_plain={ 0 | 1 },_is_colored={ 0 | 1 }

           Elevate selected 2D images into 3D volumes.

           Default values: 'depth=64', 'is_plain=1' and
            'is_colored=1'.

         expand_x:
             size_x>=0,_boundary_conditions={ 0:dirichlet | 1:neumann |
       2:periodic |
               3:mirror }

           Expand selected images along the x-axis.

           Default value: 'boundary_conditions=0'.

           Example:
             [#1] image.jpg expand_x 30,0

         expand_xy:
             size>=0,_boundary_conditions={ 0:dirichlet | 1:neumann |
       2:periodic |
               3:mirror }

           Expand selected images along the xy-axes.

           Default value: 'boundary_conditions=0'.

           Example:
             [#1] image.jpg expand_xy 30,0

         expand_xyz:
             size>=0,_boundary_conditions={ 0:dirichlet | 1:neumann |
       2:periodic |
               3:mirror }

           Expand selected images along the xyz-axes.

           Default value: 'boundary_conditions=0'.

         expand_y:
             size_y>=0,_boundary_conditions={ 0:dirichlet | 1:neumann |
       2:periodic |
               3:mirror }

           Expand selected images along the y-axis.

           Default value: 'boundary_conditions=0'.

           Example:
             [#1] image.jpg expand_y 30,0

         expand_z:
             size_z>=0,_boundary_conditions={ 0:dirichlet | 1:neumann |
       2:periodic |
               3:mirror }

           Expand selected images along the z-axis.

           Default value: 'boundary_conditions=0'.

         extract:
             "condition",_output_type={ 0:xyzc-coordinates | 1:xyz-coordinates
       |
               2:scalar-values | 3:vector-values }

           Extract a list of coordinates or values from selected image, where
           specified mathematical condition holds.
           For N coordinates matching, result is a 1xNx1x4 image.

           Default values: 'output_type=0'.

           Example:
             [#1] sp lena +extract "norm(I)>128",3

         extract_region:
             [label_image],_extract_xyz_coordinates={ 0 | 1
       },_label_1,...,_label_M

           Extract all pixels of selected images whose corresponding label in
           '[label_image]' is equal to 'label_m',
           and output them as M column images.

           Default value: 'extract_xyz_coordinates=0'.

           Example:
             [#1] image.jpg +blur 3 quantize. 4,0 +extract_region[0] [1],0,1,3

         montage:
             "_layout_code",_montage_mode={ 0<=centering<=1 | 2<=scale+2<=3 },
               _output_mode={ 0:single layer | 1:multiple layers },
               "_processing_command"

           Create a single image montage from selected images, according to
       specified
           layout code :
            * 'X' to assemble all images using an automatically estimated
           layout.
            * 'H' to assemble all images horizontally.
            * 'V' to assemble all images vertically.
            * 'A' to assemble all images as an horizontal array.
            * 'B' to assemble all images as a vertical array.
            * 'Ha:b' to assemble two blocks 'a' and 'b'
           horizontally.
            * 'Va:b' to assemble two blocks 'a' and 'b' vertically.
            * 'Ra' to rotate a block 'a' by 90 deg. ('RRa' for 180
           deg. and 'RRRa' for 270 deg.).
            * 'Ma' to mirror a block 'a' along the X-axis ('MRRa'
           for the Y-axis).
           A block 'a' can be an image index (treated periodically) or a
       nested
           layout expression 'Hb:c','Vb:c','Rb' or
           'Mb' itself.
           For example, layout code 'H0:V1:2' creates an image where image [0]
           is on the left, and images [1] and [2]
           vertically packed on the right.

           Default values: 'layout_code=X', 'montage_mode=2',
            output_mode='0' and 'processing_command=""'.

           Example:
             [#1] image.jpg sample ? +plasma[0] shape_cupid 256 normalize
       0,255
              frame 3,3,0 frame 10,10,255 to_rgb +montage A +montage[^-1]
              H1:V0:VH2:1H0:3

         mirror (+):
             { x | y | z }...{ x | y | z }

           Mirror selected images along specified axes.

           Example:
             [#1] image.jpg +mirror y +mirror[0] c
             [#2] image.jpg +mirror x +mirror y append_tiles 2,2

         permute (+):
             permutation_string

           Permute selected image axes by specified permutation.
           'permutation' is a combination of the character set {x|y|z|c},
           e.g. 'xycz', 'cxyz', ...

           Example:
             [#1] image.jpg permute yxzc

         rs:
             Shortcut for command 'rescale2d'.

         rescale2d:
             _width[%]={ 0:any | >0 },_height[%]={ 0:any | >0
       },-1=<_interpolation<=6,
               _mode={ 0:inside | 1:padded-inside | 2:outside | 3:cropped-
       outside }

           Resize selected 2D images while preserving aspect ratio.
           'interpolation' can be { -1:status only | 0:none | 1:nearest |
           2:average | 3:linear | 4=grid | 5=bicubic | 6=lanczos }.
           When 'interpolation==-1', image size is actually not modified, but
           the size that would have been used for the last selected image is
       returned
           in the status value.
           Each resized image size is computed according to the specified
           'mode':
            * If 'mode==0', image size is at most '(width,height)'.
            * If 'mode==1' or 'mode==3', image size is exactly
           '(width,height)'.
            * If 'mode==2', image size is at least '(width,height)'.
           (equivalent to shortcut command 'rs').

           Default values: 'width=height=0', 'interpolation=2' and
            'mode=0'.

         rs3d:
             Shortcut for command 'rescale3d'.

         rescale3d:
             _width[%]={ 0:any | >0 },_height[%]={ 0:any | >0 },_depth[%]={
       0:any | >0
               },-1=<_interpolation<=6,_mode={ 0:inside | 1:padded-inside |
               2:outside | 3 |
             cropped-outside }

           Resize selected 3D images while preserving aspect ratio.
           'interpolation' can be { -1:status only | 0:none | 1:nearest |
           2:average | 3:linear | 4=grid | 5=bicubic | 6=lanczos }.
           When 'interpolation==-1', image size is actually not modified, but
           the size that would have been used for the last selected image is
       returned
           in the status value.
           Each resized image size is computed according to the specified
           'mode':
            * If 'mode==0', image size is at most '(width,height)'.
            * If 'mode==1' or 'mode==3', image size is exactly
           '(width,height)'.
            * If 'mode==2', image size is at least '(width,height)'.
           (equivalent to shortcut command 'rs3d').

           Default values: 'width=height=depth=0',
            'interpolation=2' and 'mode=0'.

         r (+):
             Shortcut for command 'resize'.

         resize (+):
             {[image_w] | width>0[%]},_{[image_h] | height>0[%]},_{[image_d] |
               depth>0[%]},_{[image_s] | spectrum>0[%]},_interpolation,
               _boundary_conditions,_ax,_ay,_az,_ac

           Resize selected images with specified geometry.
           (equivalent to shortcut command 'r').

           'interpolation' can be { -1:none (memory content) | 0:none |
           1:nearest | 2:average | 3:linear | 4=grid | 5=bicubic | 6=lanczos
       }.
           'boundary_conditions' has different meanings, according to the
           chosen 'interpolation' mode :
           . When 'interpolation=={ -1 | 1 | 2 | 4 }', 'boundary_conditions'
       is
           meaningless.
           . When 'interpolation==0', 'boundary_conditions' can be {
           0:dirichlet | 1:neumann | 2:periodic | 3:mirror }.
           . When 'interpolation=={ 3 | 5 | 6 }', 'boundary_conditions' can be
           { 0:none | 1:neumann }.
           'ax,ay,az,ac' set the centering along each axis when
           'interpolation=0 or 4'
           (set to '0' by default, must be defined in range [0,1]).

           Default values: 'interpolation=1',
            'boundary_conditions=0' and 'ax=ay=az=ac=0'.

           Example:
             [#1] image.jpg +resize[-1] 256,128,1,3,2 +resize[-1]
       120%,120%,1,3,0,1,
              0.5,0.5 +resize[-1] 120%,120%,1,3,0,0,0.2,0.2 +resize[-1]
              [0],[0],1,3,4

         ri:
             Shortcut for command 'resize_as_image'.

         resize_as_image:
             [reference],_interpolation,_boundary_conditions,_ax,_ay,_az,_ac

           Resize selected images to the geometry of specified [reference]
       image.
           (equivalent to shortcut command 'ri').

           Default values: 'interpolation=1',
            'boundary_conditions=0' and 'ax=ay=az=ac=0'.

           Example:
             [#1] image.jpg sample duck +resize_as_image[-1] [-2]

         resize_mn:
             width[%]>=0,_height[%]>=0,_depth[%]>=0,_B_value,_C_value

           Resize selected images with Mitchell-Netravali filter (cubic).
           For details about the method, see:
       https://de.wikipedia.org/wiki/Mitchel
           l-Netravali-Filter.

           Default values: 'height=100%', 'depth=100%',
            'B=0.3333' and 'C=0.3333'.

           Example:
             [#1] image.jpg rescale2d 32 resize_mn 800%,800%

         resize_pow2:
             _interpolation,_boundary_conditions,_ax,_ay,_az,_ac

           Resize selected images so that each dimension is a power of 2.
           'interpolation' can be { -1:none (memory content) | 0:none |
           1:nearest | 2:average | 3:linear | 4:grid | 5:bicubic | 6:lanczos
       }.
           'boundary_conditions' has different meanings, according to the
           chosen 'interpolation' mode :
           . When 'interpolation=={ -1 | 1 | 2 | 4 }', 'boundary_conditions'
       is
           meaningless.
           . When 'interpolation==0', 'boundary_conditions' can be {
           0:dirichlet | 1:neumann | 2:periodic | 3:mirror }.
           . When 'interpolation=={ 3 | 5 | 6 }', 'boundary_conditions' can be
           { 0:none | 1:neumann }.
           'ax,ay,az,ac' set the centering along each axis when
           'interpolation=0'
           (set to '0' by default, must be defined in range [0,1]).

           Default values: 'interpolation=0',
            'boundary_conditions=0' and 'ax=ay=az=ac=0'.

           Example:
             [#1] image.jpg +resize_pow2[-1] 0

         rotate (+):
             angle,_interpolation,_boundary_conditions,_center_x[%],_center_y[%]
       |
             u,v,w,angle,interpolation,boundary_conditions,_center_x[%],_center_y[%],
               _center_z[%]

           Rotate selected images with specified angle (in deg.), and
       optionally 3D
           axis (u,v,w).
           'interpolation' can be { 0:none | 1:linear | 2:bicubic }.
           'boundary_conditions' can be { 0:dirichlet | 1:neumann |
           2:periodic | 3:mirror }.
           When a rotation center (cx,cy,_cz) is specified, the size of the
       image is
           preserved.

           Default values: 'interpolation=1',
            'boundary_conditions=0' and 'center_x=center_y=(undefined)'
            .

           Example:
             [#1] image.jpg +rotate -25,1,2,50%,50% rotate[0] 25

         rotate_tileable:
             angle,_max_size_factor>=0

           Rotate selected images by specified angle and make them tileable.
           If resulting size of an image is too big, the image is replaced by
       a 1x1
           image.

           Default values: 'max_size_factor=8'.

         rows:
             y0[%],_y1[%]

           Keep only specified rows of selected images.
           Dirichlet boundary conditions are used when specified rows are out
       of
           range.

           Default value: 'y1=y0'.

           Example:
             [#1] image.jpg rows -25%,50%

         scale2x:

           Resize selected images using the Scale2x algorithm.

           Example:
             [#1] image.jpg threshold 50% resize 50%,50% +scale2x

         scale3x:

           Resize selected images using the Scale3x algorithm.

           Example:
             [#1] image.jpg threshold 50% resize 33%,33% +scale3x

         scale_dcci2x:
             _edge_threshold>=0,_exponent>0,_extend_1px={ 0:false | 1:true }

           Double image size using directional cubic convolution
       interpolation,
           as described in
       https://en.wikipedia.org/wiki/Directional_Cubic_Convolut
           ion_Interpolation.

           Default values: 'edge_threshold=1.15', 'exponent=5' and
            'extend_1px=0'.

           Example:
             [#1] image.jpg +scale_dcci2x ,

         seamcarve:
             _width[%]>=0,_height[%]>=0,_is_priority_channel={ 0 | 1 },
               _is_antialiasing={ 0 | 1 },_maximum_seams[%]>=0

           Resize selected images with specified 2D geometry, using the seam-
       carving
           algorithm.

           Default values: 'height=100%', 'is_priority_channel=0',
            'is_antialiasing=1' and 'maximum_seams=25%'.

           Example:
             [#1] image.jpg seamcarve 60%

         shift (+):
             vx[%],_vy[%],_vz[%],_vc[%],_boundary_conditions,_interpolation={
               0:nearest_neighbor | 1:linear }

           Shift selected images by specified displacement vector.
           Displacement vector can be non-integer in which case linear
       interpolation
           should be chosen.
           'boundary_conditions' can be { 0:dirichlet | 1:neumann |
           2:periodic | 3:mirror }.

           Default value: 'boundary_conditions=0' and
            'interpolation=0'.

           Example:
             [#1] image.jpg +shift[0] 50%,50%,0,0,0 +shift[0] 50%,50%,0,0,1
              +shift[0] 50%,50%,0,0,2

         shrink_x:
             size_x>=0

           Shrink selected images along the x-axis.

           Example:
             [#1] image.jpg shrink_x 30

         shrink_xy:
             size>=0

           Shrink selected images along the xy-axes.

           Example:
             [#1] image.jpg shrink_xy 30

         shrink_xyz:
             size>=0

           Shrink selected images along the xyz-axes.

         shrink_y:
             size_y>=0

           Shrink selected images along the y-axis.

           Example:
             [#1] image.jpg shrink_y 30

         shrink_z:
             size_z>=0

           Shrink selected images along the z-axis.

         slices:
             z0[%],_z1[%]

           Keep only specified slices of selected images.
           Dirichlet boundary conditions are used when specified slices are
       out of
           range.

           Default value: 'z1=z0'.

         sort (+):
             _ordering={ + | - },_axis={ x | y | z | c }

           Sort pixel values of selected images.
           If 'axis' is specified, the sorting is done according to the data
       of
           the first column/row/slice/channel
           of selected images.

           Default values: 'ordering=+' and 'axis=(undefined)'.

           Example:
             [#1] 64 rand 0,100 +sort display_graph 400,300,3

         s (+):
             Shortcut for command 'split'.

         split (+):
             { x | y | z | c }...{ x | y | z | c },_split_mode |
             keep_splitting_values={ + | - },_{ x | y | z | c }...{ x | y | z
       | c },
               value1,_value2,... |
             (no arg)

           Split selected images along specified axes, or regarding to a
       sequence of
           scalar values
           (optionally along specified axes too).
           (equivalent to shortcut command 's').

           'split_mode' can be { 0:split according to constant values |
           >0:split in N parts | <0:split in parts of size -N }.

           Default value: 'split_mode=-1'.

           Example:
             [#1] image.jpg split c
             [#2] image.jpg split y,3
             [#3] image.jpg split x,-128
             [#4] 1,20,1,1,"1,2,3,4" +split -,2,3 append[1--1] y
             [#5] (1,2,2,3,3,3,4,4,4,4) +split x,0 append[1--1] y

         split_tiles:
             M!=0,_N!=0,_is_homogeneous={ 0 | 1 }

           Split selected images as a MxN array of tiles.
           If M or N is negative, it stands for the tile size instead.

           Default values: 'N=M' and 'is_homogeneous=0'.

           Example:
             [#1] image.jpg +local split_tiles 5,4 blur 3,0 sharpen 700
       append_tiles
              4,5 done

         undistort:
             -1<=_amplitude<=1,_aspect_ratio,_zoom,_center_x[%],_center_y[%],
               _boundary_conditions

           Correct barrel/pincushion distortions occurring with wide-angle
       lens.
           References:
           [1] Zhang Z. (1999). Flexible camera calibration by viewing a plane
       from
           unknown orientation.
           [2] Andrew W. Fitzgibbon (2001). Simultaneous linear estimation of
           multiple view geometry and lens distortion.
           'boundary_conditions' can be { 0:dirichlet | 1:neumann |
           2:periodic | 3:mirror }.

           Default values: 'amplitude=0.25', 'aspect_ratio=0',
            'zoom=0', 'center_x=center_y=50%' and
            'boundary_conditions=0'.

         y (+):
             Shortcut for command 'unroll'.

         unroll (+):
             _axis={ x | y | z | c }

           Unroll selected images along specified axis.
           (equivalent to shortcut command 'y').

           Default value: 'axis=y'.

           Example:
             [#1] (1,2,3;4,5,6;7,8,9) +unroll y

         upscale_smart:
             width[%],_height[%],_depth,_smoothness>=0,_anisotropy=[0,1],sharpening>=0

           Upscale selected images with an edge-preserving algorithm.

           Default values: 'height=100%', 'depth=100%',
            'smoothness=2', 'anisotropy=0.4' and 'sharpening=10'.

           Example:
             [#1] image.jpg rescale2d ,100 +upscale_smart 500%,500% append x

         volumetric2d:
             _x[%],_y[%],_z[%],_separator_size>=0

           Convert selected 3D volumetric images into a 2D representation.

           Default values: 'x=y=z=50%' and 'separator_size=0'.

           Example:
             [#1] image.jpg rescale2d 64 animate noise,0,100,50 cut 0,255
       append z
              volumetric2d 50%,50%,50%,1

         11.8. Filtering
               ---------

         bandpass:
             _min_freq[%],_max_freq[%]

           Apply bandpass filter to selected images.

           Default values: 'min_freq=0' and 'max_freq=20%'.

           Example:
             [#1] image.jpg bandpass 1%,3%

           Tutorial: https://gmic.eu/oldtutorial/_bandpass

         bilateral (+):
             [guide],std_deviation_s[%]>=0,std_deviation_r[%]>=0,_sampling_s>=0,
               _sampling_r>=0 |
             std_deviation_s[%]>=0,std_deviation_r[%]>=0,_sampling_s>=0,_sampling_r>=0

           Blur selected images by anisotropic (eventually joint/cross)
       bilateral
           filtering.
           If a guide image is provided, it is used for drive the smoothing
       filter.
           A guide image must be of the same xyz-size as the selected images.
           Set 'sampling' arguments to '0' for automatic adjustment.

           Example:
             [#1] image.jpg repeat 5 { bilateral 10,10 }

         b (+):
             Shortcut for command 'blur'.

         blur (+):
             std_deviation>=0[%],_boundary_conditions,_kernel |
             axes,std_deviation>=0[%],_boundary_conditions,_kernel

           Blur selected images by a deriche or gaussian filter (recursive
           implementation).
           (equivalent to shortcut command 'b').

           'boundary_conditions' can be { 0:dirichlet | 1:neumann |
           2:periodic | 3:mirror }.
           'kernel' can be { 0:deriche | 1:gaussian }.
           When specified, argument 'axes' is a sequence of { x | y | z | c
           }.
           Specifying one axis multiple times apply also the blur multiple
       times.

           Default values: 'boundary_conditions=1' and 'kernel=1'.

           Example:
             [#1] image.jpg +blur 5,0 +blur[0] 5,1
             [#2] image.jpg +blur y,10%

           Tutorial: https://gmic.eu/oldtutorial/_blur

         blur_angular:
             amplitude[%],_center_x[%],_center_y[%]

           Apply angular blur on selected images.

           Default values: 'center_x=center_y=50%'.

           Example:
             [#1] image.jpg blur_angular 2%

           Tutorial: https://gmic.eu/oldtutorial/_blur_angular

         blur_bloom:
             _amplitude>=0,_ratio>=0,_nb_iter>=0,_blend_operator={ + | max |
       min },
               _kernel={ 0:deriche | 1:gaussian | 2:box | 3:triangle |
       4:quadratic
               },_normalize_scales={ 0 | 1 },_axes

           Apply a bloom filter that blend multiple blur filters of different
       radii,
           resulting in a larger but sharper glare than a simple blur.
           When specified, argument 'axes' is a sequence of { x | y | z | c
           }.
           Specifying one axis multiple times apply also the blur multiple
       times.
           Reference: Masaki Kawase, "Practical Implementation of High Dynamic
       Range
           Rendering", GDC 2004.

           Default values: 'amplitude=1', 'ratio=2',
            'nb_iter=5', 'blend_operator=+', 'kernel=1',
            'normalize_scales=0' and 'axes=(all)'

           Example:
             [#1] image.jpg blur_bloom ,

         blur_linear:
             amplitude1[%],_amplitude2[%],_angle,_boundary_conditions={
       0:dirichlet |
               1:neumann }

           Apply linear blur on selected images, with specified angle and
       amplitudes.

           Default values: 'amplitude2=0', 'angle=0' and
            'boundary_conditions=1'.

           Example:
             [#1] image.jpg blur_linear 10,0,45

           Tutorial: https://gmic.eu/oldtutorial/_blur_linear

         blur_radial:
             amplitude[%],_center_x[%],_center_y[%]

           Apply radial blur on selected images.

           Default values: 'center_x=center_y=50%'.

           Example:
             [#1] image.jpg blur_radial 2%

           Tutorial: https://gmic.eu/oldtutorial/_blur_radial

         blur_selective:
             sigma>=0,_edges>0,_nb_scales>0

           Blur selected images using selective gaussian scales.

           Default values: 'sigma=5', 'edges=0.5' and
            'nb_scales=5'.

           Example:
             [#1] image.jpg noise 20 cut 0,255 +local[-1] repeat 4 {
       blur_selective ,
               } done

           Tutorial: https://gmic.eu/oldtutorial/_blur_selective

         blur_x:
             amplitude[%]>=0,_boundary_conditions={ 0:dirichlet | 1:neumann |
               2:periodic | 3:mirror }

           Blur selected images along the x-axis.

           Default value: 'boundary_conditions=1'.

           Example:
             [#1] image.jpg +blur_x 6

           Tutorial: https://gmic.eu/oldtutorial/_blur_x

         blur_xy:
             amplitude_x[%],amplitude_y[%],_boundary_conditions={ 0:dirichlet
       |
               1:neumann | 2:periodic | 3:mirror }

           Blur selected images along the X and Y axes.

           Default value: 'boundary_conditions=1'.

           Example:
             [#1] image.jpg +blur_xy 6

           Tutorial: https://gmic.eu/oldtutorial/_blur_y

         blur_xyz:
             amplitude_x[%],amplitude_y[%],amplitude_z,_boundary_conditions={
               0:dirichlet | 1:neumann | 2:periodic | 3:mirror }

           Blur selected images along the X, Y and Z axes.

           Default value: 'boundary_conditions=1'.

           Tutorial: https://gmic.eu/oldtutorial/_blur_xyz

         blur_y:
             amplitude[%]>=0,_boundary_conditions={ 0:dirichlet | 1:neumann |
               2:periodic | 3:mirror }

           Blur selected images along the y-axis.

           Default value: 'boundary_conditions=1'.

           Example:
             [#1] image.jpg +blur_y 6

           Tutorial: https://gmic.eu/oldtutorial/_blur_y

         blur_z:
             amplitude[%]>=0,_boundary_conditions={ 0:dirichlet | 1:neumann |
               2:periodic | 3:mirror }

           Blur selected images along the z-axis.

           Default value: 'boundary_conditions=1'.

           Tutorial: https://gmic.eu/oldtutorial/_blur_z

         boxfilter (+):
             size>=0[%],_order,_boundary_conditions,_nb_iter>=0 |
             axes,size>=0[%],_order,_boundary_conditions,_nb_iter>=0

           Blur selected images by a box filter of specified size (fast
       recursive
           implementation).
           'order' can be { 0:smooth | 1:1st-derivative | 2:2nd-derivative
           }.
           'boundary_conditions' can be { 0:dirichlet | 1:neumann |
           2:periodic | 3:mirror }.
           When specified, argument 'axes' is a sequence of { x | y | z | c
           }.
           Specifying one axis multiple times apply also the blur multiple
       times.

           Default values: 'order=0', 'boundary_conditions=1' and
            'nb_iter=1'.

           Example:
             [#1] image.jpg +boxfilter 5%
             [#2] image.jpg +boxfilter y,3,1

         bump2normal:

           Convert selected bumpmaps to normalmaps.

           Example:
             [#1] 300,300 circle 50%,50%,128,1,1 blur 5% bump2normal

         closing:
             size>=0 |
             size_x>=0,size_y>=0,_size_z>=0 |
             [kernel],_boundary_conditions,_is_real={ 0:binary-mode | 1:real-
       mode }

           Apply morphological closing to selected images.
           'boundary_conditions' can be { 0:dirichlet | 1:neumann |
           2:periodic | 3:mirror }.

           Default values: 'size_z=1', 'boundary_conditions=1' and
            'is_real=0'.

           Example:
             [#1] image.jpg +closing 10

         closing_circ:
             _size>=0,_is_real={ 0 | 1 }

           Apply circular dilation of selected images by specified size.

           Default values: 'boundary_conditions=1' and 'is_real=0'.

           Example:
             [#1] image.jpg +closing_circ 7

         compose_freq:

           Compose selected low and high frequency parts into new images.

           Example:
             [#1] image.jpg split_freq 2% mirror[-1] x compose_freq

         convolve (+):
             [mask],_boundary_conditions,_is_normalized={ 0 | 1
       },_channel_mode,
               _xcenter,_ycenter,_zcenter,_xstart,_ystart,_zstart,_xend,_yend,
               _zend,_xstride,_ystride,_zstride,_xdilation,_ydilation,_zdilation,
               interpolation_type

           Convolve selected images by specified mask.
           'boundary_conditions' can be { 0:dirichlet | 1:neumann |
           2:periodic | 3:mirror }.
           'channel_mode' can be { 0:all | 1:one-for-one | 2:partial sum |
           3:full sum }.
           'interpolation_type' can be { 0:nearest-neighbor | 1:linear }.

           Default values: 'boundary_conditions=1',
            'is_normalized=0', 'channel_mode=1',
            'xcenter=ycenter=zcenter=(undefined)', 'xstart=ystart=zstart=0
            ', 'xend=yend=zend=(max-coordinates)',
            'xstride=ystride=zstride=1', 'xdilation=ydilation=zdilation=1
       fR' and 'interpolation_type=0'.

           Example:
             [#1] image.jpg (0,1,0;1,-4,1;0,1,0) convolve[-2] [-1] keep[-2]
             [#2] image.jpg (0,1,0) resize[-1] 130,1,1,1,3 +convolve[0] [1]

           Tutorial: https://gmic.eu/oldtutorial/_convolve

         convolve_fft:
             [mask],_boundary_conditions

           Convolve selected images with specified mask, in the fourier
       domain.
           'boundary_conditions' can be { 0:dirichlet | 1:neumann |
           2:periodic | 3:mirror }.

           Example:
             [#1] image.jpg 100%,100% gaussian[-1] 20,1,45 +convolve_fft[0]
       [1]

         correlate (+):
             [mask],_boundary_conditions,_is_normalized={ 0 | 1
       },_channel_mode,
               _xcenter,_ycenter,_zcenter,_xstart,_ystart,_zstart,_xend,_yend,
               _zend,_xstride,_ystride,_zstride,_xdilation,_ydilation,_zdilation,
               interpolation_type

           Correlate selected images by specified mask.
           'boundary_conditions' can be { 0:dirichlet | 1:neumann |
           2:periodic | 3:mirror }.
           'channel_mode' can be { 0:all | 1:one-for-one | 2:partial sum |
           3:full sum }.
           'interpolation_type' can be { 0:nearest-neighbor | 1:linear }.

           Default values: 'boundary_conditions=1',
            'is_normalized=0', 'channel_mode=1',
            'xcenter=ycenter=zcenter=-1', 'xstart=ystart=zstart=0',
            'xend=yend=zend=(max-coordinates)', 'xstride=ystride=zstride=1
            ', 'xdilation=ydilation=zdilation=1' and
            'interpolation_type=0'.

           Example:
             [#1] image.jpg (0,1,0;1,-4,1;0,1,0) correlate[-2] [-1] keep[-2]
             [#2] image.jpg +crop 40%,40%,60%,60% +correlate[0] [-1],0,1

         cross_correlation:
             [mask]

           Compute cross-correlation of selected images with specified mask.

           Example:
             [#1] image.jpg +shift -30,-20 +cross_correlation[0] [1]

         curvature:

           Compute isophote curvatures on selected images.

           Example:
             [#1] image.jpg blur 10 curvature

         dct:
             _{ x | y | z }...{ x | y | z } |
             (no arg)

           Compute the discrete cosine transform of selected images,
       optionally along
           the specified axes only.
           Output images are always evenly sized, so this command may change
       the size
           of the selected images.

           Default values: (no arg)
           See also: idct.

           Example:
             [#1] image.jpg +dct +idct[-1] abs[-2] +[-2] 1 log[-2]

           Tutorial: https://gmic.eu/oldtutorial/_dct-and-idct

         deblur:
             amplitude[%]>=0,_nb_iter>=0,_dt>=0,_regul>=0,_regul_type={
       0:Tikhonov |
               1:meancurv. | 2:TV }

           Deblur image using a regularized Jansson-Van Cittert algorithm.

           Default values: 'nb_iter=10', 'dt=20', 'regul=0.7'
            and 'regul_type=1'.

           Example:
             [#1] image.jpg blur 3 +deblur 3,40,20,0.01

         deblur_goldmeinel:
             sigma>=0,_nb_iter>=0,_acceleration>=0,_kernel_type={ 0:deriche |
               1:gaussian }.

           Deblur selected images using Gold-Meinel algorithm

           Default values: 'nb_iter=8', 'acceleration=1' and
            'kernel_type=1'.

           Example:
             [#1] image.jpg +blur 1 +deblur_goldmeinel[-1] 1

         deblur_richardsonlucy:
             sigma>=0, nb_iter>=0, _kernel_type={ 0:deriche | 1:gaussian }.

           Deblur selected images using Richardson-Lucy algorithm.

           Default values: 'nb_iter=50' and 'kernel_type=1'.

           Example:
             [#1] image.jpg +blur 1 +deblur_richardsonlucy[-1] 1

         deconvolve_fft:
             [kernel],_regularization>=0

           Deconvolve selected images by specified mask in the fourier space.

           Default value: 'regularization>=0'.

           Example:
             [#1] image.jpg +gaussian 5 +convolve_fft[0] [1]
       +deconvolve_fft[-1] [1]

         deinterlace:
             _method={ 0 | 1 }

           Deinterlace selected images ('method' can be { 0:standard or
           1:motion-compensated }).

           Default value: 'method=0'.

           Example:
             [#1] image.jpg +rotate 3,1,1,50%,50% resize 100%,50% resize
       100%,200%,1,
              3,4 shift[-1] 0,1 add +deinterlace 1

         denoise (+):
             [guide],std_deviation_s[%]>=0,std_deviation_r[%]>=0,_patch_size>0,
               _lookup_size>0,_smoothness,_fast_approx={ 0 | 1 } |
             std_deviation_s[%]>=0,std_deviation_r[%]>=0,_patch_size>0,_lookup_size>0,
               _smoothness,_fast_approx={ 0 | 1 }

           Denoise selected images by non-local patch averaging.

           Default values: 'patch_size=5', 'lookup_size=6' and
            'smoothness=1'.

           Example:
             [#1] image.jpg +denoise 5,5,8

         denoise_haar:
             _threshold>=0,_nb_scales>=0,_cycle_spinning>0

           Denoise selected images using haar-wavelet thresholding with cycle
           spinning.
           Set 'nb_scales==0' to automatically determine the optimal number of
           scales.

           Default values: 'threshold=1.4', 'nb_scale=0' and
            'cycle_spinning=10'.

           Example:
             [#1] image.jpg noise 20 cut 0,255 +denoise_haar[-1] 0.8

         denoise_cnn:
             _noise_type={ 0:soft | 1:heavy | 2:heavy (faster) |
       3:poisson+gaussian |
               4:poisson+gaussian2 },_patch_size>0

           Denoise selected images using a convolutional neural network (CNN).
           Input value range should be [0,255]. Output value range is [0,255].

           Default value: 'patch_size=64'.

           Example:
             [#1] image.jpg noise 20 cut 0,255 +denoise_cnn

         denoise_patchpca:
             _strength>=0,_patch_size>0,_lookup_size>0,_spatial_sampling>0

           Denoise selected images using the patch-pca algorithm.

           Default values: 'patch_size=7', 'lookup_size=11',
            'details=1.8' and 'spatial_sampling=5'.

           Example:
             [#1] image.jpg +noise 20 cut[-1] 0,255 +denoise_patchpca[-1] ,

         deriche (+):
             std_deviation>=0[%],order={ 0 | 1 | 2 },axis={ x | y | z | c },
               _boundary_conditions

           Apply Deriche recursive filter on selected images, along specified
       axis
           and with
           specified standard deviation, order and boundary conditions.
           'boundary_conditions' can be { 0:dirichlet | 1:neumann |
           2:periodic | 3:mirror }.

           Default value: 'boundary_conditions=1'.

           Example:
             [#1] image.jpg deriche 3,1,x
             [#2] image.jpg +deriche 30,0,x deriche[-2] 30,0,y add

           Tutorial: https://gmic.eu/oldtutorial/_deriche

         dilate (+):
             size>=0 |
             size_x>=0,size_y>=0,size_z>=0 |
             [kernel],_boundary_conditions,_is_real={ 0:binary-mode | 1:real-
       mode }

           Dilate selected images by a rectangular or the specified
       structuring
           element.
           'boundary_conditions' can be { 0:dirichlet | 1:neumann |
           2:periodic | 3:mirror }.

           Default values: 'size_z=1', 'boundary_conditions=1' and
            'is_real=0'.

           Example:
             [#1] image.jpg +dilate 10

         dilate_circ:
             _size>=0,_boundary_conditions,_is_real={ 0 | 1 }

           Apply circular dilation of selected images by specified size.
           'boundary_conditions' can be { 0:dirichlet | 1:neumann |
           2:periodic | 3:mirror }.

           Default values: 'boundary_conditions=1' and 'is_real=0'.

           Example:
             [#1] image.jpg +dilate_circ 7

         dilate_oct:
             _size>=0,_boundary_conditions,_is_real={ 0 | 1 }

           Apply octagonal dilation of selected images by specified size.

           Default values: 'boundary_conditions=1' and 'is_real=0'.

           Example:
             [#1] image.jpg +dilate_oct 7

         dilate_threshold:
             size_x>=1,size_y>=1,size_z>=1,_threshold>=0,_boundary_conditions

           Dilate selected images in the (X,Y,Z,I) space.
           'boundary_conditions' can be { 0:dirichlet | 1:neumann |
           2:periodic | 3:mirror }.

           Default values: 'size_y=size_x', 'size_z=1',
            'threshold=255' and 'boundary_conditions=1'.

         divergence:

           Compute divergence of selected vector fields.

           Example:
             [#1] image.jpg luminance +gradient append[-2,-1] c divergence[-1]

         dog:
             _sigma1>=0[%],_sigma2>=0[%]

           Compute difference of gaussian on selected images.

           Default values: 'sigma1=2%' and 'sigma2=3%'.

           Example:
             [#1] image.jpg dog 2,3

         diffusiontensors:
             _sharpness>=0,0<=_anisotropy<=1,_alpha[%],_sigma[%],is_sqrt={ 0 |
       1 }

           Compute the diffusion tensors of selected images for edge-
       preserving
           smoothing algorithms.

           Default values: 'sharpness=0.7', 'anisotropy=0.3',
            'alpha=0.6', 'sigma=1.1' and 'is_sqrt=0'.

           Example:
             [#1] image.jpg diffusiontensors 0.8 abs pow 0.2

           Tutorial: https://gmic.eu/oldtutorial/_diffusiontensors

         edges:
             _threshold[%]>=0

           Estimate contours of selected images.

           Default value: 'edges=15%'

           Example:
             [#1] image.jpg +edges 15%

         erode (+):
             size>=0 |
             size_x>=0,size_y>=0,_size_z>=0 |
             [kernel],_boundary_conditions,_is_real={ 0:binary-mode | 1:real-
       mode }

           Erode selected images by a rectangular or the specified structuring
           element.
           'boundary_conditions' can be { 0:dirichlet | 1:neumann |
           2:periodic | 3:mirror }.

           Default values: 'size_z=1', 'boundary_conditions=1' and
            'is_real=0'.

           Example:
             [#1] image.jpg +erode 10

         erode_circ:
             _size>=0,_boundary_conditions,_is_real={ 0 | 1 }

           Apply circular erosion of selected images by specified size.
           'boundary_conditions' can be { 0:dirichlet | 1:neumann |
           2:periodic | 3:mirror }.

           Default values: 'boundary_conditions=1' and 'is_real=0'.

           Example:
             [#1] image.jpg +erode_circ 7

         erode_oct:
             _size>=0,_boundary_conditions,_is_real={ 0 | 1 }

           Apply octagonal erosion of selected images by specified size.

           Default values: 'boundary_conditions=1' and 'is_real=0'.

           Example:
             [#1] image.jpg +erode_oct 7

         erode_threshold:
             size_x>=1,size_y>=1,size_z>=1,_threshold>=0,_boundary_conditions

           Erode selected images in the (X,Y,Z,I) space.
           'boundary_conditions' can be { 0:dirichlet | 1:neumann |
           2:periodic | 3:mirror }.

           Default values: 'size_y=size_x', 'size_z=1',
            'threshold=255' and 'boundary_conditions=1'.

         fft (+):
             _{ x | y | z }...{ x | y | z }

           Compute the direct fourier transform (real and imaginary parts) of
           selected images,
           optionally along the specified axes only.
           See also: ifft.

           Example:
             [#1] image.jpg luminance +fft append[-2,-1] c norm[-1] log[-1]
              shift[-1] 50%,50%,0,0,2
             [#2] image.jpg w2:=int(w/2) h2:=int(h/2) fft shift $w2,$h2,0,0,2
              ellipse $w2,$h2,30,30,0,1,0 shift -$w2,-$h2,0,0,2 ifft
              remove[-1]

           Tutorial: https://gmic.eu/oldtutorial/_fft

         g (+):
             Shortcut for command 'gradient'.

         gradient:
             { x | y | z | c }...{ x | y | z | c
       },_scheme,_boundary_conditions |
             (no arg)

           Compute the gradient components (first derivatives) of selected
       images,
           along specified axes.
           (equivalent to shortcut command 'g').

           'scheme' can be { -1:backward | 0:centered | 1:forward | 2:sobel
           | 3:rotation-invariant (default) | 4:deriche | 5:vanvliet }.
           'boundary_conditions' can be { 0:dirichlet | 1:neumann |
           2:periodic | 3:mirror }.
           (no arg) compute all significant components.

           Default values: 'scheme=0' and 'boundary_conditions=1'.

           Example:
             [#1] image.jpg gradient

           Tutorial: https://gmic.eu/oldtutorial/_gradient

         gradient_norm:

           Compute gradient norm of selected images.

           Example:
             [#1] image.jpg gradient_norm equalize

           Tutorial: https://gmic.eu/oldtutorial/_gradient_norm

         gradient_orientation:
             _dimension={ 1 | 2 | 3 }

           Compute N-d gradient orientation of selected images.

           Default value: 'dimension=3'.

           Example:
             [#1] image.jpg +gradient_orientation 2

         guided (+):
             [guide],radius[%]>=0,regularization[%]>=0 |
             radius[%]>=0,regularization[%]>=0

           Blur selected images by guided image filtering.
           If a guide image is provided, it is used to drive the smoothing
       process.
           A guide image must be of the same xyz-size as the selected images.
           This command implements the filtering algorithm described in:
           He, Kaiming; Sun, Jian; Tang, Xiaoou, "Guided Image Filtering",
           IEEE Transactions on Pattern Analysis and Machine Intelligence,
       vol.35,
           no.6, pp.1397,1409, June 2013

           Example:
             [#1] image.jpg +guided 5,400

         haar:
             scale>0

           Compute the direct haar multiscale wavelet transform of selected
       images.
           See also: ihaar.

           Tutorial: https://gmic.eu/oldtutorial/_haar

         heat_flow:
             _nb_iter>=0,_dt,_keep_sequence={ 0 | 1 }

           Apply iterations of the heat flow on selected images.

           Default values: 'nb_iter=10', 'dt=30' and
            'keep_sequence=0'.

           Example:
             [#1] image.jpg +heat_flow 20

         hessian:
             { xx | xy | xz | yy | yz | zz }...{ xx | xy | xz | yy | yz | zz
       },
               _boundary_conditions |
             (no arg) :

           Compute the hessian components (second derivatives) of selected
       images
           along specified axes.
           'boundary_conditions' can be { 0:dirichlet | 1:neumann |
           2:periodic | 3:mirror }.
           (no arg) compute all significant components.

           Default value: 'boundary_conditions=1'.

           Example:
             [#1] image.jpg hessian

         idct:
             _{ x | y | z }...{ x | y | z } |
             (no arg)

           Compute the inverse discrete cosine transform of selected images,
           optionally along the specified axes only.
           Output images are always evenly sized, so this command may change
       the size
           of the selected images.
           (dct images obtained with the 'dct' command are evenly sized
       anyway).

           Default values: (no arg)
           See also: dct.

           Tutorial: https://gmic.eu/oldtutorial/_dct-and-idct

         iee:

           Compute gradient-orthogonal-directed 2nd derivative of image(s).

           Example:
             [#1] image.jpg iee

         ifft (+):
             _{ x | y | z }...{ x | y | z }

           Compute the inverse fourier transform (real and imaginary parts) of
           selected images.
           optionally along the specified axes only.
           See also: fft.

           Tutorial: https://gmic.eu/oldtutorial/_fft

         ihaar:
             scale>0

           Compute the inverse haar multiscale wavelet transform of selected
       images.
           See also: haar.

           Tutorial: https://gmic.eu/oldtutorial/_haar

         ilaplacian:
             { nb_iterations>0 | 0 },_[initial_estimate]

           Invert selected Laplacian images.
           If given 'nb_iterations' is '0', inversion is done in Fourier
           space (single iteration),
           otherwise, by applying 'nb_iterations' of a Laplacian-inversion PDE
           flow.
           Note that the resulting inversions are just estimation of
           possible/approximated solutions.

           Default values: 'nb_iterations=0' and
            '[initial_estimated]=(undefined)'.

           Example:
             [#1] image.jpg +laplacian +ilaplacian[-1] 0

         inn:

           Compute gradient-directed 2nd derivative of image(s).

           Example:
             [#1] image.jpg inn

         inpaint (+):
             [mask] |
             [mask],0,_fast_method |
             [mask],_patch_size>=1,_lookup_size>=1,_lookup_factor>=0,
               _lookup_increment!=0,_blend_size>=0,0<=_blend_threshold<=1,
               _blend_decay>=0,_blend_scales>=1,_is_blend_outer={ 0 | 1 }

           Inpaint selected images by specified mask.
           If no patch size (or 0) is specified, inpainting is done using a
       fast
           average or median algorithm.
           Otherwise, it used a patch-based reconstruction method, that can be
       very
           time consuming.
           'fast_method' can be { 0:low-connectivity average |
           1:high-connectivity average | 2:low-connectivity median |
           3:high-connectivity median }.

           Default values: 'patch_size=0', 'fast_method=1',
            'lookup_size=22', 'lookup_factor=0.5',
            'lookup_increment=1', 'blend_size=0',
            'blend_threshold=0', 'blend_decay=0.05',
            'blend_scales=10' and 'is_blend_outer=1'.

           Example:
             [#1] image.jpg 100%,100% ellipse 50%,50%,30,30,0,1,255 ellipse
       20%,20%,
              30,10,0,1,255 +inpaint[-2] [-1] remove[-2]
             [#2] image.jpg 100%,100% circle 30%,30%,30,1,255,0,255 circle
       70%,70%,
              50,1,255,0,255 +inpaint[0] [1],5,15,0.5,1,9,0 remove[1]

         inpaint_pde:
             [mask],_nb_scales[%],_diffusion_type={ 0:isotropic | 1:Delaunay-
       guided |
               2:edge-guided | 3:mask-guided },_diffusion_iter>=0

           Inpaint selected images by specified mask using a multiscale
           transport-diffusion algorithm.
           Argument 'nb_scales' sets the number of scales used in the
           multi-scale resolution scheme.
            * When the '%' qualifier is used for 'nb_scales', the number
           of used scales is relative to 'nb_scales_max =
       ceil(log2(max(w,h,d)))'.
            * When 'nb_scales<0', it determines the minimum image size
           encountered at the lowest scale.
           If 'diffusion_type==3', non-zero values of the mask (e.g. a
       distance
           function) are used
           to guide the diffusion process.

           Default values: 'nb_scales=-9', 'diffusion_type=1' and
            'diffusion_iter=20'.

           Example:
             [#1] image.jpg 100%,100% ellipse[-1] 30%,30%,40,30,0,1,255
              +inpaint_pde[0] [1]

         inpaint_flow:
             [mask],_nb_global_iter>=0,_nb_local_iter>=0,_dt>0,_alpha>=0,_sigma>=0

           Apply iteration of the inpainting flow on selected images.

           Default values: 'nb_global_iter=10', 'nb_local_iter=100',
             'dt=5', 'alpha=1' and 'sigma=3'.

           Example:
             [#1] image.jpg 100%,100% ellipse[-1] 30%,30%,40,30,0,1,255
              inpaint_flow[0] [1]

         inpaint_holes:
             maximal_area[%]>=0,_tolerance>=0,_is_high_connectivity={ 0 | 1 }

           Inpaint all connected regions having an area less than specified
       value.

           Default values: 'maximal_area=4', 'tolerance=0' and
            'is_high_connectivity=0'.

           Example:
             [#1] image.jpg noise 5%,2 +inpaint_holes 8,40

         inpaint_morpho:
             [mask]

           Inpaint selected images by specified mask using morphological
       operators.

           Example:
             [#1] image.jpg 100%,100% ellipse[-1] 30%,30%,40,30,0,1,255
              +inpaint_morpho[0] [1]

         inpaint_matchpatch:
             [mask],_nb_scales={ 0:auto | >0
       },_patch_size>0,_nb_iterations_per_scale>0,
               _blend_size>=0,_allow_outer_blending={ 0 | 1 },
               _is_already_initialized={ 0 | 1 }

           Inpaint selected images by specified binary mask, using a multi-
       scale
           matchpatch algorithm.

           Default values: 'nb_scales=0', 'patch_size=9',
            'nb_iterations_per_scale=10', 'blend_size=5',
            'allow_outer_blending=1' and 'is_already_initialized=0'.

           Example:
             [#1] image.jpg 100%,100% ellipse[-1] 30%,30%,40,30,0,1,255
              +inpaint_matchpatch[0] [1]

         kuwahara:
             size>0

           Apply Kuwahara filter of specified size on selected images.

           Example:
             [#1] image.jpg kuwahara 9

         laplacian:

           Compute Laplacian of selected images.

           Example:
             [#1] image.jpg laplacian

         lic:
             _amplitude>0,_channels>0

           Render LIC representation of selected vector fields.

           Default values: 'amplitude=30' and 'channels=1'.

           Example:
             [#1] 400,400,1,2,'!c?x-w/2:y-h/2' +lic 200,3 quiver[-2]
       [-2],10,1,1,1,
              255

         map_tones:
             _threshold>=0,_gamma>=0,_smoothness>=0,nb_iter>=0

           Apply tone mapping operator on selected images, based on Poisson
       equation.

           Default values: 'threshold=0.1', 'gamma=0.8',
            'smoothness=0.5' and 'nb_iter=30'.

           Example:
             [#1] image.jpg +map_tones ,

         map_tones_fast:
             _radius[%]>=0,_power>=0

           Apply fast tone mapping operator on selected images.

           Default values: 'radius=3%' and 'power=0.3'.

           Example:
             [#1] image.jpg +map_tones_fast ,

         meancurvature_flow:
             _nb_iter>=0,_dt,_keep_sequence={ 0 | 1 }

           Apply iterations of the mean curvature flow on selected images.

           Default values: 'nb_iter=10', 'dt=30' and
            'keep_sequence=0'.

           Example:
             [#1] image.jpg +meancurvature_flow 20

         median (+):
             size>=0,_threshold>0

           Apply (opt. thresholded) median filter on selected images with
       structuring
           element size x size.

           Example:
             [#1] image.jpg +median 5

         merge_alpha:

           Merge selected alpha detail scales into a single image.
           Alpha detail scales have been obtained with command split_alpha.

         nlmeans:
             [guide],_patch_radius>0,_spatial_bandwidth>0,_tonal_bandwidth>0,
               _patch_measure_command |
             _patch_radius>0,_spatial_bandwidth>0,_tonal_bandwidth>0,
               _patch_measure_command

           Apply non local means denoising of Buades et al, 2005. on selected
       images.
           The patch is a gaussian function of 'std_patch_radius'.
           The spatial kernel is a rectangle of radius 'spatial_bandwidth'.
           The tonal kernel is exponential ('exp(-d^2/_tonal_bandwidth^2)')
           with 'd' the euclidean distance between image patches.

           Default values: 'patch_radius=4', 'spatial_bandwidth=4',
            'tonal_bandwidth=10' and 'patch_measure_command=-norm'.

           Example:
             [#1] image.jpg +noise 10 nlmeans[-1] 4,4,{0.6*${-std_noise}}

         nlmeans_core:
             _reference_image,_scaling_map,_patch_radius>0,_spatial_bandwidth>0

           Apply non local means denoising using a image for weight and a map
       for
           scaling

         normalize_local:
             _amplitude>=0,_radius>0,_n_smooth>=0[%],_a_smooth>=0[%],_is_cut={
       0 | 1 },
               _min=0,_max=255

           Normalize selected images locally.

           Default values: 'amplitude=3', 'radius=16',
            'n_smooth=4%', 'a_smooth=2%', 'is_cut=1',
            'min=0' and 'max=255'.

           Example:
             [#1] image.jpg normalize_local 8,10

         normalized_cross_correlation:
             [mask]

           Compute normalized cross-correlation of selected images with
       specified
           mask.

           Example:
             [#1] image.jpg +shift -30,-20 +normalized_cross_correlation[0]
       [1]

         opening:
             size>=0 |
             size_x>=0,size_y>=0,_size_z>=0 |
             [kernel],_boundary_conditions,_is_real={ 0:binary-mode | 1:real-
       mode }

           Apply morphological opening to selected images.
           'boundary_conditions' can be { 0:dirichlet | 1:neumann |
           2:periodic | 3:mirror }.

           Default values: 'size_z=1', 'boundary_conditions=1' and
            'is_real=0'.

           Example:
             [#1] image.jpg +opening 10

         opening_circ:
             _size>=0,_is_real={ 0 | 1 }

           Apply circular opening of selected images by specified size.

           Default values: 'boundary_conditions=1' and 'is_real=0'.

           Example:
             [#1] image.jpg +opening_circ 7

         percentile:
             [mask],0<=_min_percentile[%]<=100,0<=_max_percentile[%]<=100.

           Apply percentile averaging filter to selected images.

           Default values: 'min_percentile=0' and
            'max_percentile=100'.

           Example:
             [#1] image.jpg shape_circle 11,11 +percentile[0] [1],25,75

         peronamalik_flow:
             K_factor>0,_nb_iter>=0,_dt,_keep_sequence={ 0 | 1 }

           Apply iterations of the Perona-Malik flow on selected images.

           Default values: 'K_factor=20', 'nb_iter=5', 'dt=5'
            and 'keep_sequence=0'.

           Example:
             [#1] image.jpg +heat_flow 20

         phase_correlation:
             [destination]

           Estimate translation vector between selected source images and
       specified
           destination.

           Example:
             [#1] image.jpg +shift -30,-20 +phase_correlation[0] [1]
       unroll[-1] y

         pde_flow:
             _nb_iter>=0,_dt,_velocity_command,_keep_sequence={ 0 | 1 }

           Apply iterations of a generic PDE flow on selected images.

           Default values: 'nb_iter=10', 'dt=30',
            'velocity_command=laplacian' and 'keep_sequence=0'.

           Example:
             [#1] image.jpg +pde_flow 20

         periodize_poisson:

           Periodize selected images using a Poisson solver in Fourier space.

           Example:
             [#1] image.jpg +periodize_poisson array 2,2,2

         rbf:
             dx,_x0,_x1,_phi(r) |
             dx,dy,_x0,_y0,_x1,_y1,_phi(r) |
             dx,dy,dz,x0,y0,z0,x1,y1,z1,phi(r)

           Reconstruct 1D/2D or 3D image from selected sets of keypoints, by
           RBF-interpolation.
           A set of keypoints is represented by a vector-valued image, where
       each
           pixel represents a single keypoint.
           Vector components of a keypoint have the following meaning:
              -  For 1D reconstruction: [ x_k, f1(k),...fN(k) ].
              -  For 2D reconstruction: [ x_k,y_k, f1(k),...,fN(k) ].
              -  For 3D reconstruction: [ x_k,y_k,z_k, f1(k),...,fN(k) ].
           Values 'x_k','y_k' and 'z_k' are the spatial coordinates
           of keypoint 'k'.
           Values 'f1(k),..,fN(k)' are the 'N' components of the vector
           value of keypoint 'k'.
           The command reconstructs an image with specified size
       'dx'x'dy'x'dz',
            with 'N' channels.

           Default values: 'x0=y0=z0=0', 'x1=dx-1', 'y1=dy-1',
             'z1=dz-1', 'phi(r)=r^2*log(1e-5+r)'.

           Example:
             [#1] sample colorful,400 100%,100% noise_poissondisk. 10
       1,{is},1,5
              eval[-2] "begin(p=0);i?(I[#-1,p++]=[x,y,I(#0)])" to_rgb[1]
              mul[0,1] dilate_circ[0] 5 +rbf[-1] {0,[w,h]} c[-1] 0,255
             [#2] 32,1,1,5,u([400,400,255,255,255]) rbf 400,400 c 0,255

         red_eye:
             0<=_threshold<=100,_smoothness>=0,0<=attenuation<=1

           Attenuate red-eye effect in selected images.

           Default values: 'threshold=75', 'smoothness=3.5' and
            'attenuation=0.1'.

           Example:
             [#1] image.jpg +red_eye ,

         remove_hotpixels:
             _mask_size>0, _threshold[%]>0

           Remove hot pixels in selected images.

           Default values: 'mask_size=3' and 'threshold=10%'.

           Example:
             [#1] image.jpg noise 10,2 +remove_hotpixels ,

         remove_pixels:
             number_of_pixels[%]>=0

           Remove specified number of pixels (i.e. set them to 0) from the set
       of
           non-zero pixels in selected images.

           Example:
             [#1] image.jpg +remove_pixels 50%

         rolling_guidance:
             std_deviation_s[%]>=0,std_deviation_r[%]>=0,_precision>=0

           Apply the rolling guidance filter on selected image.
           Rolling guidance filter is a fast image abstraction filter,
       described in:
           "Rolling Guidance Filter", Qi Zhang Xiaoyong, Shen Li, Xu Jiaya
       Jia,
           ECCV'2014.

           Default values: 'std_deviation_s=4',
            'std_deviation_r=10' and 'precision=0.5'.

           Example:
             [#1] image.jpg +rolling_guidance , +-

         sharpen:
             amplitude>=0 |
             amplitude>=0,edge>=0,_alpha[%],_sigma[%]

           Sharpen selected images by inverse diffusion or shock filters
       methods.
           'edge' must be specified to enable shock-filter method.

           Default values: 'edge=0', 'alpha=0' and 'sigma=0'.

           Example:
             [#1] image.jpg sharpen 300
             [#2] image.jpg blur 5 sharpen 300,1

         sharpen_alpha:
             _amplitude[%]>=0,_nb_scales>0,0<=_anisotropy<=1,0<=_minimize_alpha<=1

           Sharpen selected images using a multi-scale and alpha boosting
       algorithm.

           Default values: 'amplitude=1', 'nb_scales=5',
            'anisotropy=0' and 'minimize_alpha=1'.

         smooth (+):
             amplitude[%]>=0,_sharpness>=0,0<=_anisotropy<=1,_alpha[%],_sigma[%],_dl>0,
               _da>0,_precision>0,_interpolation,_fast_approx={ 0 | 1 } |
             nb_iterations>=0,_sharpness>=0,_anisotropy,_alpha,_sigma,_dt>0,0
       |
             [tensor_field],_amplitude>=0,_dl>0,_da>0,_precision>0,_interpolation,
               _fast_approx={ 0 | 1 } |
             [tensor_field],_nb_iters>=0,_dt>0,0

           Smooth selected images anisotropically using diffusion PDE's, with
           specified field of
           diffusion tensors.
           'interpolation' can be { 0:nearest | 1:linear | 2:runge-kutta
           }.

           Default values: 'sharpness=0.7', 'anisotropy=0.3',
            'alpha=0.6', 'sigma=1.1', 'dl=0.8', 'da=30',
            'precision=2', 'interpolation=0' and 'fast_approx=1'.

           Example:
             [#1] image.jpg repeat 3 smooth 40,0,1,1,2 done
             [#2] image.jpg 100%,100%,1,2 rand[-1] -100,100 repeat 2
       smooth[-1] 100,
              0.2,1,4,4 done warp[0] [-1],1,1,1

           Tutorial: https://gmic.eu/oldtutorial/_smooth

         split_freq:
             smoothness>0[%]

           Split selected images into low and high frequency parts.

           Example:
             [#1] image.jpg split_freq 2%

         solve_poisson:
             "laplacian_command",_nb_iterations>=0,_time_step>0,_nb_scales>=0

           Solve Poisson equation so that applying 'laplacian[n]' is close to
           the result of 'laplacian_command[n]'.
           Solving is performed using a multi-scale gradient descent
       algorithm.
           If 'nb_scales=0', the number of scales is automatically determined.

           Default values: 'nb_iterations=60', 'dt=5' and
            'nb_scales=0'.

           Example:
             [#1] image.jpg command "foo : gradient x" +solve_poisson foo
       +foo[0]
              +laplacian[1]

         split_alpha:
             _nb_scales[%]={ 0:auto | -S<0 | N>0 },_subsample={ 0:no | 1:yes
       },
               0<=_anisotropy<=1,0<=_minimize_alpha<=1

           Split selected images into alpha detail scales.
           If 'nb_scales==-S', the lowest scale has a size of at least
           'SxS'.
           Parameter 'anisotropy' is only considered when 'subsample=0'.
           Image reconstruction is done with command merge_alpha.

           Default values: 'nb_scales=0', 'subsample=0',
            'anisotropy=0' and 'minimize_alpha=1'.

         split_details:
             _nb_scales[%]={ 0:auto | -S<0 | N>0
       },_base_scale[%]>=0,_detail_scale[%]>=0

           Split selected images into 'nb_scales' detail scales.
           If 'base_scale' = 'detail_scale' = 0, the image decomposition
           is done with 'a trous' wavelets.
           Otherwise, it uses laplacian pyramids with linear standard
       deviations.

           Default values: 'nb_scales=0', 'base_scale=0' and
            'detail_scale=0'.

           Example:
             [#1] image.jpg split_details ,

         structuretensors:
             _scheme={ 0:centered | 1:forward/backward }

           Compute the structure tensor field of selected images.

           Default value: 'scheme=0'.

           Example:
             [#1] image.jpg structuretensors abs pow 0.2

           Tutorial: https://gmic.eu/oldtutorial/_structuretensors

         solidify:
             _smoothness[%]>=0,_diffusion_type={ 0:isotropic | 1:Delaunay-
       guided |
               2:edge-oriented },_diffusion_iter>=0

           Solidify selected transparent images.

           Default values: 'smoothness=75%', 'diffusion_type=1' and
            'diffusion_iter=20'.

           Example:
             [#1] image.jpg 100%,100% circle[-1] 50%,50%,25%,1,255 append c
              +solidify , display_rgba

         syntexturize:
             _width[%]>0,_height[%]>0

           Resynthetize 'width'x'height' versions of selected micro-textures
       by
           phase randomization.
           The texture synthesis algorithm is a straightforward implementation
       of the
           method described in :
           http://www.ipol.im/pub/art/2011/ggm_rpn/.

           Default values: 'width=height=100%'.

           Example:
             [#1] image.jpg crop 2,282,50,328 +syntexturize 320,320

         syntexturize_matchpatch:
             _width[%]>0,_height[%]>0,_nb_scales>=0,_patch_size>0,_blending_size>=0,
               _precision>=0

           Resynthetize 'width'x'height' versions of selected micro-textures
           using a patch-matching algorithm.
           If 'nbscales==0', the number of scales used is estimated from the
           image size.

           Default values: 'width=height=100%', 'nb_scales=0',
            'patch_size=7', 'blending_size=5' and 'precision=1'.

           Example:
             [#1] image.jpg crop 25%,25%,75%,75% syntexturize_matchpatch
       512,512

         tv_flow:
             _nb_iter>=0,_dt,_keep_sequence={ 0 | 1 }

           Apply iterations of the total variation flow on selected images.

           Default values: 'nb_iter=10', 'dt=30' and
            'keep_sequence=0'.

           Example:
             [#1] image.jpg +tv_flow 40

         unsharp:
             radius[%]>=0,_amount>=0,_threshold[%]>=0

           Apply unsharp mask on selected images.

           Default values: 'amount=2' and 'threshold=0'.

           Example:
             [#1] image.jpg blur 3 +unsharp 1.5,15 cut 0,255

         unsharp_octave:
             _nb_scales>0,_radius[%]>=0,_amount>=0,threshold[%]>=0

           Apply octave sharpening on selected images.

           Default values: 'nb_scales=4', 'radius=1',
            'amount=2' and 'threshold=0'.

           Example:
             [#1] image.jpg blur 3 +unsharp_octave 4,5,15 cut 0,255

         vanvliet (+):
             std_deviation>=0[%],order={ 0 | 1 | 2 | 3 },axis={ x | y | z | c
       },
               _boundary_conditions

           Apply Vanvliet recursive filter on selected images, along specified
       axis
           and with
           specified standard deviation, order and boundary conditions.
           'boundary_conditions' can be { 0:dirichlet | 1:neumann |
           2:periodic | 3:mirror }.

           Default value: 'boundary_conditions=1'.

           Example:
             [#1] image.jpg +vanvliet 3,1,x
             [#2] image.jpg +vanvliet 30,0,x vanvliet[-2] 30,0,y add

         voronoi:

           Compute the discrete Voronoi diagram of non-zero pixels in selected
       images.

           Example:
             [#1] 400,400 noise 0.2,2 eq 1 +label_fg 0 voronoi[-1]
       +gradient[-1] xy,
              1 append[-2,-1] c norm[-1] ==[-1] 0 map[-2] 2,2 mul[-2,-1]
              normalize[-2] 0,255 dilate_circ[-2] 4 reverse max

         watermark_fourier:
             text,_size>0

           Add a textual watermark in the frequency domain of selected images.

           Default value: 'size=33'.

           Example:
             [#1] image.jpg +watermark_fourier "Watermarked!" +display_fft
       remove[-3,
              -1] normalize 0,255 append[-4,-2] y append[-2,-1] y

         watershed (+):
             [priority_image],_is_high_connectivity={ 0 | 1 }

           Compute the watershed transform of selected images.

           Default value: 'is_high_connectivity=1'.

           Example:
             [#1] 400,400 noise 0.2,2 eq 1 +distance 1 mul[-1] -1 label[-2]
              watershed[-2] [-1] mod[-2] 256 map[-2] 0 reverse

         11.9. Features Extraction
               -------------------

         area:
             tolerance>=0,is_high_connectivity={ 0 | 1 }

           Compute area of connected components in selected images.

           Default values: 'is_high_connectivity=0'.

           Example:
             [#1] image.jpg luminance stencil[-1] 1 +area 0

           Tutorial: https://gmic.eu/oldtutorial/_area

         area_fg:
             tolerance>=0,is_high_connectivity={ 0 | 1 }

           Compute area of connected components for non-zero values in
       selected
           images.
           Similar to 'area' except that 0-valued pixels are not considered.

           Default values: 'is_high_connectivity=0'.

           Example:
             [#1] image.jpg luminance stencil[-1] 1 +area_fg 0

         at_line:
             x0[%],y0[%],z0[%],x1[%],y1[%],z1[%]

           Retrieve pixels of the selected images belonging to the specified
       line (x0,
           y0,z0)-(x1,y1,z1).

           Example:
             [#1] image.jpg +at_line 0,0,0,100%,100%,0 line[0]
       0,0,100%,100%,1,
              0xFF00FF00,255,0,0

         at_quadrangle:
             x0[%],y0[%],x1[%],y1[%],x2[%],y2[%],x3[%],y3[%],_interpolation,
               _boundary_conditions |
             x0[%],y0[%],z0[%],x1[%],y1[%],z1[%],x2[%],y2[%],z2[%],x3[%],y3[%],z3[%],
               _interpolation,_boundary_conditions

           Retrieve pixels of the selected images belonging to the specified
       2D or 3D
           quadrangle.
           'interpolation' can be { 0:nearest-neighbor | 1:linear | 2:cubic
           }.
           'boundary_conditions' can be { 0:dirichlet | 1:neumann |
           2:periodic | 3:mirror }.

           Example:
             [#1] image.jpg params=5%,5%,95%,5%,60%,95%,40%,95% +at_quadrangle
              $params polygon.. 4,$params,0.5,255

         barycenter:

           Compute the barycenter vector of pixel values.

           Example:
             [#1] 256,256 ellipse 50%,50%,20%,20%,0,1,1 deform 20 +barycenter
              +ellipse[-2] {@0,1},5,5,0,10

         betti:

           Compute Betti numbers B0,B1 and B2 from selected 3D binary shapes.
           Values B0,B1 and B2 are returned in the status. When multiple
       images are
           selected, the B0,B1,B2 of each image are concatenated in the
       status.
           (see 'https://en.wikipedia.org/wiki/Betti_number' for details about
           Betti numbers).

         canny:
             _sigma[%]>=0,_low_threshold>=0,_high_threshold>=0

           Locate image edges using Canny edge detector.

           Default values: 'sigma=1', 'low_threshold=0.05',
            'high_threshold=0.15'.

           Example:
             [#1] image.jpg canny 1

         delaunay:
             _output_type={ 0:image | 1:coordinates/triangles }

           Generate discrete 2D Delaunay triangulation of non-zero pixels in
       selected
           images.
           Input images must be scalar.
           Each pixel of the output image is a triplet (a,b,c) meaning the
       pixel
           belongs to
           the Delaunay triangle 'ABC' where 'a','b','c' are
           the labels of the pixels 'A','B','C'.

           Example:
             [#1] 400,400 rand 32,255 100%,100% noise. 0.4,2 eq. 1 mul
       +delaunay
             [#2] image.jpg 100%,100% noise. 2,2 eq. 1 delaunay. +blend
       shapeaverage0

         detect_skin:
             0<=tolerance<=1,_skin_x,_skin_y,_skin_radius>=0

           Detect skin in selected color images and output an appartenance
           probability map.
           Detection is performed using CbCr chromaticity data of skin pixels.
           If arguments 'skin_x', 'skin_y' and 'skin_radius' are
           provided, skin pixels are learnt
           from the sample pixels inside the circle located at ('skin_x',
           'skin_y') with radius 'skin_radius'.

           Default value: 'tolerance=0.5' and
            'skin_x=skiny=radius=-1'.

         displacement (+):
             [source_image],_smoothness,_precision>=0,_nb_scales>=0,_iteration_max>=0,
               is_backward={ 0 | 1 },_[guide]

           Estimate displacement field between specified source and selected
       target
           images.
           If 'smoothness>=0', regularization type is set to isotropic, else
       to
           anisotropic.
           If 'nbscales==0', the number of scales used is estimated from the
           image size.

           Default values: 'smoothness=0.1', 'precision=5',
            'nb_scales=0', 'iteration_max=10000',
            'is_backward=1' and '[guide]=(unused)'.

           Example:
             [#1] image.jpg +rotate 3,1,0,50%,50% +displacement[-1] [-2]
       quiver[-1]
              [-1],15,1,1,1,{1.5*iM}

         distance (+):
             isovalue[%],_metric |
             isovalue[%],[metric],_method

           Compute the unsigned distance function to specified isovalue, opt.
           according to a custom metric.
           'metric' can be { 0:chebyshev | 1:manhattan | 2:euclidean |
           3:squared-euclidean }.
           'method' can be { 0:fast-marching | 1:low-connectivity dijkstra |
           2:high-connectivity dijkstra | 3:1+return path | 4:2+return path }.

           Default value: 'metric=2' and 'method=0'.

           Example:
             [#1] image.jpg threshold 20% distance 0 pow 0.3
             [#2] 400,400 set 1,50%,50% +distance[0] 1,2 +distance[0] 1,1
              distance[0] 1,0 mod 32 threshold 16 append c

           Tutorial: https://gmic.eu/oldtutorial/_distance

         fftpolar:

           Compute fourier transform of selected images, as centered
       magnitude/phase
           images.

           Example:
             [#1] image.jpg fftpolar ellipse 50%,50%,10,10,0,1,0 ifftpolar

         histogram (+):
             nb_levels>0[%],_min_value[%],_max_value[%]

           Compute the histogram of selected images.
           If value range is set, the histogram is estimated only for pixels
       in the
           specified
           value range. Argument 'max_value' must be specified if
           'min_value' is set.

           Default values: 'min_value=0%' and 'max_value=100%'.

           Example:
             [#1] image.jpg +histogram 64 display_graph[-1] 400,300,3

         histogram_masked:
             [mask],nb_levels>0[%],_min_value[%],_max_value[%]

           Compute the masked histogram of selected images.

           Default values: 'min_value=0%' and 'max_value=100%'.

         histogram_nd:
             nb_levels>0[%],_value0[%],_value1[%]

           Compute the 1D,2D or 3D histogram of selected multi-channels images
           (having 1,2 or 3 channels).
           If value range is set, the histogram is estimated only for pixels
       in the
           specified
           value range.

           Default values: 'value0=0%' and 'value1=100%'.

           Example:
             [#1] image.jpg channels 0,1 +histogram_nd 256

         histogram_cumul:
             _nb_levels>0,_is_normalized={ 0 | 1 },_val0[%],_val1[%]

           Compute cumulative histogram of selected images.

           Default values: 'nb_levels=256', 'is_normalized=0',
            'val0=0%' and 'val1=100%'.

           Example:
             [#1] image.jpg +histogram_cumul 256 histogram[0] 256
       display_graph 400,
              300,3

         histogram_pointwise:
             nb_levels>0[%],_value0[%],_value1[%]

           Compute the histogram of each vector-valued point of selected
       images.
           If value range is set, the histogram is estimated only for values
       in the
           specified
           value range.

           Default values: 'value0=0%' and 'value1=100%'.

         hough:
             _width>0,_height>0,gradient_norm_voting={ 0 | 1 }

           Compute hough transform (theta,rho) of selected images.

           Default values: 'width=512', 'height=width' and
            'gradient_norm_voting=1'.

           Example:
             [#1] image.jpg +blur 1.5 hough[-1] 400,400 blur[-1] 0.5 add[-1] 1
              log[-1]

         ifftpolar:

           Compute inverse fourier transform of selected images, from centered
           magnitude/phase images.

         img2patches:
             patch_size>0,_overlap[%]>0,_boundary_conditions

           Decompose selected 2D images into (possibly overlapping) patches
       and stack
           them along the z-axis.
           'overlap' must be in range '[0,patch_size-1]'.
           'boundary_conditions' can be { 0:dirichlet | 1:neumann |
           2:periodic | 3:mirror }.

           Default values: 'overlap=0' and 'boundary_conditions=0'.
           See also: patches2img.

           Example:
             [#1] image.jpg img2patches 64

         isophotes:
             _nb_levels>0

           Render isophotes of selected images on a transparent background.

           Default value: 'nb_levels=64'

           Example:
             [#1] image.jpg blur 2 isophotes 6 dilate_circ 5 display_rgba

         label (+):
             _tolerance>=0,is_high_connectivity={ 0 | 1 },_is_L2_norm={ 0 | 1
       }

           Label connected components in selected images.
           If 'is_L2_norm=1', tolerances are compared against L2-norm,
           otherwise L1-norm is used.

           Default values: 'tolerance=0', 'is_high_connectivity=0'
            and 'is_L2_norm=1'.

           Example:
             [#1] image.jpg luminance threshold 60% label normalize 0,255 map
       0
             [#2] 400,400 set 1,50%,50% distance 1 mod 16 threshold 8 label
       mod 255
              map 2

           Tutorial: https://gmic.eu/oldtutorial/_label

         label_fg:
             tolerance>=0,is_high_connectivity={ 0 | 1 },_is_L2_norm={ 0 | 1 }

           Label connected components for non-zero values (foreground) in
       selected
           images.
           Similar to 'label' except that 0-valued pixels are not labeled.
           If 'is_L2_norm=1', tolerances are compared against L2-norm,
           otherwise L1-norm is used.

           Default value: 'is_high_connectivity=0'.

         laar:

           Extract the largest axis-aligned rectangle in non-zero areas of
       selected
           images.
           Rectangle coordinates are returned in status, as a sequence of
       numbers x0,
           y0,x1,y1.

           Example:
             [#1] shape_cupid 256 coords=${-laar} normalize 0,255 to_rgb
       rectangle
              $coords,0.5,0,128,0

         max_patch:
             _patch_size>=1

           Return locations of maximal values in local patch-based
       neighborhood of
           given size for selected images.

           Default value: 'patch_size=16'.

           Example:
             [#1] image.jpg norm +max_patch 16

         min_patch:
             _patch_size>=1

           Return locations of minimal values in local patch-based
       neighborhood of
           given size for selected images.

           Default value: 'patch_size=16'.

           Example:
             [#1] image.jpg norm +min_patch 16

         minimal_path:
             x0[%]>=0,y0[%]>=0,z0[%]>=0,x1[%]>=0,y1[%]>=0,z1[%]>=0,
               _is_high_connectivity={ 0 | 1 }

           Compute minimal path between two points on selected potential maps.

           Default value: 'is_high_connectivity=0'.

           Example:
             [#1] image.jpg +gradient_norm fill[-1] 1/(1+i) minimal_path[-1]
       0,0,0,
              100%,100%,0 pointcloud[-1] 0 *[-1] 280 to_rgb[-1] ri[-1]
              [-2],0 or

         mse:
             [reference]

           Return the MSE (Mean-Squared Error) between selected images and
       specified
           reference image.
           This command does not modify the images. It returns a value or a
       list of
           values in the status.

         mse_matrix:

           Compute MSE (Mean-Squared Error) matrix between selected images.

           Example:
             [#1] image.jpg +noise 30 +noise[0] 35 +noise[0] 38 cut. 0,255
              +mse_matrix

         patches2img:
             width>0,height>0,_overlap[%]>0,_overlap_std[%]

           Recompose 2D images from their selected patch representations.
           'overlap' must be in range '[0,patch_size-1]' where
           'patch_size' is the width/height of the selected image.
           'overlap_std' is the standard deviation of the gaussian weights
       used
           for reconstructing overlapping patches.
           If 'overlap_std' is set to '-1', uniform weights are used
           rather than gaussian.

           Default value: 'overlap=0' and 'overlap_std=-1'.
           See also: img2patches.

           Example:
             [#1] image.jpg +img2patches 32,0,3 mirror[-1] xy patches2img[-1]
       {0,[w,
              h]}

         patches:
             patch_width>0,patch_height>0,patch_depth>0,x0,y0,z0,_x1,_y1,_z1,...,_xN,
               _yN,_zN

           Extract N+1 patches from selected images, centered at specified
       locations.

           Example:
             [#1] image.jpg +patches
       64,64,1,153,124,0,184,240,0,217,126,0,275,38,0

         matchpatch (+):
             [patch_image],patch_width>=1,_patch_height>=1,_patch_depth>=1,
               _nb_iterations>=0,_nb_randoms>=0,_patch_penalization,
               _output_score={ 0 | 1 },_[guide]

           Estimate correspondence map between selected images and specified
       patch
           image, using
           a patch-matching algorithm.
           Each pixel of the returned correspondence map gives the location
       (p,q) of
           the closest patch in
           the specified patch image. If 'output_score=1', the third channel
           also gives the corresponding
           matching score for each patch as well.
           If 'patch_penalization' is >=0, SSD is penalized with patch
           occurrences.
           If 'patch_penalization' is <0, SSD is inf-penalized when distance
           between patches are less than '-patch_penalization'.

           Default values: 'patch_height=patch_width',
            'patch_depth=1', 'nb_iterations=5', 'nb_randoms=5',
            'patch_penalization=0', 'output_score=0' and
            'guide=(undefined)'.

           Example:
             [#1] image.jpg sample colorful +matchpatch[0] [1],3 +warp[-2]
       [-1],0

         plot2value:

           Retrieve values from selected 2D graph plots.

           Example:
             [#1] 400,300,1,1,'y>300*abs(cos(x/10+2*u))' +plot2value
              +display_graph[-1] 400,300

         pointcloud:
             _type = { -X:-X-opacity | 0:binary | 1:cumulative | 2:label |
       3:retrieve
               coordinates },_width,_height>0,_depth>0

           Render a set of point coordinates, as a point cloud in a 1D/2D or
       3D
           binary image
           (or do the reverse, i.e. retrieve coordinates of non-zero points
       from a
           rendered point cloud).
           Input point coordinates can be a NxMx1x1, Nx1x1xM or 1xNx1xM image,
       where
           'N' is the number of points,
           and M the point coordinates.
           If 'M'>3, the 3-to-M components sets the (M-3)-dimensional color at
       each
           point.
           Parameters 'width','height' and 'depth' are related to
           the size of the final image :
              -  If set to 0, the size is automatically set along the
       specified axis.
              -  If set to N>0, the size along the specified axis is N.
              -  If set to N<0, the size along the specified axis is at most
       N.
           Points with coordinates that are negative or higher than specified
           ('width','height','depth')
           are not plotted.

           Default values: 'type=0' and 'max_width=max_height=max_depth
            =0'.

           Example:
             [#1] 3000,2 rand 0,400 +pointcloud 0 dilate[-1] 3
             [#2] 3000,2 rand 0,400 {w} {w},3 rand[-1] 0,255 append y
       +pointcloud 0
              dilate[-1] 3

         psnr:
             [reference],_max_value>0

           Return PSNR (Peak Signal-to-Noise Ratio) between selected images
       and
           specified reference image.
           This command does not modify the images. It returns a value or a
       list of
           values in the status.

           Default value: 'max_value=255'.

         psnr_matrix:
             _max_value>0

           Compute PSNR (Peak Signal-to-Noise Ratio) matrix between selected
       images.

           Default value: 'max_value=255'.

           Example:
             [#1] image.jpg +noise 30 +noise[0] 35 +noise[0] 38 cut. 0,255
              +psnr_matrix

         segment_watershed:
             _threshold>=0

           Apply watershed segmentation on selected images.

           Default values: 'threshold=2'.

           Example:
             [#1] image.jpg segment_watershed 2

         shape2bump:
             _resolution>=0,0<=_weight_std_max_avg<=1,_dilation,_smoothness>=0

           Estimate bumpmap from binary shape in selected images.

           Default value: 'resolution=256', 'weight_std_max=0.75',
            'dilation=0' and 'smoothness=100'.

         skeleton:
             _boundary_conditions={ 0:dirichlet | 1:neumann }

           Compute skeleton of binary shapes using distance transform and
       constrained
           thinning.

           Default value: 'boundary_conditions=1'.

           Example:
             [#1] shape_cupid 320 +skeleton 0

         slic:
             size>0,_regularity>=0,_nb_iterations>0

           Segment selected 2D images with superpixels, using the SLIC
       algorithm
           (Simple Linear Iterative Clustering).
           Scalar images of increasingly labeled pixels are returned.
           Reference paper: Achanta, R., Shaji, A., Smith, K., Lucchi, A.,
       Fua, P., &
           Susstrunk, S. (2010). SLIC Superpixels (No. EPFL-REPORT-149300).

           Default values: 'size=16', 'regularity=10' and
            'nb_iterations=10'.

           Example:
             [#1] image.jpg +srgb2lab slic[-1] 16 +blend shapeaverage f[-2]
       "j(1,
              0)==i && j(0,1)==i" *[-1] [-2]

         ssd_patch:
             [patch],_use_fourier={ 0 | 1 },_boundary_conditions

           Compute fields of SSD between selected images and specified patch.
           Argument 'boundary_conditions' is valid only when
           'use_fourier=0'.
           'boundary_conditions' can be { 0:dirichlet | 1:neumann |
           2:periodic | 3:mirror }.

           Default value: 'use_fourier=0' and
            'boundary_conditions=0'.

           Example:
             [#1] image.jpg +crop 20%,20%,35%,35% +ssd_patch[0] [1],0,0

         ssim:
             [reference],_patch_size>0,_max_value>0

           Compute the Structural Similarity Index Measure (SSIM) between
       selected
           images and specified reference image.
           This command does not modify the images, it just returns a value or
       a list
           of values in the status.
           When 'downsampling_factor' is specified with a ending '%', its
           value is equal to '1+(patch_size-1)*spatial_factor%'.

           SSIM is a measure introduced int the following paper:
           Wang, Zhou, et al., "Image quality assessment: from error
       visibility to
           structural similarity.",
           in IEEE transactions on image processing 13.4 (2004): 600-612.

           The implementation of this command is a direct translation of the
           reference code (in Matlab), found at :
           https://ece.uwaterloo.ca/~z70wang/research/ssim/

           Default values: 'patch_size=11', and 'max_value=255'.

         ssim_matrix:
             _patch_size>0,_max_value>0

           Compute SSIM (Structural Similarity Index Measure) matrix between
       selected
           images.

           Default values: 'patch_size=11', and 'max_value=255'.

           Example:
             [#1] image.jpg +noise 30 +noise[0] 35 +noise[0] 38 cut. 0,255
              +ssim_matrix

         thinning:
             _boundary_conditions={ 0:dirichlet | 1:neumann }

           Compute skeleton of binary shapes using morphological thinning
           (beware, this is a quite slow iterative process)

           Default value: 'boundary_conditions=1'.

           Example:
             [#1] shape_cupid 320 +thinning

         tones:
             N>0

           Get N tones masks from selected images.

           Example:
             [#1] image.jpg +tones 3

         topographic_map:
             _nb_levels>0,_smoothness

           Render selected images as topographic maps.

           Default values: 'nb_levels=16' and 'smoothness=2'.

           Example:
             [#1] image.jpg topographic_map 10

         tsp:
             _precision>=0

           Try to solve the 'travelling salesman' problem, using a combination
       of
           greedy search and 2-opt algorithms.
           Selected images must have dimensions Nx1x1xC to represent N cities
       each
           with C-dimensional coordinates.
           This command re-order the selected data along the x-axis so that
       the point
           sequence becomes a shortest path.

           Default values: 'precision=256'.

           Example:
             [#1] 256,1,1,2 rand 0,512 tsp , 512,512,1,3 repeat w#0 circle[-1]
       {0,
              I[$>]},2,1,255,255,255 line[-1] {0,boundary=2;[I[$>],
              I[$>+1]]},1,255,128,0 done keep[-1]

         variance_patch:
             _patch_size>=1

           Compute variance of each images patch centered at (x,y), in
       selected
           images.

           Default value: 'patch_size=16'

           Example:
             [#1] image.jpg +variance_patch

         11.10. Image Drawing
                -------------

         arrow:
             x0[%],y0[%],x1[%],y1[%],_thickness[%]>=0,_head_length[%]>=0,
               _head_thickness[%]>=0,_opacity,_pattern,_color1,...

           Draw specified arrow on selected images.
           'pattern' is an hexadecimal number starting with '0x' which
           can be omitted
           even if a color is specified. If a pattern is specified, the arrow
       is
           drawn outlined instead of filled.

           Default values: 'thickness=1%', 'head_length=10%',
            'head_thickness=3%', 'opacity=1',
            'pattern=(undefined)' and 'color1=0'.

           Example:
             [#1] 400,400,1,3 repeat 100 arrow
       50%,50%,{u(100)}%,{u(100)}%,3,20,10,
              0.3,${-rgb} done

         axes:
             x0,x1,y0,y1,_font_height>=0,_opacity,_pattern,_color1,...

           Draw xy-axes on selected images.
           'pattern' is an hexadecimal number starting with '0x' which
           can be omitted
           even if a color is specified.
           To draw only one x-axis at row Y, set both 'y0' and 'y1' to Y.
           To draw only one y-axis at column X, set both 'x0' and 'x1' to
           X.

           Default values: 'font_height=14', 'opacity=1',
            'pattern=(undefined)' and 'color1=0'.

           Example:
             [#1] 400,400,1,3,255 axes -1,1,1,-1

         ball:
             _size>0,
       _R,_G,_B,0<=_specular_light<=8,0<=_specular_size<=8,_shadow>=0

           Input a 2D RGBA colored ball sprite.

           Default values: 'size=64', 'R=255', 'G=R',
            'B=R', 'specular_light=0.8', 'specular_size=1' and
            'shading=1.5'.

           Example:
             [#1] repeat 9 { ball {1.5^($>+2)},${-rgb} } append x

         chessboard:
             size1>0,_size2>0,_offset1,_offset2,_angle,_opacity,_color1,...,_color2,...

           Draw chessboard on selected images.

           Default values: 'size2=size1', 'offset1=offset2=0',
            'angle=0', 'opacity=1', 'color1=0' and
            'color2=255'.

           Example:
             [#1] image.jpg chessboard 32,32,0,0,25,0.3,255,128,0,0,128,255

         cie1931:

           Draw CIE-1931 chromaticity diagram on selected images.

           Example:
             [#1] 500,400,1,3 cie1931

         circle:
             x[%],y[%],R[%],_opacity,_pattern,_color1,...

           Draw specified colored circle on selected images.
           A radius of '100%' stands for 'sqrt(width^2+height^2)'.
           'pattern' is an hexadecimal number starting with '0x' which
           can be omitted
           even if a color is specified. If a pattern is specified, the circle
       is
           drawn outlined instead of filled.

           Default values: 'opacity=1', 'pattern=(undefined)' and
            'color1=0'.

           Example:
             [#1] image.jpg repeat 300 circle {u(100)}%,{u(100)}%,{u(30)},0.3,
              ${-rgb} done circle 50%,50%,100,0.7,255

         close_binary:
             0<=_endpoint_rate<=100,_endpoint_connectivity>=0,_spline_distmax>=0,
               _segment_distmax>=0,0<=_spline_anglemax<=180,_spline_roundness>=0,
               _area_min>=0,_allow_self_intersection={ 0 | 1 }

           Automatically close open shapes in binary images (defining white
       strokes
           on black background).

           Default values: 'endpoint_rate=75',
            'endpoint_connectivity=2', 'spline_distmax=80',
            'segment_distmax=20', 'spline_anglemax=90',
            'spline_roundness=1','area_min=100',
            'allow_self_intersection=1'.

         curve:
             [xy_coordinates],_thickness>0,_tilt,_tilt_strength[%],_is_closed={
       0:no |
               1:yes },_opacity,_color1,...

           Draw specified parameterized curve on selected images.
           Arguments are:
            * '[xy_coordinates]' is the set of XY-coordinates of the curve,
           specified as a 2-channels image.
            * 'thickness' is the thickness of the drawing, specified in
       pixels.
            * 'tilt' is an angle, specified in degrees.
            * 'tilt_strength' must be a float value in [0,1] (or in [0,100] if
           specified as a percentage).
            * 'is_closed' is a boolean which tells if the curve is closed or
           not.

           Default values: 'thickness=0', 'tilt=45'

           Example:
             [#1] image.jpg srand 3 16,1,1,4,u s. c,2 rbf[-2,-1] 1000,0,1
       n[-2] 10,
              {w#0-10} n[-1] 10,{h#0-10} a[-2,-1] c curve[-2] [-1],6,0,0,0,
              1,0,128,0

         ellipse (+):
             x[%],y[%],R[%],r[%],_angle,_opacity,_pattern,_color1,...

           Draw specified colored ellipse on selected images.
           A radius of '100%' stands for 'sqrt(width^2+height^2)'.
           'pattern' is an hexadecimal number starting with '0x' which
           can be omitted
           even if a color is specified. If a pattern is specified, the
       ellipse is
           drawn outlined instead of filled.

           Default values: 'opacity=1', 'pattern=(undefined)' and
            'color1=0'.

           Example:
             [#1] image.jpg repeat 300 ellipse
       {u(100)}%,{u(100)}%,{u(30)},{u(30)},
              {u(180)},0.3,${-rgb} done ellipse 50%,50%,100,100,0,0.7,255

         flood (+):
             x[%],_y[%],_z[%],_tolerance>=0,_is_high_connectivity={ 0 | 1
       },_opacity,
               _color1,...

           Flood-fill selected images using specified value and tolerance.

           Default values: 'y=z=0', 'tolerance=0',
            'is_high_connectivity=0', 'opacity=1' and 'color1=0'.

           Example:
             [#1] image.jpg repeat 1000 flood
       {u(100)}%,{u(100)}%,0,20,0,1,${-rgb}
              done

         gaussian:
             _sigma1[%],_sigma2[%],_angle

           Draw a centered gaussian on selected images, with specified
       standard
           deviations and orientation.

           Default values: 'sigma1=3', 'sigma2=sigma1' and
            'angle=0'.

           Example:
             [#1] 400,400 gaussian 100,30,45

           Tutorial: https://gmic.eu/oldtutorial/_gaussian

         graph (+):
             [function_image],_plot_type,_vertex_type,_ymin,_ymax,_opacity,_pattern,
               _color1,... |
             'formula',_resolution>=0,_plot_type,_vertex_type,_xmin,xmax,_ymin,_ymax,
               _opacity,_pattern,_color1,...

           Draw specified function graph on selected images.
           'plot_type' can be { 0:none | 1:lines | 2:splines | 3:bar }.
           'vertex_type' can be { 0:none | 1:points | 2,3:crosses | 4,
           5:circles | 6,7:squares }.
           'pattern' is an hexadecimal number starting with '0x' which
           can be omitted
           even if a color is specified.

           Default values: 'plot_type=1', 'vertex_type=1',
            'ymin=ymax=0 (auto)', 'opacity=1', 'pattern=(undefined)'
           and 'color1=0'.

           Example:
             [#1] image.jpg +rows 50% blur[-1] 3 split[-1] c div[0] 1.5
       graph[0] [1],
              2,0,0,0,1,255,0,0 graph[0] [2],2,0,0,0,1,0,255,0 graph[0]
              [3],2,0,0,0,1,0,0,255 keep[0]

         grid:
             size_x[%]>=0,size_y[%]>=0,_offset_x[%],_offset_y[%],_opacity,_pattern,
               _color1,...

           Draw xy-grid on selected images.
           'pattern' is an hexadecimal number starting with '0x' which
           can be omitted
           even if a color is specified.

           Default values: 'offset_x=offset_y=0', 'opacity=1',
            'pattern=(undefined)' and 'color1=0'.

           Example:
             [#1] image.jpg grid 10%,10%,0,0,0.5,255
             [#2] 400,400,1,3,255 grid 10%,10%,0,0,0.3,0xCCCCCCCC,128,32,16

         j (+):
             Shortcut for command 'image'.

         image (+):
             [sprite],_x[%|~],_y[%|~],_z[%|~],_c[%|~],_opacity,_[opacity_mask],
               _max_opacity_mask

           Draw specified sprite on selected images.
           (equivalent to shortcut command 'j').

           If one of the x,y,z or c argument ends with a '~', its value is
           expected to be
           a centering ratio (in [0,1]) rather than a position.
           Usual centering ratio are { 0:left-justified | 0.5:centered |
           1:right-justified }.

           Default values: 'x=y=z=c=0', 'opacity=1',
            'opacity_mask=(undefined)' and 'max_opacity_mask=1'.

           Example:
             [#1] image.jpg +crop 40%,40%,60%,60% resize[-1] 200%,200%,1,3,5
              frame[-1] 2,2,0 image[0] [-1],30%,30% keep[0]

         ja:
             Shortcut for command 'imagealpha'.

         imagealpha:
             [sprite],_x[%|~],_y[%|~],_z[%|~],_c[%|~],_opacity

           Draw specified sprite on selected images, considering that the
       sprite's
           last channel is the drawing's alpha.
           (equivalent to shortcut command 'ja').

           If one of the x,y,z or c argument ends with a '~', its value is
           expected to be
           a centering ratio (in [0,1]) rather than a position.
           Usual centering ratio are { 0:left-justified | 0.5:centered |
           1:right-justified }.

           Default values: 'x=y=z=c=0' and 'opacity=1'.

         line (+):
             x0[%],y0[%],x1[%],y1[%],_opacity,_pattern,_color1,...

           Draw specified colored line on selected images.
           'pattern' is an hexadecimal number starting with '0x' which
           can be omitted
           even if a color is specified.

           Default values: 'opacity=1', 'pattern=(undefined)' and
            'color1=0'.

           Example:
             [#1] image.jpg repeat 500 line 50%,50%,{u(w)},{u(h)},0.5,${-rgb}
       done
              line 0,0,100%,100%,1,0xCCCCCCCC,255 line 100%,0,0,100%,1,
              0xCCCCCCCC,255

         line_aa:
             x0[%],y0[%],x1[%],y1[%],_opacity,_color1,...

           Draw specified antialiased colored line on selected images.

           Default values: 'opacity=1' and 'color1=0'.

           Example:
             [#1] 512,512,1,3 repeat 100 line_aa {v([w,h,w,h])-1},1,${-RGB}
       done

         spline:
             x0[%],y0[%],u0[%],v0[%],x1[%],y1[%],u1[%],v1[%],_opacity,_color1,...

           Draw specified colored spline curve on selected images (cubic
       hermite
           spline).

           Default values: 'opacity=1' and 'color1=0'.

           Example:
             [#1] image.jpg repeat 30 { spline
       {u(100)}%,{u(100)}%,{u(-600,600)},
              {u(-600,600)},{u(100)}%,{u(100)}%,{u(-600,600)},{u(-600,
              600)},1,${-RGB} }

         thickline:
             x0[%],y0[%],x1[%],y1[%],_thickness,_opacity,_color1

           Draw specified colored thick line on selected images.

           Default values: 'thickness=2', 'opacity=1' and
            'color1=0'.

           Example:
             [#1] 400,400,1,3 repeat 100 thickline
       {u([w,h,w,h,5])},0.5,${-rgb} done

         thickspline:
             x0[%],y0[%],u0[%],v0[%],x1[%],y1[%],u1[%],v1[%],_thickness,_opacity,
               _color1,...

           Draw specified colored thick spline curve on selected images (cubic
           hermite spline).

           Default values: 'thickness=3', 'opacity=1' and
            'color1=0'.

           Example:
             [#1] image.jpg repeat 30 { thickspline
       {u(100)}%,{u(100)}%,{u(-600,
              600)},{u(-600,600)},{u(100)}%,{u(100)}%,{u(-600,600)},
              {u(-600,600)},3,1,${-RGB} }

         mandelbrot (+):
             z0r,z0i,z1r,z1i,_iteration_max>=0,_is_julia={ 0 | 1
       },_c0r,_c0i,_opacity

           Draw mandelbrot/julia fractal on selected images.

           Default values: 'iteration_max=100', 'is_julia=0',
            'c0r=c0i=0' and 'opacity=1'.

           Example:
             [#1] 400,400 mandelbrot -2.5,-2,2,2,1024 map 0 +blur 2
       elevation3d[-1]
              -0.2

         marble:
             _image_weight,_pattern_weight,_angle,_amplitude,_sharpness>=0,
               _anisotropy>=0,_alpha,_sigma,_cut_low>=0,_cut_high>=0

           Render marble like pattern on selected images.

           Default values: 'image_weight=0.2', 'pattern_weight=0.1',
             'angle=45', 'amplitude=0', 'sharpness=0.4' and
            'anisotropy=0.8',
           'alpha=0.6', 'sigma=1.1' and 'cut_low=cut_high=0'.

           Example:
             [#1] image.jpg +marble ,

         maze:
             _width>0,_height>0,_cell_size>0

           Input maze with specified size.

           Example:
             [#1] maze 30,20 negate normalize 0,255

         maze_mask:
             _cellsize>0

           Input maze according to size and shape of selected mask images.
           Mask may contain disconnected shapes.

           Example:
             [#1] 0 text "G'MIC",0,0,53,1,1 dilate 3 autocrop 0 frame 1,1,0
              maze_mask 8 dilate 3 negate mul 255

         newton_fractal:
             z0r,z0i,z1r,z1i,_angle,0<=_descent_method<=2,_iteration_max>=0,
               _convergence_precision>0,_expr_p(z),_expr_dp(z),_expr_d2p(z)

           Draw newton fractal on selected images, for complex numbers in
       range (z0r,
           z0i) - (z1r,z1i).
           Resulting images have 3 channels whose meaning is [ last_zr,
       last_zi,
           nb_iter_used_for_convergence ].
           'descent_method' can be { 0:secant | 1:newton | 2:householder
           }.

           Default values: 'angle=0', 'descent_method=1',
            'iteration_max=200', 'convergence_precision=0.01',
            'expr_p(z)=z^^3-1', 'expr_dp(z)=3*z^^2' and
            'expr_d2z(z)=6*z'.

           Example:
             [#1] 400,400 newton_fractal -1.5,-1.5,1.5,1.5,0,2,200,0.01,"z^^6
       + z^^3
              - 1","6*z^^5 + 3*z^^2","30*z^^4 + 6*z" f "[ atan2(i1,
              i0)*90+20,1,cut(i2/30,0.2,0.7) ]" hsl2rgb

         j3d (+):
             Shortcut for command 'object3d'.

         object3d (+):
             [object3d],_x[%],_y[%],_z,_opacity,_rendering_mode,_is_double_sided={
       0 |
               1 },_is_zbuffer={ 0 | 1 },_focale,_light_x,_light_y,_light_z,
               _specular_lightness,_specular_shininess

           Draw specified 3D object on selected images.
           (equivalent to shortcut command 'j3d').

           'rendering_mode' can be { 0:dots | 1:wireframe | 2:flat |
           3:flat-shaded | 4:gouraud-shaded | 5:phong-shaded }.

           Default values: 'x=y=z=0', 'opacity=1' and
            'is_zbuffer=1'. All other arguments take their default values
           from the 3D environment variables.

           Example:
             [#1] image.jpg torus3d 100,10 cone3d 30,-120 add3d[-2,-1]
       rotate3d. 1,1,
              0,60 object3d[0] [-1],50%,50% keep[0]

         pack_sprites:
             _nb_scales>=0,0<=_min_scale<=100,_allow_rotation={ 0:0 deg. |
       1:180 deg. |
               2:90 deg. | 3:any },_spacing,_precision>=0,max_iterations>=0

           Try to randomly pack as many sprites as possible onto the 'empty'
           areas of an image.
           Sprites can be eventually rotated and scaled during the packing
       process.
           First selected image is the canvas that will be filled with the
       sprites.
           Its last channel must be a binary mask whose zero values represent
           potential locations for drawing the sprites.
           All other selected images represent the sprites considered for
       packing.
           Their last channel must be a binary mask that represents the sprite
       shape
           (i.e. a 8-connected component).
           The order of sprite packing follows the order of specified sprites
       in the
           image list.
           Sprite packing is done on random locations and iteratively with
       decreasing
           scales.
           'nb_scales' sets the number of decreasing scales considered for all
           specified sprites to be packed.
           'min_scale' (in %) sets the minimal size considered for packing
           (specified as a percentage of the
           original sprite size).
           'spacing' can be positive or negative.
           'precision' tells about the desired number of failed trials before
           ending the filling process.

           Default values: 'nb_scales=5', 'min_scale=25',
            'allow_rotation=3', 'spacing=1', 'precision=7' and
            'max_iterations=256'.

           Example:
             [#1] 512,512,1,3,"min(255,y*c/2)" 100%,100% circle
       50%,50%,100,1,255
              append c image.jpg rescale2d[-1] ,24 to_rgba pack_sprites 3,
              25

         piechart:
             label_height>=0,label_R,label_G,label_B,"label1",value1,R1,G1,B1,...,
               "labelN",valueN,RN,GN,BN

           Draw pie chart on selected (RGB) images.

           Example:
             [#1] image.jpg piechart
       25,0,0,0,"Red",55,255,0,0,"Green",40,0,255,0,
              "Blue",30,128,128,255,"Other",5,128,128,128

         plasma (+):
             _alpha,_beta,_scale>=0

           Draw a random colored plasma fractal on selected images.
           This command implements the so-called 'Diamond-Square' algorithm.

           Default values: 'alpha=1', 'beta=1' and 'scale=8'.

           Example:
             [#1] 400,400,1,3 plasma

           Tutorial: https://gmic.eu/oldtutorial/_plasma

         point (+):
             x[%],_y[%],_z[%],_opacity,_color1,...

           Set specified colored pixel on selected images.

           Default values: 'z=0', 'opacity=1' and 'color1=0'.

           Example:
             [#1] image.jpg repeat 10000 point {u(100)}%,{u(100)}%,0,1,${-rgb}
       done

         polka_dots:
             diameter>=0,_density,_offset1,_offset2,_angle,_aliasing,_shading,_opacity,
               _color,...

           Draw dots pattern on selected images.

           Default values: 'density=20', 'offset1=offset2=50',
            'angle=0', 'aliasing=10', 'shading=1',
            'opacity=1' and 'color=255'.

           Example:
             [#1] image.jpg polka_dots 10,15,0,0,20,10,1,0.5,0,128,255

         polygon (+):
             N>=1,x1[%],y1[%],...,xN[%],yN[%],_opacity,_pattern,_color1,...

           Draw specified colored N-vertices polygon on selected images.
           'pattern' is an hexadecimal number starting with '0x' which
           can be omitted
           even if a color is specified. If a pattern is specified, the
       polygon is
           drawn outlined instead of filled.

           Default values: 'opacity=1', 'pattern=(undefined)' and
            'color1=0'.

           Example:
             [#1] image.jpg polygon
       4,20%,20%,80%,30%,80%,70%,20%,80%,0.3,0,255,0
              polygon 4,20%,20%,80%,30%,80%,70%,20%,80%,1,0xCCCCCCCC,255
             [#2] image.jpg 2,16,1,1,'u(x?{h}:{w})' polygon[-2]
       {h},{^},0.6,255,0,
              255 remove[-1]

         quiver:
             [function_image],_sampling[%]>0,_factor>=0,_is_arrow={ 0 | 1
       },_opacity,
               _color1,...

           Draw specified 2D vector/orientation field on selected images.

           Default values: 'sampling=5%', 'factor=1',
            'is_arrow=1', 'opacity=1', 'pattern=(undefined)'
           and 'color1=0'.

           Example:
             [#1] 100,100,1,2,'!c?x-w/2:y-h/2' 500,500,1,3,255 quiver[-1]
       [-2],10
             [#2] image.jpg +rescale2d ,600 luminance[0] gradient[0] mul[1] -1
              reverse[0,1] append[0,1] c blur[0] 8 orientation[0]
              quiver[1] [0],20,1,1,0.8,255

         rectangle:
             x0[%],y0[%],x1[%],y1[%],_opacity,_pattern,_color1,...

           Draw specified colored rectangle on selected images.
           'pattern' is an hexadecimal number starting with '0x' which
           can be omitted
           even if a color is specified. If a pattern is specified, the
       rectangle is
           drawn outlined instead of filled.

           Default values: 'opacity=1', 'pattern=(undefined)' and
            'color1=0'.

           Example:
             [#1] image.jpg repeat 30 { rectangle
       {u(100)}%,{u(100)}%,{u(100)}%,
              {u(100)}%,0.3,${-rgb} }

         rorschach:
             'smoothness[%]>=0','mirroring={ 0:none | 1:x | 2:y | 3:xy }

           Render rorschach-like inkblots on selected images.

           Default values: 'smoothness=5%' and 'mirroring=1'.

           Example:
             [#1] 400,400 rorschach 3%

         sierpinski:
             recursion_level>=0

           Draw Sierpinski triangle on selected images.

           Default value: 'recursion_level=7'.

           Example:
             [#1] image.jpg sierpinski 7

         spiralbw:
             width>0,_height>0,_is_2dcoords={ 0 | 1 }

           Input a 2D rectangular spiral image with specified size.

           Default values: 'height=width' and 'is_2dcoords=0'.

           Example:
             [#1] spiralbw 16
             [#2] image.jpg spiralbw {[w,h]},1 +warp[0] [1],0,1,1 +warp[2]
       [1],2,1,1

         tetraedron_shade:
             x0,y0,z0,x1,y1,z1,x2,y2,z2,x3,y3,z3,R0,G0,B0,...,R1,G1,B1,...,R2,G2,B2,...,
               R3,G3,B3,...

           Draw tetraedron with interpolated colors on selected (volumetric)
       images.

         t (+):
             Shortcut for command 'text'.

         text (+):
             text,_x[%|~],_y[%|~],_{ font_height[%]>=0 | custom_font
       },_opacity,_color1,
               ...

           Draw specified colored text string on selected images.
           (equivalent to shortcut command 't').

           If one of the x or y argument ends with a '~', its value is
       expected
           to be a centering ratio (in [0,1]) rather than a position.
           Usual centering ratio are { 0:left-justified | 0.5:centered |
           1:right-justified }.
           Sizes '13' and '128' are special and correspond to binary
           fonts (no-antialiasing). Any other font size is rendered with anti-
       aliasing.
           Specifying an empty target image resizes it to new dimensions such
       that
           the image contains the entire text string.
           A custom font can be specified as a variable name that stores an
       image
           list of 256 or 512 items (512 for 256 character sprites + 256
       associated
           opacities), or as an image selection that is a serialized version
       of such
           an image list.

           Default values: 'x=y=0.01~', 'font_height=16',
            'opacity=1' and 'color1=0'.

           Example:
             [#1] image.jpg rescale2d ,600 div 2 y=0 repeat 30 { text {2*$>}"
       : This
              is a nice text!",10,$y,{2*$>},0.9,255 y+={2*$>} }
             [#2] 0 text "G'MIC",0,0,23,1,255

         to:
             Shortcut for command 'text_outline'.

         text_outline:
             text,_x[%|~],_y[%|~],{ _font_height[%]>0 | custom_font
       },_outline>=0,
               _opacity,_color1,...

           Draw specified colored and outlined text string on selected images.
           If one of the x or y argument ends with a '~', its value is
       expected
           to be
           a centering ratio (in [0,1]) rather than a position.
           Usual centering ratio are { 0:left-justified | 0.5:centered |
           1:right-justified }.

           Default values: 'x=y=0.01~', 'font_height=7.5%',
            'outline=2', 'opacity=1', 'color1=color2=color3=255'
            and 'color4=255'.

           Example:
             [#1] image.jpg text_outline "Hi there!",10,10,63,3

         triangle_shade:
             x0,y0,x1,y1,x2,y2,R0,G0,B0,...,R1,G1,B1,...,R2,G2,B2,...

           Draw triangle with interpolated colors on selected images.

           Example:
             [#1] image.jpg triangle_shade
       20,20,400,100,120,200,255,0,0,0,255,0,0,0,
              255

         truchet:
             _scale>0,_radius>=0,_pattern_type={ 0:straight | 1:curved }

           Fill selected images with random truchet patterns.

           Default values: 'scale=32', 'radius=5' and
            'pattern_type=1'.

           Example:
             [#1] 400,300 truchet ,

         turbulence:
             _radius>0,_octaves={1,2,3...,12},_alpha>0,_difference={-10,10},_mode={0,1,
               2,3}

           Render fractal noise or turbulence on selected images.

           Default values: 'radius=32', 'octaves=6',
            'alpha=3', 'difference=0' and 'mode=0'.

           Example:
             [#1] 400,400,1,3 turbulence 16

           Tutorial: https://gmic.eu/oldtutorial/_turbulence

         yinyang:

           Draw a yin-yang symbol on selected images.

           Example:
             [#1] 400,400 yinyang

         11.11. Matrix Computation
                ------------------

         dijkstra:
             starting_vertex>=0,_ending_vertex={ -1:none | >=0 }

           Compute minimal distances/paths in selected graphs, from specified
           'starting_vertex' to all other vertices (opt. only until
           'ending_vertex' has been reached).
           A graph of 'N' vertices is specified as a 'NxN' adjacency
           matrix giving the weights of all edges connecting vertices (set to
           'inf' when two vertices are not connected).
           This command return a '1xNx1x2' image containing the '[distance,
           parent]' information :
              -  'distance' is the minimal distance from vertex '#y' to
           the 'starting_vertex' (i.e. the sum of edge weights composing the
           minimal path between these two vertices).
              -  'parent' is the index of the next vertex that must be
       followed
           to reaches the 'starting_vertex' through the minimal path.

           Default value: 'ending_vertex=-1'

         eigen (+):

           Compute the eigenvalues and eigenvectors of selected symmetric
       matrices or
           matrix fields.
           If one selected image has 3 or 6 channels, it is regarded as a
       field of
           2x2 or 3x3 symmetric matrices,
           whose eigen elements are computed at each point of the field.

           Example:
             [#1] (1,0,0;0,2,0;0,0,3) +eigen
             [#2] image.jpg structuretensors blur 2 eigen split[0] c

           Tutorial: https://gmic.eu/oldtutorial/_eigen

         eye:
             _size>0

           Insert an identity matrix of given size at the end of the image
       list.

           Example:
             [#1] eye 3 eye 7 eye 10

         fitsamples:
             nb_samples>0,_relevant_dimension[%]>0,_average_vector_varname,
               _dilation_vector_varname,_orientation_matrix_varname

           Generate 'nb_samples' vectors having the same multivariate gaussian
           distribution as the vectors of the selected images.
           Each input represents a set of 'M' vectors of dimension 'N'
           (with M>1) (specified as an image with size 'MxNx1x1',
           'Mx1xNx1', 'Mx1x1xN', '1xMxNx1', '1xMx1xN' or
           '1x1xMxN').
           The command returns a new set of random vectors with similar
       geometry.

           Default values: 'relevant_dimension=100%', and
            'average_vector_varname=orientation_matrix_varname=dilation_matrix_v
            arname=(undefined)'.

         invert (+):
             _use_LU={ 0:SVD | 1:LU },_lambda>=0

           Inverse selected matrices (or compute Moore-Penrose pseudoinverse
       for
           non-square matrices).
           SVD solver is slower but more precise than LU.
           'lambda' is used only in the Moore-Penrose pseudoinverse, by
           estimating A^t.(A^t.A + lambda.Id)^-1.

           Default value: 'use_LU=0' and 'lambda=0'.

           Example:
             [#1] (0,1,0;0,0,1;1,0,0) +invert

         meigen:
             m>=1

           Compute an approximation of the 'm' largest eigenvalues and
           eigenvectors of selected symmetric matrices,
           using the Arnoldi iteration method
       (https://en.wikipedia.org/wiki/Arnoldi_i
           teration).
           A larger 'm' goes with better numerical precision.

           Example:
             [#1] (1,0,0;0,2,0;0,0,3) +meigen 3

         mproj (+):
             [dictionary],_method,_max_iter={ 0:auto | >0 },_max_residual>=0

           Find best matching projection of selected matrices onto the span of
       an
           over-complete
           dictionary D, using the orthogonal projection or Matching Pursuit
           algorithm.
           Selected images are 2D-matrices in which each column represent a
       signal to
           project.
           '[dictionary]' is a matrix in which each column is an element of
       the
           dictionary D.
           'method' tells what projection algorithm must be applied. It can
       be:
              - 0 = orthogonal projection (least-squares solution using LU-
       based
           solver).
              - 1 = matching pursuit.
              - 2 = matching pursuit, with a single orthogonal projection step
       at
           the end.
              - >=3 = orthogonal matching pursuit where an orthogonal
       projection
           step is performed
                      every 'method-2' iterations.
           'max_iter' sets the max number of iterations processed for each
           signal.
           If set to '0' (default), 'max_iter' is equal to the number of
           columns in D.
           (only meaningful for matching pursuit and its variants).
           'max_residual' gives a stopping criterion on signal reconstruction
           accuracy.
           (only meaningful for matching pursuit and its variants).
           For each selected image, the result is returned as a matrix W
           whose columns correspond to the weights associated to each column
       of D,
           such that the matrix product D*W is an approximation of the input
       matrix.

           Default values: 'method=0', 'max_iter=0' and
            'max_residual=1e-6'.

         orthogonalize:
             _mode = { 0:orthogonalize | 1:orthonormalize }

           Orthogonalize or orthonormalize selected matrices, using Modified
           Gram-Schmidt process.

           Default value: 'mode=0'.

         poweriteration:
             _nb_eigenvectors>0,_epsilon>0,_max_iter>0

           Compute the 'nb_eigenvectors' largest eigenvectors of the selected
           symmetric matrices,
           using the power iteration algorithm.

           Default values: 'nb_eigenvectors=1', 'epsilon=1e-5' and
            'max_iter=100'.

         solve (+):
             [image],_use_LU={ 0:SVD | 1:LU }

           Solve linear system AX = B for selected B-matrices and specified A-
       matrix.
           If the system is under- or over-determined, the least squares
       solution is
           returned.

           Default value: 'use_LU=0'.

           Example:
             [#1] (0,1,0;1,0,0;0,0,1) (1;2;3) +solve[-1] [-2]

         svd (+):

           Compute SVD decomposition of selected matrices.

           Example:
             [#1] 10,10,1,1,'x==y?x+u(-0.2,0.2):0' +svd

         transpose:

           Transpose selected matrices.

           Example:
             [#1] image.jpg +transpose

         trisolve (+):
             [image]

           Solve tridiagonal system AX = B for selected B-vectors and
       specified
           tridiagonal A-matrix.
           Tridiagonal matrix must be stored as a 3 column vector, where 2nd
       column
           contains the
           diagonal coefficients, while 1st and 3rd columns contain the left
       and
           right coefficients.

           Example:
             [#1] (0,0,1;1,0,0;0,1,0) (1;2;3) +trisolve[-1] [-2]

         11.12. 3D Meshes
                ---------

         +3d (+):
             Shortcut for command 'add3d'.

         add3d (+):
             tx,_ty,_tz |
             [object3d] |
             (no arg)

           Shift selected 3D objects with specified displacement vector, or
       merge
           them with specified
           3D object, or merge all selected 3D objects together.
           (equivalent to shortcut command '+3d').

           Default values: 'ty=tz=0'.

           Example:
             [#1] sphere3d 10 repeat 5 { +add3d[-1] 10,{u(-10,10)},0
       color3d[-1]
              ${-rgb} } add3d
             [#2] repeat 20 { torus3d 15,2 color3d[-1] ${-rgb} mul3d[-1] 0.5,1
       if
              $>%2 rotate3d[-1] 0,1,0,90 fi add3d[-1] 70 add3d
              rotate3d[-1] 0,0,1,18 } double3d 0

         animate3d:
             nb_frames>0,_step_angle_x,_step_angle_y,_step_angle_z,_zoom_factor,
               0<=_fake_shadow_level<=100,_[background]

           Generate 3D animation frames of rotating 3D objects.
           Frames are stacked along the z-axis (volumetric image).
           Frame size is the same as the size of the '[background]' image (or
           800x800 if no background specified).

           Default values: 'step_angle_x=0', 'step_angle_y=5',
            'step_angle_z=0', 'zoom_factor=1',
            'fake_shadow_level=50' and 'background=(undefined)'.

         apply_camera3d:
             pos_x,pos_y,pos_z,target_x,target_y,target_z,up_x,up_y,up_z

           Apply 3D camera matrix to selected 3D objects.

           Default values: 'target_x=0', 'target_y=0',
            'target_z=0', 'up_x=0', 'up_y=-1' and 'up_z=0'.

         apply_matrix3d:
             a11,a12,a13,...,a31,a32,a33

           Apply specified 3D rotation matrix to selected 3D objects.

           Example:
             [#1] torus3d 10,1 +apply_matrix3d
       {mul(rot(1,0,1,-15<degree>),[1,0,0,0,2,0,0,
              0,8],3)} double3d 0

         array3d:
             size_x>=1,_size_y>=1,_size_z>=1,_offset_x[%],_offset_y[%],_offset_y[%]

           Duplicate a 3D object along the X,Y and Z axes.

           Default values: 'size_y=1', 'size_z=1' and
            'offset_x=offset_y=offset_z=100%'.

           Example:
             [#1] torus3d 10,1 +array3d 5,5,5,110%,110%,300%

         arrow3d:
             x0,y0,z0,x1,y1,z1,_radius[%]>=0,_head_length[%]>=0,_head_radius[%]>=0

           Input 3D arrow with specified starting and ending 3D points.

           Default values: 'radius=5%', 'head_length=25%' and
            'head_radius=15%'.

           Example:
             [#1] repeat 10 { a:=$>*2*pi/10 arrow3d
       0,0,0,{cos($a)},{sin($a)},-0.5 }
              +3d

         axes3d:
             _size_x,_size_y,_size_z,_font_size>0,_label_x,_label_y,_label_z,
               _is_origin={ 0:no | 1:yes }

           Input 3D axes with specified sizes along the x,y and z
       orientations.

           Default values: 'size_x=size_y=size_z=1', 'font_size=23',
             'label_x=X', 'label_y=Y', 'label_z=Z' and
            'is_origin=1'

           Example:
             [#1] axes3d ,

         boundingbox3d:

           Replace selected 3D objects by their 3D bounding boxes.

           Example:
             [#1] torus3d 100,30 +boundingbox3d +3d[-1] [-2]

         box3d:
             _size_x,_size_y,_size_z

           Input 3D box at (0,0,0), with specified geometry.

           Default values: 'size_x=1' and 'size_z=size_y=size_x'.

           Example:
             [#1] box3d 100,40,30 +primitives3d 1 color3d[-2] ${-rgb}

         c3d:
             Shortcut for command 'center3d'.

         center3d:

           Center selected 3D objects at (0,0,0).
           (equivalent to shortcut command 'c3d').

           Example:
             [#1] repeat 100 { circle3d {u(100)},{u(100)},{u(100)},2 } add3d
              color3d[-1] 255,0,0 +center3d color3d[-1] 0,255,0 add3d

         chainring3d:
             _nb_links>=3,_x_scale>0,_y_scale>0,_z_scale>0

           Input 3D chain ring with specified geometry.
           'nb_links' should be preferably even.

           Default values: 'nb_links=16', 'x_scale=0.5',
            'y_scale=1' and 'z_scale=1'.

           Example:
             [#1] chainring3d

         circle3d:
             _x0,_y0,_z0,_radius>=0

           Input 3D circle at specified coordinates.

           Default values: 'x0=y0=z0=0' and 'radius=1'.

           Example:
             [#1] repeat 500 { a:=$>*pi/250 circle3d
       {cos(3*$a)},{sin(2*$a)},0,
              {$a/50} color3d[-1] ${-rgb},0.4 } add3d

         circles3d:
             _radius>=0,_is_outlined={ 0 | 1 }

           Convert specified 3D objects to sets of 3D circles with specified
       radius.

           Default values: 'radius=1' and 'is_outlined=1'.

           Example:
             [#1] image.jpg luminance rescale2d ,40 threshold 50% * 255
       pointcloud3d
              color3d[-1] 255,255,255 circles3d 0.7

         col3d:
             Shortcut for command 'color3d'.

         color3d:
             R,_G,_B,_opacity

           Set color (and optionally opacity) of selected 3D objects.
           (equivalent to shortcut command 'col3d').

           Default value: 'B=G=R' and 'opacity=(undefined)'.

           Example:
             [#1] torus3d 100,10 double3d 0 repeat 7 { +rotate3d[-1] 1,0,0,20
              color3d[-1] ${-rgb} } add3d

         colorcube3d:
             _is_wireframe={ 0 | 1 }

           Input 3D color cube.

           Default value: 'is_wireframe=0'.

           Example:
             [#1] colorcube3d mode3d 2 +primitives3d 1

         colorize3d:
             _color_function,_passed_images_for_color_function

           Colorize primitives of selected 3D objects, according to a
       specified
           function.
            * 'color_function' returns a G,GA,RGB or RGBA vector that can
           depend on variables 'x','y' and 'z', which are defined as
           the barycenter coordinates for each primitive.
            * 'passed_images_for_color_function' can be specified as a
           selection (e.g. '[0,2]') of images that will be inserted at the end
           of the image list while modifying 3D objects, so that the
           'color_function' can have access to their content.

           Default values: 'color_function=[x,y,z]' and
            'passed_images_for_color_function='.

           Example:
             [#1] torus3d 100,40,640,100 c3d n3d mul3d 256 +3d 128,128,128
       sample
              colorful,257 colorize3d[0] "I(#-1,x,y,0)",[1]

         cone3d:
             _radius,_height,_nb_subdivisions>0

           Input 3D cone at (0,0,0), with specified geometry.

           Default value: 'radius=1','height=1' and
            'nb_subdivisions=24'.

           Example:
             [#1] cone3d 10,40 +primitives3d 1 color3d[-2] ${-rgb}

         cubes3d:
             _size>=0

           Convert specified 3D objects to sets of 3D cubes with specified
       size.

           Default value: 'size=1'.

           Example:
             [#1] image.jpg luminance rescale2d ,40 threshold 50% * 255
       pointcloud3d
              color3d[-1] 255,255,255 cubes3d 1

         cup3d:
             _resolution>0

           Input 3D cup object.

           Default value: 'resolution=128'.

           Example:
             [#1] cup3d ,

         curve3d:
             _"x(t)",_"y(t)",_"z(t)",_"r(t)",_resolution>1,_tmin,_tmax,_nb_sides>=0,
               _is_closed_curve={ 0 | 1 }

           Input 3D curve with specified parameterization.
           If 'r(t)==0' or 'nb_sides<3', the generated 3D object is
           composed of segments only.

           Default values: 'x(t)=cos(2*pi*t)', 'y(t)=sin(2*pi*t)',
            'z(t)=t', 'r(t)=0.025', 'resolution=128',
            'tmin=0', 'tmax=1', 'nb_sides=16' and
            'is_closed_curve=0'.

           Example:
             [#1] curve3d ,

         cylinder3d:
             _radius,_height,_nb_subdivisions>0

           Input 3D cylinder at (0,0,0), with specified geometry.

           Default value: 'radius=1','height=1' and
            'nb_subdivisions=24'.

           Example:
             [#1] cylinder3d 10,40 +primitives3d 1 color3d[-2] ${-rgb}

         delaunay3d:

           Generate 3D Delaunay triangulations from selected images.
           One assumes that the selected input images are binary images
       containing
           the set of points to mesh.
           The output 3D object is a mesh composed of non-oriented triangles.

           Example:
             [#1] 500,500 noise 0.05,2 eq 1 * 255 +delaunay3d color3d[1]
       255,128,0
              dilate_circ[0] 5 to_rgb[0] +object3d[0] [1],0,0,0,1,1
              max[-1] [0]

         distribution3d:

           Get 3D color distribution of selected images.

           Example:
             [#1] image.jpg distribution3d colorcube3d primitives3d[-1] 1
       add3d

         /3d (+):
             Shortcut for command 'div3d'.

         div3d (+):
             factor |
             factor_x,factor_y,_factor_z

           Scale selected 3D objects isotropically or anisotropically, with
       the
           inverse of specified
           factors.
           (equivalent to shortcut command '/3d').

           Default value: 'factor_z=1'.

           Example:
             [#1] torus3d 5,2 repeat 5 { +add3d[-1] 12,0,0 div3d[-1] 1.2
       color3d[-1]
              ${-rgb} } add3d

         db3d:
             Shortcut for command 'double3d'.

         double3d:
             _is_double_sided={ 0 | 1 }

           Enable/disable double-sided mode for 3D rendering.
           (equivalent to shortcut command 'db3d').

           Default value: 'is_double_sided=1'.

           Example:
             [#1] mode3d 1 repeat 2 { torus3d 100,30 rotate3d[-1] 1,1,0,60
       double3d
              $> snapshot3d[-1] 400 }

         elevation3d:
             { z-factor | [elevation_map] | 'formula' },base_height={ -1 | >=0
       } |
             (no arg)

           Generate 3D elevation of selected images, opt. with a specified
       elevation
           map.
           When invoked with (no arg) or 'z-factor', the elevation map is
           computed as the pointwise L2 norm of the
           pixel values. Otherwise, the elevation map is taken from the
       specified
           image or formula.

           Example:
             [#1] image.jpg +blur 5 elevation3d. 0.75
             [#2] 128,128,1,3,u(255) plasma 10,3 blur 4 sharpen 10000 n 0,255
              elevation3d[-1] 'X=(x-64)/6;Y=(y-64)/6;-100*exp(-(X^2+Y^2)/30
              )*abs(cos(X)*sin(Y))'

         empty3d:

           Input empty 3D object.

           Example:
             [#1] empty3d

         extract_textures3d:

           Extract texture data from selected 3D objects.

           Example:
             [#1] image.jpg imagesphere3d 10,10 +extract_textures3d

         extrude3d:
             _depth>0,_resolution>0,_smoothness[%]>=0

           Generate extruded 3D object from selected binary XY-profiles.

           Default values: 'depth=16', 'resolution=1024' and
            'smoothness=0.5%'.

           Example:
             [#1] image.jpg threshold 50% extrude3d 16

         f3d:
             Shortcut for command 'focale3d'.

         focale3d:
             focale

           Set 3D focale.
           (equivalent to shortcut command 'f3d').

           Set 'focale' to 0 to enable parallel projection (instead of
           perspective).
           Set negative 'focale' will disable 3D sprite zooming.

           Default value: 'focale=700'.

           Example:
             [#1] repeat 5 { torus3d 100,30 rotate3d[-1] 1,1,0,60 focale3d
       {$<*90}
              snapshot3d[-1] 400 } remove[0]

         fov3d:
             fov_angle>=0,_image_resolution>0

           Set 3D focale to match specified field of vision angle (in degree)
       for
           rendering a 3D object in an image with specified resolution.
           Return corresponding value of the focale in status.

           Default value: 'fov_angle=45' and 'image_size=max(w,h)'
            (max size of the latest image).

         gaussians3d:
             _size>0,_opacity

           Convert selected 3D objects into set of 3D gaussian-shaped sprites.

           Example:
             [#1] image.jpg rescale2d ,32 distribution3d gaussians3d 20
       colorcube3d
              primitives3d[-1] 1 +3d

         gmic3d:

           Input a 3D G'MIC logo.

           Example:
             [#1] gmic3d +primitives3d 1

         gyroid3d:
             _resolution>0,_zoom

           Input 3D gyroid at (0,0,0), with specified resolution.

           Default values: 'resolution=32' and 'zoom=5'.

           Example:
             [#1] gyroid3d 48 +primitives3d 1

         histogram3d:

           Get 3D color histogram of selected images.

           Example:
             [#1] image.jpg rescale2d 64 histogram3d circles3d 3 opacity3d.
       0.75
              colorcube3d primitives3d[-1] 1 add3d

         image6cube3d:

           Generate 3D mapped cubes from 6-sets of selected images.

           Example:
             [#1] image.jpg animate flower,"30,0","30,5",6 image6cube3d

         imageblocks3d:
             _maximum_elevation,_smoothness[%]>=0

           Generate 3D blocks from selected images.
           Transparency of selected images is taken into account.

           Default values: 'maximum_elevation=10' and
            'smoothness=0'.

           Example:
             [#1] image.jpg rescale2d ,32 imageblocks3d -20 mode3d 3

         imagecube3d:

           Generate 3D mapped cubes from selected images.

           Example:
             [#1] image.jpg imagecube3d

         imageplane3d:

           Generate 3D mapped planes from selected images.

           Example:
             [#1] image.jpg imageplane3d

         imagepyramid3d:

           Generate 3D mapped pyramids from selected images.

           Example:
             [#1] image.jpg imagepyramid3d

         imagerubik3d:
             _xy_tiles>=1,0<=xy_shift<=100,0<=z_shift<=100

           Generate 3D mapped rubik's cubes from selected images.

           Default values: 'xy_tiles=3', 'xy_shift=5' and
            'z_shift=5'.

           Example:
             [#1] image.jpg imagerubik3d ,

         imagesphere3d:
             _resolution1>=3,_resolution2>=3

           Generate 3D mapped sphere from selected images.

           Default values: 'resolution1=32' and 'resolutions2=16'.

           Example:
             [#1] image.jpg imagesphere3d 32,16

         isoline3d (+):
             isovalue[%] |
             'formula',value,_x0,_y0,_x1,_y1,_size_x>0[%],_size_y>0[%]

           Extract 3D isolines with specified value from selected images or
       from
           specified formula.

           Default values: 'x0=y0=-3', 'x1=y1=3' and
            'size_x=size_y=256'.

           Example:
             [#1] image.jpg blur 1 isoline3d 50%
             [#2] isoline3d 'X=x-w/2;Y=y-h/2;(X^2+Y^2)%20',10,-10,-10,10,10

         isosurface3d (+):
             isovalue[%] |
             'formula',value,_x0,_y0,_z0,_x1,_y1,_z1,_size_x>0[%],_size_y>0[%],
               _size_z>0[%]

           Extract 3D isosurfaces with specified value from selected images or
       from
           specified formula.

           Default values: 'x0=y0=z0=-3', 'x1=y1=z1=3' and
            'size_x=size_y=size_z=32'.

           Example:
             [#1] image.jpg rescale2d ,128 luminance threshold 50% expand_z
       2,0 blur
              1 isosurface3d 50% mul3d 1,1,30
             [#2] isosurface3d 'x^2+y^2+abs(z)^abs(4*cos(x*y*z*3))',3

         label3d:
             "text",font_height>=0,_opacity,_color1,...

           Generate 3D text label.

           Default values: 'font_height=13', 'opacity=1' and
            'color=255,255,255'.

         label_points3d:
             _label_size>0,_opacity

           Add a numbered label to all vertices of selected 3D objects.

           Default values: 'label_size=13' and 'opacity=0.8'.

           Example:
             [#1] torus3d 100,40,6,6 label_points3d 23,1 mode3d 1

         lathe3d:
             _resolution>0,_smoothness[%]>=0,_max_angle>=0

           Generate 3D object from selected binary XY-profiles.

           Default values: 'resolution=128', 'smoothness=0.5%' and
            'max_angle=361'.

           Example:
             [#1] 300,300 rand -1,1 blur 40 sign normalize 0,255 lathe3d ,

         l3d (+):
             Shortcut for command 'light3d'.

         light3d (+):
             position_x,position_y,position_z |
             [texture] |
             (no arg)

           Set the light coordinates or the light texture for 3D rendering.
           (equivalent to shortcut command 'l3d').

           (no arg) resets the 3D light to default.

           Example:
             [#1] torus3d 100,30 double3d 0 specs3d 1.2 repeat 5 { light3d
       {$>*100},
              0,-300 +snapshot3d[0] 400 } remove[0]

         line3d:
             x0,y0,z0,x1,y1,z1

           Input 3D line at specified coordinates.

           Example:
             [#1] repeat 100 { a:=$>*pi/50 line3d
       0,0,0,{cos(3*$a)},{sin(2*$a)},0
              color3d. ${-rgb} } add3d

         lines3d:
             _length>=0

           Convert specified 3D objects to sets of 3D horizontal segments with
           specified length.

           Default values: 'length=1'.

           Example:
             [#1] torus3d 100,40 +lines3d 20

         lissajous3d:
             resolution>1,a,A,b,B,c,C

           Input 3D lissajous curves 'x(t)=sin(a*t+A*2*pi)',
           'y(t)=sin(b*t+B*2*pi)', 'z(t)=sin(c*t+C*2*pi)'.

           Default values: 'resolution=1024', 'a=2', 'A=0',
            'b=1', 'B=0', 'c=0' and 'C=0'.

           Example:
             [#1] lissajous3d ,

         m3d:
             Shortcut for command 'mode3d'.

         mode3d:
             _mode

           Set static 3D rendering mode.
           (equivalent to shortcut command 'm3d').

           'mode' can be { -1:bounding-box | 0:dots | 1:wireframe | 2:flat |
           3:flat-shaded | 4:gouraud-shaded | 5:phong-shaded }.
           Bounding-box mode ('mode==-1') is active only for the interactive
       3D
           viewer.

           Default value: 'mode=4'.

           Example:
             [#1] (0,1,2,3,4,5) double3d 0 repeat w { torus3d 100,30
       rotate3d[-1] 1,
              1,0,60 mode3d {0,@$>} snapshot3d[-1] 300 } remove[0]

         md3d:
             Shortcut for command 'moded3d'.

         moded3d:
             _mode

           Set dynamic 3D rendering mode for interactive 3D viewer.
           (equivalent to shortcut command 'md3d').

           'mode' can be { -1:bounding-box | 0:dots | 1:wireframe | 2:flat |
           3:flat-shaded | 4:gouraud-shaded | 5:phong-shaded }.

           Default value: 'mode=-1'.

         *3d (+):
             Shortcut for command 'mul3d'.

         mul3d (+):
             factor |
             factor_x,factor_y,_factor_z

           Scale selected 3D objects isotropically or anisotropically, with
       specified
           factors.
           (equivalent to shortcut command '*3d').

           Default value: 'factor_z=1'.

           Example:
             [#1] torus3d 5,2 repeat 5 { +add3d[-1] 10,0,0 mul3d[-1] 1.2
       color3d[-1]
              ${-rgb} } add3d

         n3d:
             Shortcut for command 'normalize3d'.

         normalize3d:

           Normalize selected 3D objects to unit size.
           (equivalent to shortcut command 'n3d').

           Example:
             [#1] repeat 100 { circle3d {u(3)},{u(3)},{u(3)},0.1 } add3d
       color3d[-1]
              255,0,0 +normalize3d[-1] color3d[-1] 0,255,0 add3d

         o3d:
             Shortcut for command 'opacity3d'.

         opacity3d:
             opacity

           Set opacity of selected 3D objects.
           (equivalent to shortcut command 'o3d').

           Example:
             [#1] torus3d 100,10 double3d 0 repeat 7 { +rotate3d[-1] 1,0,0,20
              opacity3d[-1] {u} } add3d

         parametric3d:
             _x(a,b),_y(a,b),_z(a,b),_amin,_amax,_bmin,_bmax,_res_a>0,_res_b>0,_res_x>0,
               _res_y>0,_res_z>0,_smoothness>=0,_isovalue>=0

           Input 3D object from specified parametric surface '(a,b) <?>
       (x(a,b),y(a,
           b),z(a,b))'.

           Default values: 'x=(2+cos(b))*sin(a)',
            'y=(2+cos(b))*cos(a)', 'c=sin(b)', 'amin=-pi',
            'amax=pi', 'bmin=-pi', 'bmax=pi', 'res_a=512',
            'res_b=res_a', 'res_x=64', 'res_y=res_x',
            'res_z=res_y', 'smoothness=2%' and 'isovalue=10%'.

           Example:
             [#1] parametric3d ,

         pca_patch3d:
             _patch_size>0,_M>0,_N>0,_normalize_input={ 0 | 1
       },_normalize_output={ 0 |
               1 },_lambda_xy

           Get 3D patch-pca representation of selected images.
           The 3D patch-pca is estimated from M patches on the input image,
       and
           displayed as a cloud of N 3D points.

           Default values: 'patch_size=7', 'M=1000', 'N=3000',
             'normalize_input=1', 'normalize_output=0', and
            'lambda_xy=0'.

           Example:
             [#1] image.jpg pca_patch3d 7

         plane3d:
             _size_x,_size_y,_nb_subdivisions_x>0,_nb_subdisivions_y>0

           Input 3D plane at (0,0,0), with specified geometry.

           Default values: 'size_x=1', 'size_y=size_x' and
            'nb_subdivisions_x=nb_subdivisions_y=24'.

           Example:
             [#1] plane3d 50,30 +primitives3d 1 color3d[-2] ${-rgb}

         point3d:
             x0,y0,z0

           Input 3D point at specified coordinates.

           Example:
             [#1] repeat 1000 { a:=$>*pi/500 point3d {cos(3*$a)},{sin(2*$a)},0
              color3d[-1] ${-rgb} } add3d

         pointcloud3d:

           Convert selected planar or volumetric images to 3D point clouds.

           Example:
             [#1] image.jpg luminance rescale2d ,100 threshold 50% mul 255
              pointcloud3d color3d[-1] 255,255,255

         pose3d:
             p1,...,p12

           Apply 3D pose matrix to selected 3D objects.

           Example:
             [#1] torus3d 100,20 pose3d
       0.152437,1.20666,-0.546366,0,-0.535962,
              0.559129,1.08531,0,1.21132,0.0955431,0.548966,0,0,0,-206,1
              snapshot3d 400

         p3d:
             Shortcut for command 'primitives3d'.

         primitives3d:
             mode

           Convert primitives of selected 3D objects.
           (equivalent to shortcut command 'p3d').

           'mode' can be { 0:points | 1:outlines | 2:non-textured }.

           Example:
             [#1] sphere3d 30 primitives3d 1 torus3d 50,10 color3d[-1] ${-rgb}
       add3d

         projections3d:
             _x[%],_y[%],_z[%],_is_bounding_box={ 0 | 1 },nb_subdivisions>0

           Generate 3D xy,xz,yz projection planes from specified volumetric
       images.

           Default values: 'x=y=z=50%', 'is_bounding_box=1' and
            'nb_subdividions=5'

         pyramid3d:
             width,height

           Input 3D pyramid at (0,0,0), with specified geometry.

           Example:
             [#1] pyramid3d 100,-100 +primitives3d 1 color3d[-2] ${-rgb}

         quadrangle3d:
             x0,y0,z0,x1,y1,z1,x2,y2,z2,x3,y3,z3

           Input 3D quadrangle at specified coordinates.

           Example:
             [#1] quadrangle3d -10,-10,10,10,-10,10,10,10,10,-10,10,10 repeat
       10 {
              +rotate3d[-1] 0,1,0,30 color3d[-1] ${-rgb},0.6 } add3d
              mode3d 2

         random3d:
             nb_points>=0

           Input random 3D point cloud in [0,1]^3.

           Example:
             [#1] random3d 100 circles3d 0.1 opacity3d 0.5

         rv3d:
             Shortcut for command 'reverse3d'.

         reverse3d:

           Reverse primitive orientations of selected 3D objects.
           (equivalent to shortcut command 'rv3d').

           Example:
             [#1] torus3d 100,40 double3d 0 +reverse3d

         r3d (+):
             Shortcut for command 'rotate3d'.

         rotate3d (+):
             u,v,w,angle

           Rotate selected 3D objects around specified axis with specified
       angle (in
           deg.).
           (equivalent to shortcut command 'r3d').

           Example:
             [#1] torus3d 100,10 double3d 0 repeat 7 { +rotate3d[-1] 1,0,0,20
       } add3d

         rotation3d:
             u,v,w,angle

           Input 3x3 rotation matrix with specified axis and angle (in deg).

           Example:
             [#1] rotation3d 1,0,0,0 rotation3d 1,0,0,90 rotation3d 1,0,0,180

         sierpinski3d:
             _recursion_level>=0,_width,_height

           Input 3D Sierpinski pyramid.

           Example:
             [#1] sierpinski3d 3,100,-100 +primitives3d 1 color3d[-2] ${-rgb}

         size3d:

           Return bounding box size of the last selected 3D object.

         skeleton3d:
             _metric,_frame_type={ 0:squares | 1:diamonds | 2:circles | 3:auto
       },
               _skeleton_opacity,_frame_opacity,_is_frame_wireframe={ 0 | 1 }

           Build 3D skeletal structure object from 2d binary shapes located in
           selected images.
           'metric' can be { 0:chebyshev | 1:manhattan | 2:euclidean }.

           Default values: 'metric=2', 'bones_type=3',
            'skeleton_opacity=1' and 'frame_opacity=0.1'.

           Example:
             [#1] shape_cupid 480 +skeleton3d ,

         snapshot3d:
             _size>0,_zoom>=0,_backgroundR,_backgroundG,_backgroundB,_backgroundA,
               _fov_angle>=0 |
             [background_image],zoom>=0,_fov_angle>=0

           Take 2D snapshots of selected 3D objects.
           Set 'zoom' to 0 to disable object auto-scaling.

           Default values: 'size=1024', 'zoom=1',
            '[background_image]=(default)' and 'fov_angle=45'.

           Example:
             [#1] torus3d 100,20 rotate3d 1,1,0,60 snapshot3d
       400,1.2,128,64,32
             [#2] torus3d 100,20 rotate3d 1,1,0,60 sample ? +snapshot3d[0]
       [1],1.2

         sl3d:
             Shortcut for command 'specl3d'.

         specl3d:
             value>=0

           Set lightness of 3D specular light.
           (equivalent to shortcut command 'sl3d').

           Default value: 'value=0.15'.

           Example:
             [#1] (0,0.3,0.6,0.9,1.2) repeat w { torus3d 100,30 rotate3d[-1]
       1,1,0,
              60 color3d[-1] 255,0,0 specl3d {0,@$>} snapshot3d[-1] 400 }
              remove[0]

         ss3d:
             Shortcut for command 'specs3d'.

         specs3d:
             value>=0

           Set shininess of 3D specular light.
           (equivalent to shortcut command 'ss3d').

           Default value: 'value=0.8'.

           Example:
             [#1] (0,0.3,0.6,0.9,1.2) repeat w { torus3d 100,30 rotate3d[-1]
       1,1,0,
              60 color3d[-1] 255,0,0 specs3d {0,@$>} snapshot3d[-1] 400 }
              remove[0]

         sphere3d:
             radius,_nb_recursions!=0 |
             radius,_nb_phi>=3,_nb_theta>=3

           Input 3D sphere at (0,0,0), with specified geometry.
            * If 2 arguments are specified:
              -  If 'nb_recursions>0', the sphere is generated using recursive
           subdivisions of an icosahedron.
              -  If 'nb_recursions<0', the sphere is generated using recursive
           subdividions of a cube.
            * If 3 arguments are specified, the sphere is generated using
       spherical
           coordinates discretization.

           Default value: 'nb_recursions=3'.

           Example:
             [#1] sphere3d 100 +primitives3d 1 color3d[-2] ${-rgb}

         spherical3d:
             "radius_function(phi,theta)",_nb_recursions!=0 |
             "radius_function(phi,theta)",_nb_phi>=3,_nb_theta>=3

           Input 3D spherical object at (0,0,0), with specified geometry.
           Second and third arguments are the same as in command sphere3d.

           Default values: 'nb_recursions=5'.

           Example:
             [#1] spherical3d "abs(1+0.5*cos(3*phi)*sin(4*theta))"
       +primitives3d 1

         spline3d:
             x0[%],y0[%],z0[%],u0[%],v0[%],w0[%],x1[%],y1[%],z1[%],u1[%],v1[%],w1[%],
               _nb_vertices>=2

           Input 3D spline with specified geometry.

           Default values: 'nb_vertices=128'.

           Example:
             [#1] repeat 100 { spline3d
       {u},{u},{u},{u},{u},{u},{u},{u},{u},{u},{u},
              {u},128 color3d[-1] ${-rgb} } box3d 1 primitives3d[-1] 1
              add3d

         s3d:
             Shortcut for command 'split3d'.

         split3d:

           Split selected 3D objects into feature vectors :
           { header, sizes, vertices, primitives, colors, opacities }.
           (equivalent to shortcut command 's3d').

           To recreate the 3D object, append all produced images along the y-
       axis
           (with command 'append y').

           Example:
             [#1] box3d 100 +split3d

         sprite3d:

           Convert selected images as 3D sprites.
           Selected images with alpha channels are managed.

           Example:
             [#1] image.jpg sprite3d

         sprites3d:
             [sprite],_sprite_has_alpha_channel={ 0 | 1 }

           Convert selected 3D objects as a sprite cloud.
           Set 'sprite_has_alpha_channel' to 1 to make the last channel of the
           selected sprite be a transparency mask.

           Default value: 'mask_has_alpha_channel=0'.

           Example:
             [#1] torus3d 100,20 image.jpg rescale2d[-1] ,64 100%,100%
       gaussian[-1]
              30%,30% *[-1] 255 append[-2,-1] c +sprites3d[0] [1],1
              display_rgba[-2]

         star3d:
             _nb_branches>0,0<=_thickness<=1

           Input 3D star at position '(0,0,0)', with specified geometry.

           Default values: 'nb_branches=5' and 'thickness=0.38'.

           Example:
             [#1] star3d , +primitives3d 1 color3d[-2] ${-rgb}

         streamline3d (+):
             x[%],y[%],z[%],_L>=0,_dl>0,_interpolation,_is_backward={ 0 | 1 },
               _is_oriented={ 0 | 1 } |
             'formula',x,y,z,_L>=0,_dl>0,_interpolation,_is_backward={ 0 | 1
       },
               _is_oriented={ 0 | 1 }

           Extract 3D streamlines from selected vector fields or from
       specified
           formula.
           'interpolation' can be { 0:nearest integer | 1:1st-order |
           2:2nd-order | 3:4th-order }.

           Default values: 'dl=0.1', 'interpolation=2',
            'is_backward=0' and 'is_oriented=0'.

           Example:
             [#1] 100,100,100,3 rand -10,10 blur 3 repeat 300 {
       +streamline3d[0]
              {u(100)},{u(100)},{u(100)},1000,1,1 color3d[-1] ${-rgb} }
              remove[0] box3d 100 primitives3d[-1] 1 add3d

         -3d (+):
             Shortcut for command 'sub3d'.

         sub3d (+):
             tx,_ty,_tz

           Shift selected 3D objects with the opposite of specified
       displacement
           vector.
           (equivalent to shortcut command '3d').

           Default values: 'ty=tz=0'.

           Example:
             [#1] sphere3d 10 repeat 5 { +sub3d[-1] 10,{u(-10,10)},0
       color3d[-1]
              ${-rgb} } add3d

         subdivide3d:

           Subdivide primitives of selected 3D objects.

         superformula3d:
             resolution>1,m>=1,n1,n2,n3

           Input 2D superformula curve as a 3D object.

           Default values: 'resolution=1024', 'm=8', 'n1=1',
            'n2=5' and 'n3=8'.

           Example:
             [#1] superformula3d ,

         surfels3d:
             0<=_left_right_attenuation<=1,0<=_top_bottom_attenuation<=1,
               0<=_closer_further_attenuation<=1

           Convert selected images to 3D objects composed of 3D surfels (or 2D
       edgels
           for 2D images).
           The binary shape is composed of all non-zero voxels.
           The resulting 3D object is colored according to the color of non
       zero
           voxels.

           Default values: 'left_right_attenuation=1',
            'top_bottom_attenuation=1' and 'closer_further_attenuation=1
            R'.

           Example:
             [#1] 100,100,100 = 1,40%,40%,40% = 1,60%,60%,60% distance 1 lt
       30% blur
              3 gt 50% surfels3d 0.5,0.75,1

         tensors3d:
             _radius_factor>=0,_shape={ 0:box | >=N:ellipsoid },_radius_min>=0

           Generate 3D tensor fields from selected images.
           when 'shape'>0, it gives the ellipsoid shape precision.

           Default values: 'radius_factor=1', 'shape=2' and
            'radius_min=0.05'.

           Example:
             [#1] 6,6,6,9,"U = [x,y,z] - [w,h,d]/2; U/=norm(U); mul(U,U,3) +
              0.3*eye(3)" tensors3d 0.8

         text_pointcloud3d:
             _"text1",_"text2",_smoothness

           Input 3D text pointcloud from the two specified strings.

           Default values: 'text1="text1"', 'text2="text2"' and
            'smoothness=1'.

           Example:
             [#1] text_pointcloud3d "G'MIC","Rocks!"

         text3d:
             text,_{ font_height>=0 | custom_font },_depth>0,_smoothness

           Input a 3D text object from specified text.

           Default values: 'font_height=53', 'depth=10' and
            'smoothness=1.5'.

           Example:
             [#1] text3d "G'MIC as a0D logo!"

         t3d:
             Shortcut for command 'texturize3d'.

         texturize3d:
             [ind_texture],_[ind_coords]

           Texturize selected 3D objects with specified texture and
       coordinates.
           (equivalent to shortcut command 't3d').

           When '[ind_coords]' is omitted, default XY texture projection is
           performed.

           Default value: 'ind_coords=(undefined)'.

           Example:
             [#1] image.jpg torus3d 100,30 texturize3d[-1] [-2] keep[-1]

         torus3d:
             _radius1,_radius2,_nb_subdivisions1>2,_nb_subdivisions2>2

           Input 3D torus at (0,0,0), with specified geometry.

           Default values: 'radius1=1', 'radius2=0.3',
            'nb_subdivisions1=24' and 'nb_subdivisions2=12'.

           Example:
             [#1] torus3d 10,3 +primitives3d 1 color3d[-2] ${-rgb}

         triangle3d:
             x0,y0,z0,x1,y1,z1,x2,y2,z2

           Input 3D triangle at specified coordinates.

           Example:
             [#1] repeat 100 { a:=$>*pi/50 triangle3d 0,0,0,0,0,3,{cos(3*$a)},
              {sin(2*$a)},0 color3d[-1] ${-rgb} } add3d

         volume3d:

           Transform selected 3D volumetric images as 3D parallelepipedic
       objects.

           Example:
             [#1] image.jpg animate blur,0,5,30 append z volume3d

         voxelize3d:
             _max_resolution>0,_fill_interior={ 0 | 1 },_preserve_colors={ 0 |
       1 }

           Convert selected 3D objects as 3D volumetric images of binary
       voxels,
           using 3D mesh rasterization.

           Default values: 'max_resolution=128', 'fill_interior=1'
            and 'preserve_colors=0'.

         weird3d:
             _resolution>0

           Input 3D weird object at (0,0,0), with specified resolution.

           Default value: 'resolution=32'.

           Example:
             [#1] weird3d 48 +primitives3d 1 color3d[-2] ${-rgb}

         11.13. Flow Control
                ------------

         ap:
             Shortcut for command 'apply_parallel'.

         apply_parallel:
             "command"

           Apply specified command on each of the selected images, by
       parallelizing
           it for all image of the list.
           (equivalent to shortcut command 'ap').

           Example:
             [#1] image.jpg +mirror x +mirror y apply_parallel "blur 3"

         apc:
             Shortcut for command 'apply_parallel_channels'.

         apply_parallel_channels:
             "command"

           Apply specified command on each of the selected images, by
       parallelizing
           it for all channel
           of the images independently.
           (equivalent to shortcut command 'apc').

           Example:
             [#1] image.jpg apply_parallel_channels "blur 3"

         apo:
             Shortcut for command 'apply_parallel_overlap'.

         apply_parallel_overlap:
             "command",overlap[%],nb_threads={ 0:auto | 1 | 2 | 4 | 8 | 16 }

           Apply specified command on each of the selected images, by
       parallelizing
           it on 'nb_threads'
           overlapped sub-images.
           (equivalent to shortcut command 'apo').

           'nb_threads' must be a power of 2.

           Default values: 'overlap=0','nb_threads=0'.

           Example:
             [#1] image.jpg +apply_parallel_overlap "smooth 500,0,1",1

         at:
             Shortcut for command 'apply_tiles'.

         apply_tiles:
             "command",_tile_width[%]>0,_tile_height[%]>0,_tile_depth[%]>0,
               _overlap_width[%]>=0,_overlap_height[%]>=0,_overlap_depth[%]>=0,
               _boundary_conditions={ 0:dirichlet | 1:neumann | 2:periodic |
               3:mirror }

           Apply specified command on each tile (neighborhood) of the selected
       images,
            eventually with overlapping tiles.
           (equivalent to shortcut command 'at').

           Default values: 'tile_width=tile_height=tile_depth=10%',
            'overlap_width=overlap_height=overlap_depth=0' and
            'boundary_conditions=1'.

           Example:
             [#1] image.jpg +equalize[0] 256 +apply_tiles[0] "equalize
       256",16,16,1,
              50%,50%

         apply_timeout:
             "command",_timeout={ 0:no timeout | >0:with specified timeout (in
       seconds)
               }

           Apply a command with a timeout.
           Set variable '$_is_timeout' to '1' if timeout occurred,
           '0' otherwise.

           Default value: 'timeout=20'.

         check (+):
             condition

           Evaluate specified condition and display an error message if
       evaluated to
           false.

         check3d (+):
             _is_full_check={ 0 | 1 }

           Check validity of selected 3D vector objects, and display an error
       message
           if one of the selected images is not a valid 3D vector object.
           Full 3D object check is slower but more precise.

           Default value: 'is_full_check=1'.

         continue (+):

           Go to end of current 'do...while', 'for...done',
           'foreach...done', 'local...done' or 'repeat...done' block.

           Example:
             [#1] image.jpg repeat 10 blur 1 if 1==1 continue fi deform 10
       done

         break (+):

           Break current 'do...while', 'for...done',
           'foreach...done', 'local...done' or 'repeat...done' block.

           Example:
             [#1] image.jpg repeat 10 blur 1 if 1==1 break fi deform 10 done

         do (+):

           Start a 'do...while' block.

           Example:
             [#1] image.jpg luminance i:=ia+2 do set 255,{u(100)}%,{u(100)}%
       while
              ia<$i

         done (+):

           End a 'for/foreach/local/repeat...done' block, and go to associated
           'for/foreach/repeat' if iterations remain.
           (equivalent to shortcut command '}').

         elif (+):
             condition

           Start a 'elif...[else]...fi' block if previous 'if' was not
           verified
           and test if specified condition holds
           'condition' is a mathematical expression, whose evaluation is
           interpreted as { 0:false | other:true }..

           Tutorial: https://gmic.eu/tutorial/iffi

         else (+):

           Execute following commands if previous 'if' or 'elif'
           conditions failed.

           Tutorial: https://gmic.eu/tutorial/iffi

         fi (+):

           End a 'if...[elif]...[else]...fi' block.
           (equivalent to shortcut command 'fi').

           Tutorial: https://gmic.eu/tutorial/iffi

         error (+):
             message

           Print specified error message on the standard error (stderr) and
       exit
           interpreter, except
           if error is caught by a 'onfail' command.
           Command selection (if any) stands for displayed call stack subset
       instead
           of image indices.

         eval (+):
             expression

           Evaluate specified math expression.
            * If no command selection is specified, the expression is
       evaluated once
           and its result is set to status.
            * If command selection is specified, the evaluation is looped over
           selected images. Status is unchanged. In this case, 'eval' is
       similar
           to fill without assigning the image values.

         x (+):
             Shortcut for command 'exec'.

         exec (+):
             _is_verbose={ 0 | 1 },"command"

           Execute external command using a system call.
           The status value is then set to the error code returned by the
       system call.
           If 'is_verbose=1', the executed command is allowed to output on
           stdout/stderr.
           (equivalent to shortcut command 'x').

           Default value: 'is_verbose=1'.

         xo:
             Shortcut for command 'exec_out'.

         exec_out:
             _mode,"command"

           Execute external command using a system call, and return resulting
           'stdout' and/or 'stderr'.
           'mode' can be { 0:stdout | 1:stderr | 2:stdout+stderr }.

         for (+):
             condition

           Start a 'for...done' block.

           Example:
             [#1] image.jpg rescale2d ,32 400,400,1,3 x=0 for $x<400 image[1]
       [0],$x,
              $x x+=40 done

         foreach (+):

           Start a 'foreach...done' block, that iterates over all images in
       the
           selection, with a separate local environment for each one.

           Example:
             [#1] sample colorful,earth,duck,dog foreach[^2] +blur 10 sub
       normalize
              0,255 done

         if (+):
             condition

           Start a 'if...[elif]...[else]...fi' block and test if specified
           condition holds.
           'condition' is a mathematical expression, whose evaluation is
           interpreted as { 0:false | other:true }.

           Example:
             [#1] image.jpg if ia<64 add 50% elif ia<128 add 25% elif ia<192
       sub 25%
              else sub 50% fi cut 0,255

           Tutorial: https://gmic.eu/tutorial/iffi

         l (+):
             Shortcut for command 'local'.

         local (+):

           Start a 'local...[onfail]...done' block, with selected images.
           (equivalent to shortcut command 'l').

           Example:
             [#1] image.jpg local[] 300,300,1,3 rand[0] 0,255 blur 4 sharpen
       1000
              done
             [#2] image.jpg +local repeat 3 { deform 20 } done

           Tutorial: https://gmic.eu/oldtutorial/_local

         mutex (+):
             index,_action={ 0:unlock | 1:lock }

           Lock or unlock specified mutex for multi-threaded programming.
           A locked mutex can be unlocked only by the same thread. All mutexes
       are
           unlocked by default.
           'index' designates the mutex index, in [0,255].

           Default value: 'action=1'.

         noarg (+):

           Used in a custom command, 'noarg' tells the command that its
           argument list have not been used
           finally, and so they must be evaluated next in the G'MIC pipeline,
       just as
           if the custom
           command takes no arguments at all.
           Use this command to write a custom command which can decide if it
       takes
           arguments or not.

         onfail (+):

           Execute following commands when an error is encountered in the body
       of the
           'local...done' block.
           The status value is set with the corresponding error message.

           Example:
             [#1] image.jpg +local blur -3 onfail mirror x done

         parallel (+):
             _wait_threads,"command1","command2",...

           Execute specified commands in parallel, each in a different thread.
           Parallel threads share the list of images.
           'wait_threads' can be { 0:when current environment ends |
           1:immediately }.

           Default value: 'wait_threads=1'.

           Example:
             [#1] image.jpg [0] parallel "blur[0] 3","mirror[1] c"

         progress (+):
             0<=value<=100 |
             -1

           Set the progress index of the current processing pipeline.
           This command is useful only when G'MIC is used by an embedding
       application.

         q (+):
             Shortcut for command 'quit'.

         quit (+):

           Quit G'MIC interpreter.
           (equivalent to shortcut command 'q').

         repeat (+):
             nb_iterations

           Start 'nb_iterations' iterations of a 'repeat...done' block.
           'nb_iterations' is a mathematical expression that will be
       evaluated.

           Example:
             [#1] image.jpg split y repeat $! n=$> shift[$n] $<,0,0,0,2 done
       append y
             [#2] image.jpg mode3d 2 repeat 4 imagecube3d rotate3d 1,1,0,40
              snapshot3d 400,1.4 done

           Tutorial: https://gmic.eu/oldtutorial/_repeat

         return (+):

           Return from current custom command.

         rprogress:
             0<=value<=100 | -1 |
       "command",0<=value_min<=100,0<=value_max<=100

           Set the progress index of the current processing pipeline
       (relatively to
           previously defined progress bounds), or call the specified command
       with
           specified progress bounds.

         run:
             "G'MIC pipeline"

           Run specified G'MIC pipeline.

         skip (+):
             item

           Do nothing but skip specified item.

         u (+):
             Shortcut for command 'status'.

         status (+):
             status_string

           Set the current status. Used to define a returning value from a
       function.
           (equivalent to shortcut command 'u').

           Example:
             [#1] image.jpg command "foo : u0=Dark u1=Bright status
       ${u{ia>=128}}"
              text_outline ${-foo},2,2,23,2,1,255

         while (+):
             condition

           End a 'do...while' block and go back to associated 'do' if
           specified condition holds.
           'condition' is a mathematical expression, whose evaluation is
           interpreted as { 0:false | other:true }.

         11.14. Neural Networks
                ---------------

         nn_lib ::

           Return the list of library functions that has to be included in a
       math
           expression,in order to use the neural network library.

         nn_init:

           Initialize a new network.

         nn_check_layer:
             name

           Check that the layer with specified name already exists in the
       network.

         nn_add:
             out,in0,_in1

           Add an 'add' layer to the network.

           Default value: 'in1=. (previous layer)'.

         nn_append:
             out,in0,_in1

           Add an 'append' layer to the network.

           Default value: 'in1=. (previous layer)'.

         nn_avgpool2d:
             out,_in,_patch_size>1

           Add a 'avgpool2d' layer (2D average pooling) to the network.

           Default value: 'in=. (previous layer)'.

         nn_avgpool3d:
             out,_in,_patch_size>1

           Add a 'avgpool3d' layer (3D average pooling) to the network.

           Default value: 'in=. (previous layer)'.

         nn_clone:
             name0,name1,_in

           Add a 'clone' layer to the network.

           Default value: 'in=. (previous layer)'.

         nn_conv2d:
             out,in,nb_channels>0,_kernel_size>0,_stride>0,_dilation,_border_shrink>=0,
               _boundary_conditions,0<=_learning_mode<=3

           Add a 'conv2d' layer (2D convolutional layer) to the network.
           'boundary_conditions' can be { 0:dirichlet | 1:neumann |
           2:periodic | 3:mirror }.
           'learning_mode' can be { 0:no learning | 1:weights only |
           2:biases only | 3:weights+biases }.

           Default values: 'kernel_size=3', 'stride=1',
            'dilation=1', 'border_shrink=0', 'boundary_conditions=1     fR'
       and 'learning_mode=3'.

         nn_conv2dnl:
             out,in,nb_channels>0,_kernel_size>0,_stride>0,_dilation>0,
               _border_shrink>=0,_boundary_conditions,_activation,
               0<=_learning_mode<=3

           Add a 'conv2dnl' (2D convolutional layer followed by a
           non-linearity) to the network.
           'boundary_conditions' can be { 0:dirichlet | 1:neumann |
           2:periodic | 3:mirror }.
           'learning_mode' can be { 0:no learning | 1:weights only |
           2:biases only | 3:weights+biases }.

           Default values: 'kernel_size=3', 'stride=1',
            'dilation=1', 'border_shrink=0', 'boundary_conditions=1     fR',
       'activation=leakyrelu' and 'learning_mode=3'.

         nn_conv2dnnl:
             out,in,nb_channels>0,_kernel_size>0,_stride>0,_dilation>0,
               _border_shrink>=0,_boundary_conditions,_activation,
               0<=_learning_mode<=3

           Add a 'conv2dnnl' (2D convolutional layer followed by a
           normalization layer, then a non-linearity) to the network.
           'boundary_conditions' can be { 0:dirichlet | 1:neumann |
           2:periodic | 3:mirror }.
           'learning_mode' can be { 0:no learning | 1:weights only |
           2:biases only | 3:weights+biases }.

           Default values: 'kernel_size=3', 'stride=1',
            'dilation=1', 'border_shrink=0', 'boundary_conditions=1     fR',
       'activation=leakyrelu' and 'learning_mode=3'.

         nn_conv3d:
             out,in,nb_channels>0,_kernel_size>0,_stride>0,_dilation,_border_shrink>=0,
               _boundary_conditions,0<=_learning_mode<=3

           Add a 'conv3d' layer (3D convolutional layer) to the network.
           'boundary_conditions' can be { 0:dirichlet | 1:neumann |
           2:periodic | 3:mirror }.
           'learning_mode' can be { 0:no learning | 1:weights only |
           2:biases only | 3:weights+biases }.

           Default values: 'kernel_size=3', 'stride=1',
            'dilation=1', 'border_shrink=0', 'boundary_conditions=1     fR'
       and 'learning_mode=3'.

         nn_conv3dnl:
             out,in,nb_channels>0,_kernel_size>0,_stride>0,_dilation>0,
               _border_shrink>=0,_boundary_conditions,_activation,
               0<=_learning_mode<=3

           Add a 'conv3dnl' (3D convolutional layer followed by a
           non-linearity) to the network.
           'boundary_conditions' can be { 0:dirichlet | 1:neumann |
           2:periodic | 3:mirror }.
           'learning_mode' can be { 0:no learning | 1:weights only |
           2:biases only | 3:weights+biases }.

           Default values: 'kernel_size=3', 'stride=1',
            'dilation=1', 'border_shrink=0', 'boundary_conditions=1     fR',
       'activation=leakyrelu' and 'learning_mode=3'.

         nn_conv3dnnl:
             out,in,nb_channels>0,_kernel_size>0,_stride>0,_dilation>0,
               _border_shrink>=0,_boundary_conditions,_activation,
               0<=_learning_mode<=3

           Add a 'conv3dnnl' (3D convolutional layer followed by a
           normalization layer, then a non-linearity) to the network.
           'boundary_conditions' can be { 0:dirichlet | 1:neumann |
           2:periodic | 3:mirror }.
           'learning_mode' can be { 0:no learning | 1:weights only |
           2:biases only | 3:weights+biases }.

           Default values: 'kernel_size=3', 'stride=1',
            'dilation=1', 'border_shrink=0', 'boundary_conditions=1     fR',
       'activation=leakyrelu' and 'learning_mode=3'.

         nn_crop:
             out,in,x0,y0,z0,c0,x1,y1,z1,c1,_boundary_conditions

           Add a 'crop' layer to the network.
           'boundary_conditions' can be { 0:dirichlet | 1:neumann |
           2:periodic | 3:mirror }.

           Default value: 'boundary_conditions=0'.

         nn_distance:
             out,in0,_in1,_metric={ 0:squared-L2 | p>0:Lp-norm }

           Add a 'distance' layer to the network (distance between two inputs,
           with specified metric).

           Default value: 'in=. (previous layer)',

         nn_dropout:
             out,in,0<=dropout_rate<1

           Add a 'dropout' layer to the network.

         nn_fc:
             out,in,nb_channels>0,0<=_learning_mode<=3

           Add a 'fc' layer (fully connected layer) to the network.
           'learning_mode' can be { 0:no learning | 1:weights only |
           2:biases only | 3:weights+biases }.

           Default value: 'learning_mode=3'.

         nn_nlfc:
             out,in,nb_channels>0,_activation,0<=_learning_mode<=3

           Add a 'nlfc' layer (nonlinear fully connected layer) to the
       network.
           'learning_mode' can be { 0:no learning | 1:weights only |
           2:biases only | 3:weights+biases }.

           Default values: 'activation=leakyrelu' and
            'learning_mode=3'.

         nn_fcnl:
             out,in,nb_neurons>0,_activation,0<=_learning_mode<=3

           Add a 'fcnl' layer (fully connected layer followed by a
           non-linearity) to the network.
           'learning_mode' can be { 0:no learning | 1:weights only |
           2:biases only | 3:weights+biases }.

           Default values: 'activation=leakyrelu' and
            'learning_mode=3'.

         nn_fcnnl:
             out,in,nb_neurons>0,_activation,0<=_learning_mode<=3

           Add a 'fcnnl' layer (fully connected layer followed by a
           normalization layer, then a non-linearity) to the network.
           'learning_mode' can be { 0:no learning | 1:weights only |
           2:biases only | 3:weights+biases }.

           Default values: 'activation=leakyrelu' and
            'learning_mode=3'.

         nn_input:
             name,width,_height,_depth,_spectrum

           Add a new 'input' to the network.

           Default values: 'height=1', 'depth=1' and
            'spectrum=1'.

         nn_maxpool2d:
             out,_in,_patch_size>1

           Add a 'maxpool2d' layer (2D max pooling) to the network.

           Default values: 'in=. (previous layer)' and 'patch_size=2'.

         nn_maxpool3d:
             out,_in,_patch_size>1

           Add a 'maxpool3d' layer (3d max pooling) to the network.

           Default values: 'in=. (previous layer)' and 'patch_size=2'.

         nn_mul:
             out,in0,_in1

           Add an 'mul' layer to the network.

           Default value: 'in1=. (previous layer)'.

         nn_nl:
             out,_in,_activation

           Add a 'nl' (nonlinearity) layer to the network.
           'activation' can be { elu | gelu | leakyrelu | linear | relu |
           sigmoid | sin | sinc | softmax | sqr | sqrt | swish | tanh }.

           Default values: 'in=. (previous layer)' and
            'activation=leakyrelu'.

         nn_normalize:
             out,_in,_normalization_mode_,0<=_learning_mode<=3

           Add a 'normalize' layer to the network.
           'normalization_mode' can be { 0:global parameters |
           1:channel-by-channel parameters }
           'learning_mode' can be { 0:no learning | 1:alpha only | 2:beta
           only | 3:alpha+beta }

           Default values: 'in=. (previous layer)','normalization_mode=0'
            and 'learning_mode=3'.

         nn_patchdown2d:
             out,_in,_patch_size>1

           Add a 'patchdown2d' (2D downscale by patch) layer to the network.

           Default values: 'in=. (previous layer)' and 'patch_size=2'.

         nn_patchdown3d:
             out,_in,_patch_size>1

           Add a 'patchdown3d' (3D downscale by patch) layer to the network.

           Default values: 'in=. (previous layer)' and 'patch_size=2'.

         nn_patchup2d:
             out,_in,_patch_size>1

           Add a 'patchup2d' (2D upscale by patch) layer to the network.

           Default values: 'in=. (previous layer)' and 'patch_size=2'.

         nn_patchup3d:
             out,_in,_patch_size>1

           Add a 'patchup3d' (3D upscale by patch) layer to the network.

           Default values: 'in=. (previous layer)' and 'patch_size=2'.

         nn_rename:
             out,_in

           Add a 'rename' layer to the network.

           Default value: 'in=. (previous layer)'.

         nn_resconv2d:
             out,_in,_kernel_size>0,_dilation>0,_boundary_conditions,
               0<=_learning_mode<=3

           Add a 'resconv2d' (residual 2D convolutional layer) to the network.
           'boundary_conditions' can be { 0:dirichlet | 1:neumann |
           2:periodic | 3:mirror }.
           'learning_mode' can be { 0:no learning | 1:weights only |
           2:biases only | 3:weights+biases }.

           Default values: 'in=. (previous layer)', 'kernel_size=3',
            'dilation=1', 'boundary_conditions=1' and
            'learning_mode=3'.

         nn_resconv2dnl:
             out,_in,_kernel_size>0,_dilation>0,_boundary_conditions,_activation,
               0<=_learning_mode<=3

           Add a 'resconv2dnl' (residual 2D convolutional layer followed by a
           non-linearity) to the network.
           'boundary_conditions' can be { 0:dirichlet | 1:neumann |
           2:periodic | 3:mirror }.
           'learning_mode' can be { 0:no learning | 1:weights only |
           2:biases only | 3:weights+biases }.

           Default values: 'in=. (previous layer)', 'kernel_size=3',
            'dilation=1', 'boundary_conditions=1',
            'activation=leakyrelu' and 'learning_mode=3'.

         nn_resconv2dnnl:
             out,_in,_kernel_size>0,_dilation>0,_boundary_conditions,_activation,
               0<=_learning_mode<=3

           Add a 'resconv2dnnl' (residual 2D convolutional layer followed by a
           normalization layer, then a non-linearity)to the network.
           'boundary_conditions' can be { 0:dirichlet | 1:neumann |
           2:periodic | 3:mirror }.
           'learning_mode' can be { 0:no learning | 1:weights only |
           2:biases only | 3:weights+biases }.

           Default values: 'in=. (previous layer)', 'kernel_size=3',
            'dilation=1', 'boundary_conditions=1',
            'activation=leakyrelu' and 'learning_mode=3'.

         nn_resconv3d:
             out,_in,_kernel_size>0,_dilation>0,_boundary_conditions,
               0<=_learning_mode<=3

           Add a 'resconv3d' (residual 3D convolutional layer) to the network.
           'boundary_conditions' can be { 0:dirichlet | 1:neumann |
           2:periodic | 3:mirror }.
           'learning_mode' can be { 0:no learning | 1:weights only |
           2:biases only | 3:weights+biases }.

           Default values: 'in=. (previous layer)', 'kernel_size=3',
            'dilation=1', 'boundary_conditions=1' and
            'learning_mode=3'.

         nn_resconv3dnl:
             out,_in,_kernel_size>0,_dilation>0,_boundary_conditions,_activation,
               0<=_learning_mode<=3

           Add a 'resconv3dnl' (residual 3D convolutional layer followed by a
           non-linearity) to the network.
           'boundary_conditions' can be { 0:dirichlet | 1:neumann |
           2:periodic | 3:mirror }.
           'learning_mode' can be { 0:no learning | 1:weights only |
           2:biases only | 3:weights+biases }.

           Default values: 'in=. (previous layer)', 'kernel_size=3',
            'dilation=1', 'boundary_conditions=1',
            activation='leakyrelu' and 'learning_mode=3'.

         nn_resconv3dnnl:
             out,_in,_kernel_size>0,_dilation>0,_boundary_conditions,_activation,
               0<=_learning_mode<=3

           Add a 'resconv3dnnl' (residual 3D convolutional layer followed by a
           normalization layer, then a non-linearity)to the network.
           'boundary_conditions' can be { 0:dirichlet | 1:neumann |
           2:periodic | 3:mirror }.
           'learning_mode' can be { 0:no learning | 1:weights only |
           2:biases only | 3:weights+biases }.

           Default values: 'in=. (previous layer)', 'kernel_size=3',
            'dilation=1', 'boundary_conditions=1',
            'activation=leakyrelu' and 'learning_mode=3'.

         nn_resfc:
             out,_in,0<=_learning_mode<=3

           Add a 'resfc' (residual fully connecter layer) to the network.
           'learning_mode' can be { 0:no learning | 1:weights only |
           2:biases only | 3:weights+biases }.

           Default values: 'in=. (previous layer)' and 'learning_mode=3'.

         nn_resfcnl:
             out,_in,_activation,0<=_learning_mode<=3

           Add a 'resfcnl' (residual fully connecter layer followed by a
           non-linearity) to the network.
           'learning_mode' can be { 0:no learning | 1:weights only |
           2:biases only | 3:weights+biases }.

           Default values: 'in=. (previous layer)',
            'activation=leakyrelu' and 'learning_mode=3'.

         nn_resfcnnl:
             out,_in,_activation,0<=_learning_mode<=3

           Add a 'resfcnnl' (residual fully connecter layer followed by a
           normalization layer, then a non-linearity) to the network.
           'learning_mode' can be { 0:no learning | 1:weights only |
           2:biases only | 3:weights+biases }.

           Default values: 'in=. (previous layer)',
            'activation=leakyrelu' and 'learning_mode=3'.

         nn_reshape:
             out,in,width>0,height>0,depth>0,spectrum>0

           Add a 'reshape' layer to the network.

         nn_resize:
             out,in,width[%]>0,_height[%]>0,_depth[%]>0,_spectrum[%]>0,_interpolation

           Add a 'resize' layer to the network.

           Default values: 'height=depth=spectrum=100%' and
            'interpolation=3'.

         nn_run:
             out,in,"command",_width[%]>0,_height[%]>0,_depth[%]>0,_spectrum[%]>0

           Add a 'run' layer to the network.

           Default values: 'width=height=depth=spectrum=100%'.

         nn_split:
             name0,name1,in,nb_channels0

           Add a 'split' layer to the network.

         nn_loss_binary_crossentropy:
             out,in,ground_truth

           Add a 'binary_crossentropy' loss to the network (binary cross
           entropy).

         nn_loss_crossentropy:
             out,in,ground_truth

           Add a 'crossentropy' loss to the network (cross entropy).

         nn_loss_mse:
             out,in,ground_truth

           Add a 'mse' loss to the network (mean-squared error).

         nn_loss_normp:
             out,in,ground_truth,_metric={ 0:squared-L2 | p>0:Lp-norm }

           Add a 'normp' loss to the network (||out - ground_truth||_p).

           Default value: 'metric=1'.

         nn_loss_softmax_crossentropy:
             out,in,ground_truth

           Add a 'softmax_crossentropy' loss to the network (softmax followed
           by cross entropy).

         nn_print:

           Print info on current neural network.

         nn_trainer:
             name,_loss,_learning_rate>0,_optimizer,_scheduler

           Add a network trainer to the network.
           'optimizer' can be { sgd | rmsprop | adam | adamax }.
           'scheduler' can be { constant | linear | exponential | adaptive
           }.

           Default values: 'loss=. (previous loss)', 'learning_rate=2e-4',
             'optimizer=rmsprop' and 'scheduler=constant'.

         nn_size:

           Return size of the current network (i.e. number of stored
       parameters).

         nn_load:
             'filename.gmz',_include_trainer_data={ 0:no | 1:yes }

           Load and initialize network saved as a .gmz file.
           Neural network files can be only loaded in .gmz format.

           Default value: 'include_trainer_data=1'.

         nn_save:
             'filename.gmz',_include_trainer_data={ 0:no | 1:yes }

           Save current network as a .gmz file.
           '.gmz' is mandatory extension, specifying another file extension
       will
           throw an error.

           Default value: 'include_trainer_data=1'.

         nn_store:
             'variable_name',_include_trainer_data={ 0:no | 1:yes }

           Store current network into a variable.

           Default value: 'include_trainer_data=1'.

         11.15. Arrays, Tiles and Frames
                ------------------------

         array:
             M>0,_N>0,_expand_type={ 0:min | 1:max | 2:all }

           Create MxN array from selected images.

           Default values: 'N=M' and 'expand_type=0'.

           Example:
             [#1] image.jpg array 3,2,2

         array_fade:
             M>0,_N>0,0<=_fade_start<=100,0<=_fade_end<=100,_expand_type={0:min
       | 1:max
               | 2:all}

           Create MxN array from selected images.

           Default values: 'N=M', 'fade_start=60',
            'fade_end=90' and 'expand_type=1'.

           Example:
             [#1] image.jpg array_fade 3,2

         array_mirror:
             N>=0,_dir={ 0:x | 1:y | 2:xy | 3:tri-xy },_expand_type={ 0 | 1 }

           Create 2^Nx2^N array from selected images.

           Default values: 'dir=2' and 'expand_type=0'.

           Example:
             [#1] image.jpg array_mirror 2

         array_random:
             Ms>0,_Ns>0,_Md>0,_Nd>0

           Create MdxNd array of tiles from selected MsxNs source arrays.

           Default values: 'Ns=Ms', 'Md=Ms' and 'Nd=Ns'.

           Example:
             [#1] image.jpg +array_random 8,8,15,10

         frame:
             Shortcut for command 'frame_xy'.

         frame_blur:
             _sharpness>0,_size>=0,_smoothness,_shading,_blur

           Draw RGBA-colored round frame in selected images.

           Default values: 'sharpness=10', 'size=30',
            'smoothness=0', 'shading=1' and 'blur=3%'.

           Example:
             [#1] image.jpg frame_blur 3,30,8,10%

         frame_cube:
             _depth>=0,_centering_x,_centering_y,_left_side={ 0:normal |
       1:mirror-x |
               2:mirror-y | 3:mirror-xy },_right_side,_lower_side,_upper_side

           Insert 3D frames in selected images.

           Default values: 'depth=1', 'centering_x=centering_y=0'
            and 'left_side=right_side,lower_side=upper_side=0'.

           Example:
             [#1] image.jpg frame_cube ,

         frame_fuzzy:
             size_x[%]>=0,_size_y[%]>=0,_fuzzyness>=0,_smoothness[%]>=0,_R,_G,_B,_A

           Draw RGBA-colored fuzzy frame in selected images.

           Default values: 'size_y=size_x', 'fuzzyness=5',
            'smoothness=1' and 'R=G=B=A=255'.

           Example:
             [#1] image.jpg frame_fuzzy 20

         frame_painting:
             _size[%]>=0,0<=_contrast<=1,_profile_smoothness[%]>=0,_R,_G,_B,
               _vignette_size[%]>=0,_vignette_contrast>=0,_defects_contrast>=0,
               0<=_defects_density<=100,_defects_size>=0,_defects_smoothness[%]>=0,
               _serial_number

           Add a painting frame to selected images.

           Default values: 'size=10%', 'contrast=0.4',
            'profile_smoothness=6%', 'R=225', 'G=200',
            'B=120', 'vignette_size=2%', 'vignette_contrast=400',
             'defects_contrast=50', 'defects_density=10',
            'defects_size=1', 'defects_smoothness=0.5%' and
            'serial_number=123456789'.

           Example:
             [#1] image.jpg frame_painting ,

         frame_pattern:
             M>=3,_constrain_size={ 0 | 1 } |
             M>=3,_[frame_image],_constrain_size={ 0 | 1 }

           Insert selected pattern frame in selected images.

           Default values: 'pattern=0' and 'constrain_size=0'.

           Example:
             [#1] image.jpg frame_pattern 8

         frame_round:
             size_x[%]>=0,size_y[%]>=0,radius[%]>=0,_smoothness[%]>=0,_col1,...,_colN

           Insert an inner round frame in selected images.

           Default values: 'size_x=size_y=5%, 'radius=30%',
            'smoothness=0' and 'col=0,0,0,255'.

         frame_seamless:
             frame_size>=0,_patch_size>0,_blend_size>=0,_frame_direction={
       0:inner
               (preserve image size) | 1:outer }

           Insert frame in selected images, so that tiling the resulting image
       makes
           less visible seams.

           Default values: 'patch_size=7', 'blend_size=5' and
            'frame_direction=1'.

           Example:
             [#1] image.jpg +frame_seamless 30 array 2,2

         frame_x:
             size_x[%],_col1,...,_colN

           Insert outer frame along the x-axis in selected images.

           Default values: 'col1=col2=col3=255' and 'col4=255'.

           Example:
             [#1] image.jpg frame_x 20,255,0,255

         frame_xy:
             size_x[%],_size_y[%],_col1,...,_colN

           Insert outer frame along the x-axis in selected images.

           Default values: 'size_y=size_x', 'col1=col2=col3=255'
            and 'col4=255'.
           (equivalent to shortcut command 'frame').

           Example:
             [#1] image.jpg frame_xy 1,1,0 frame_xy 20,10,255,0,255

         frame_xyz:
             size_x[%],_size_y[%],_size_z[%]_col1,...,_colN

           Insert outer frame along the x-axis in selected images.

           Default values: 'size_y=size_x=size_z',
            'col1=col2=col3=255' and 'col4=255'.

         frame_y:
             size_y[%],_col1,...,_colN

           Insert outer frame along the y-axis in selected images.

           Default values: 'col1=col2=col3=255' and 'col4=255'.

           Example:
             [#1] image.jpg frame_y 20,255,0,255

         img2ascii:
             _charset,_analysis_scale>0,_analysis_smoothness[%]>=0,_synthesis_scale>0,
               _output_ascii_filename

           Render selected images as binary ascii art.
           This command returns the corresponding the list of widths and
       heights
           (expressed as a number of characters)
           for each selected image.

           Default values: 'charset=[ascii charset]', 'analysis_scale=16',
             'analysis_smoothness=20%', 'synthesis_scale=16' and
            '_output_ascii_filename=[undefined]'.

           Example:
             [#1] image.jpg img2ascii ,

         imagegrid:
             M>0,_N>0

           Create MxN image grid from selected images.

           Default value: 'N=M'.

           Example:
             [#1] image.jpg imagegrid 16

         imagegrid_hexagonal:
             _resolution>0,0<=_outline<=1

           Create hexagonal grids from selected images.

           Default values: 'resolution=32', 'outline=0.1' and
            'is_antialiased=1'.

           Example:
             [#1] image.jpg imagegrid_hexagonal 24

         imagegrid_triangular:
             pattern_width>=1,_pattern_height>=1,_pattern_type,0<=_outline_opacity<=1,
               _outline_color1,...

           Create triangular grids from selected images.
           'pattern type' can be { 0:horizontal | 1:vertical | 2:crossed |
       3:cube
           | 4:decreasing | 5:increasing }.

           Default values: 'pattern_width=24',
            'pattern_height=pattern_width', 'pattern_type=0',
            'outline_opacity=0.1' and 'outline_color1=0'.

           Example:
             [#1] image.jpg imagegrid_triangular 6,10,3,0.5

         linearize_tiles:
             M>0,_N>0

           Linearize MxN tiles on selected images.

           Default value: 'N=M'.

           Example:
             [#1] image.jpg +linearize_tiles 16

         map_sprites:
             _nb_sprites>=1,_allow_rotation={ 0:none | 1:90 deg. | 2:180 deg.
       }

           Map set of sprites (defined as the 'nb_sprites' latest images of
       the
           selection) to other selected images,
           according to the luminosity of their pixel values.

           Example:
             [#1] image.jpg rescale2d ,48 repeat 16 ball {8+2*$>},${-rgb}
       mul[-1]
              {(1+$>)/16} done map_sprites 16

         pack:
             is_ratio_constraint={ 0 | 1 },_sort_criterion

           Pack selected images into a single image.
           The returned status contains the list of new (x,y) offsets for each
       input
           image.
           Parameter 'is_ratio_constraint' tells if the resulting image must
           tend to a square image.

           Default values: 'is_ratio_constraint=0' and
            'sort_criterion=max(w,h)'.

           Example:
             [#1] image.jpg repeat 10 +rescale2d[-1] 75% balance_gamma[-1]
       ${-rgb}
              done pack 0

         puzzle:
             _width>0,_height>0,_M>=1,_N>=1,_curvature,_centering,
               _connectors_variability,_resolution>=1

           Input puzzle binary mask with specified size and geometry.

           Default values: 'width=height=512', 'M=N=5',
            'curvature=0.5', 'centering=0.5',
            'connectors_variability=0.5' and 'resolution=64'.

           Example:
             [#1] puzzle ,

         quadratize_tiles:
             M>0,_N>0

           Quadratize MxN tiles on selected images.

           Default value: 'N=M'.

           Example:
             [#1] image.jpg +quadratize_tiles 16

         rotate_tiles:
             angle,_M>0,N>0

           Apply MxN tiled-rotation effect on selected images.

           Default values: 'M=8' and 'N=M'.

           Example:
             [#1] image.jpg to_rgba rotate_tiles 10,8 drop_shadow 10,10
       display_rgba

         shift_tiles:
             M>0,_N>0,_amplitude

           Apply MxN tiled-shift effect on selected images.

           Default values: 'N=M' and 'amplitude=20'.

           Example:
             [#1] image.jpg +shift_tiles 8,8,10

         taquin:
             M>0,_N>0,_remove_tile={ 0:none | 1:first | 2:last | 3:random
       },_relief,
               _border_thickness[%],_border_outline[%],_outline_color

           Create MxN taquin puzzle from selected images.

           Default value: 'N=M', 'relief=50',
            'border_thickness=5', 'border_outline=0' and
            'remove_tile=0'.

           Example:
             [#1] image.jpg +taquin 8

         tunnel:
             _level>=0,_factor>0,_centering_x,_centering_y,_opacity,_angle

           Apply tunnel effect on selected images.

           Default values: 'level=9', 'factor=80%',
            'centering_x=centering_y=0.5', 'opacity=1' and
            'angle=0'

           Example:
             [#1] image.jpg tunnel 20

         11.16. Artistic
                --------

         boxfitting:
             _min_box_size>=1,_max_box_size>=0,_initial_density>=0,_min_spacing>0

           Apply box fitting effect on selected images, as displayed the web
       page:
           http://www.complexification.net/gallery/machines/boxFittingImg/.

           Default values: 'min_box_size=1', 'max_box_size=0',
            'initial_density=0.25' and 'min_spacing=1'.

           Example:
             [#1] image.jpg boxfitting ,

         brushify:
             [brush],_brush_nb_sizes>=1,0<=_brush_min_size_factor<=1,
               _brush_nb_orientations>=1,_brush_light_type,0<=_brush_light_strength
               <=1,_brush_opacity,_painting_density[%]>=0,0<=_painting_contours_coh
               erence<=1,0<=_painting_orientation_coherence<=1,
               _painting_coherence_alpha[%]>=0,_painting_coherence_sigma[%]>=0,
               _painting_primary_angle,0<=_painting_angle_dispersion<=1

           Apply specified brush to create painterly versions of specified
       images.
           'brush_light_type' can be { 0:none | 1:flat | 2:darken |
           3:lighten | 4:full }.

           Default values: 'brush_nb_sizes=3',
            'brush_min_size_factor=0.66', 'brush_nb_orientations=12',
            'brush_light_type=0', 'brush_light_strength=0.25',
            'brush_opacity=0.8', 'painting_density=20%',
            'painting_contours_coherence=0.9', 'painting_orientation_coher
            ence=0.9', 'painting_coherence_alpha=1',
            'painting_coherence_sigma=1', 'painting_primary_angle=0',
            'painting_angle_dispersion=0.2'

           Example:
             [#1] image.jpg 40,40 gaussian[-1] 10,4 spread[-1] 10,0
       brushify[0] [1],1

         cartoon:
             _smoothness,_sharpening,_threshold>=0,_thickness>=0,_color>=0,
               quantization>0

           Apply cartoon effect on selected images.

           Default values: 'smoothness=3', 'sharpening=150',
            'threshold=20', 'thickness=0.25', 'color=1.5' and
            'quantization=8'.

           Example:
             [#1] image.jpg cartoon 3,50,10,0.25,3,16

         color_ellipses:
             _count>0,_radius>=0,_opacity>=0

           Add random color ellipses to selected images.

           Default values: 'count=400', 'radius=5' and
            'opacity=0.1'.

           Example:
             [#1] image.jpg +color_ellipses ,,0.15

         cubism:
             _density>=0,0<=_thickness<=50,_max_angle,_opacity,_smoothness>=0

           Apply cubism effect on selected images.

           Default values: 'density=50', 'thickness=10',
            'max_angle=75', 'opacity=0.7' and 'smoothness=0'.

           Example:
             [#1] image.jpg cubism ,

         draw_whirl:
             _amplitude>=0

           Apply whirl drawing effect on selected images.

           Default value: 'amplitude=100'.

           Example:
             [#1] image.jpg draw_whirl ,

         drawing:
             _amplitude>=0

           Apply drawing effect on selected images.

           Default value: 'amplitude=200'.

           Example:
             [#1] image.jpg +drawing ,

         drop_shadow:
             _offset_x[%],_offset_y[%],_smoothness[%]>=0,_curvature_x,_curvature_y,
               _expand_size={ 0 | 1 }

           Drop shadow behind selected images.

           Default values: 'offset_x=20', 'offset_y=offset_x',
            'smoothness=5', 'curvature=0' and 'expand_size=1'.

           Example:
             [#1] image.jpg drop_shadow 10,20,5,0.5 expand_xy 20,0
       display_rgba

         drop_shadow:
             _offset_x[%],_offset_y[%],_smoothness[%]>=0,curvature_x>=0,curvature_y>=0,
               _expand_size={ 0 | 1 },_output_separate_layers={ 0 | 1 }

           Drop shadow behind selected images.

           Default values: 'offset_x=20', 'offset_y=offset_x',
            'smoothness=5', 'curvature_x=curvature_y=0',
            'expand_size=1' and 'output_separate_layers=0'.

           Example:
             [#1] image.jpg drop_shadow 10,20,5,0.5 display_rgba

         ellipsionism:
             _R>0[%],_r>0[%],_smoothness>=0[%],_opacity,_outline>0,_density>0

           Apply ellipsionism filter to selected images.

           Default values: 'R=10', 'r=3', 'smoothness=1%',
            'opacity=0.7', 'outline=8' and 'density=0.6'.

           Example:
             [#1] image.jpg ellipsionism ,

         fire_edges:
             _edges>=0,0<=_attenuation<=1,_smoothness>=0,_threshold>=0,_nb_frames>0,
               _starting_frame>=0,frame_skip>=0

           Generate fire effect from edges of selected images.

           Default values: 'edges=0.7', 'attenuation=0.25',
            'smoothness=0.5', 'threshold=25', 'nb_frames=1',
            'starting_frame=20' and 'frame_skip=0'.

           Example:
             [#1] image.jpg fire_edges ,

         fractalize:
             0<=detail_level<=1

           Randomly fractalize selected images.

           Default value: 'detail_level=0.8'

           Example:
             [#1] image.jpg fractalize ,

         glow:
             _amplitude>=0

           Add soft glow on selected images.

           Default value: 'amplitude=1%'.

           Example:
             [#1] image.jpg glow ,

         halftone:
             nb_levels>=2,_size_dark>=2,_size_bright>=2,_shape={ 0:square |
       1:diamond |
               2:circle | 3:inv-square | 4:inv-diamond | 5:inv-circle },
               _smoothness[%]>=0

           Apply halftone dithering to selected images.

           Default values: 'nb_levels=5', 'size_dark=8',
            'size_bright=8', 'shape=5' and 'smoothnesss=0'.

           Example:
             [#1] image.jpg halftone ,

         hardsketchbw:
             _amplitude>=0,_density>=0,_opacity,0<=_edge_threshold<=100,_is_fast={
       0 |
               1 }

           Apply hard B&W sketch effect on selected images.

           Default values: 'amplitude=1000', 'sampling=3',
            'opacity=0.1', 'edge_threshold=20' and 'is_fast=0'.

           Example:
             [#1] image.jpg +hardsketchbw 200,70,0.1,10 median[-1] 2 +local
       reverse
              blur[-1] 3 blend[-2,-1] overlay done

         hearts:
             _density>=0

           Apply heart effect on selected images.

           Default value: 'density=10'.

           Example:
             [#1] image.jpg hearts ,

         houghsketchbw:
             _density>=0,_radius>0,0<=_threshold<=100,0<=_opacity<=1,_votesize[%]>0

           Apply hough B&W sketch effect on selected images.

           Default values: 'density=100', 'radius=3',
            'threshold=100', 'opacity=0.1' and 'votesize=100%'.

           Example:
             [#1] image.jpg +houghsketchbw ,

         lightrays:
             100<=_density<=0,_center_x[%],_center_y[%],_ray_length>=0,
               _ray_attenuation>=0

           Generate ray lights from the edges of selected images.

           Default values: 'density=50%', 'center_x=50%',
            'center_y=50%', 'ray_length=0.9' and
            'ray_attenuation=0.5'.

           Example:
             [#1] image.jpg +lightrays , + cut 0,255

         light_relief:
             _ambient_light,_specular_lightness,_specular_size,_darkness,
               _light_smoothness,_xl,_yl,_zl,_zscale,_opacity_is_heightmap={ 0
       | 1
               }

           Apply relief light to selected images.
           Default values(s) : 'ambient_light=0.3',
           'specular_lightness=0.5', 'specular_size=0.2',
           'darkness=0', 'xl=0.2', 'yl=zl=0.5',
           'zscale=1', 'opacity=1' and 'opacity_is_heightmap=0'.

           Example:
             [#1] image.jpg blur 2 light_relief 0.3,4,0.1,0

         linify:
             0<=_density<=100,_spreading>=0,_resolution[%]>0,_line_opacity>=0,
               _line_precision>0,_mode={ 0:subtractive | 1:additive }

           Apply linify effect on selected images.
           The algorithm is inspired from the one described on the webpage
           http://linify.me/about.

           Default values: 'density=50', 'spreading=2',
            'resolution=40%', 'line_opacity=10',
            'line_precision=24' and 'mode=0'.

           Example:
             [#1] image.jpg linify 60

         mosaic:
             0<=_density<=100

           Create random mosaic from selected images.

           Default values: 'density=30'.

           Example:
             [#1] image.jpg mosaic , +fill "I!=J(1) || I!=J(0,1)?[0,0,0]:I"

         old_photo:

           Apply old photo effect on selected images.

           Example:
             [#1] image.jpg old_photo

         pencilbw:
             _size>=0,_amplitude>=0

           Apply B&W pencil effect on selected images.

           Default values: 'size=0.3' and 'amplitude=60'.

           Example:
             [#1] image.jpg pencilbw ,

         pixelsort:
             _ordering={ + | - },_axis={ x | y | z | xy | yx
       },_[sorting_criterion],
               _[mask]

           Apply a 'pixel sorting' algorithm on selected images, as described
       in the
           page :
           http://satyarth.me/articles/pixel-sorting/.

           Default values: 'ordering=+', 'axis=x' and
            'sorting_criterion=mask=(undefined)'.

           Example:
             [#1] image.jpg +norm +ge[-1] 30% +pixelsort[0] +,y,[1],[2]

         polaroid:
             _size1>=0,_size2>=0

           Create polaroid effect in selected images.

           Default values: 'size1=10' and 'size2=20'.

           Example:
             [#1] image.jpg to_rgba polaroid 5,30 rotate 20 drop_shadow ,
       drgba

         polygonize:
             _warp_amplitude>=0,_smoothness[%]>=0,_min_area[%]>=0,_resolution_x[%]>0,
               _resolution_y[%]>0

           Apply polygon effect on selected images.

           Default values: 'warp_amplitude=300', 'smoothness=2%',
            'min_area=0.1%', 'resolution_x=resolution_y=10%'.

           Example:
             [#1] image.jpg +polygonize 100,10 fill[-1] "I!=J(1) ||
       I!=J(0,1)?[0,0,
              0]:I"

         poster_edges:
             0<=_edge_threshold<=100,0<=_edge_shade<=100,_edge_thickness>=0,
               _edge_antialiasing>=0,0<=_posterization_level<=15,
               _posterization_antialiasing>=0

           Apply poster edges effect on selected images.

           Default values: 'edge_threshold=40', 'edge_shade=5',
            'edge_thickness=0.5', 'edge_antialiasing=10',
            'posterization_level=12' and 'posterization_antialiasing=0'
            .

           Example:
             [#1] image.jpg poster_edges ,

         poster_hope:
             _smoothness>=0

           Apply Hope stencil poster effect on selected images.

           Default value: 'smoothness=3'.

           Example:
             [#1] image.jpg poster_hope ,

         rodilius:
             0<=_amplitude<=100,_0<=thickness<=100,_sharpness>=0,_nb_orientations>0,
               _offset,_color_mode={ 0:darker | 1:brighter }

           Apply rodilius (fractalius-like) filter on selected images.

           Default values: 'amplitude=10', 'thickness=10',
            'sharpness=400', 'nb_orientations=7', 'offset=0' and
            'color_mode=1'.

           Example:
             [#1] image.jpg rodilius 12,10,300,10 normalize_local 10,6
             [#2] image.jpg normalize_local 10,16 rodilius 10,4,400,16 smooth
       60,0,1,
              1,4 normalize_local 10,16

         sketchbw:
             _nb_angles>0,_start_angle,_angle_range>=0,_length>=0,_threshold>=0,
               _opacity,_bgfactor>=0,_density>0,_sharpness>=0,_anisotropy>=0,
               _smoothness>=0,_coherence>=0,_is_boost={ 0 | 1 },_is_curved={ 0
       | 1
               }

           Apply sketch effect to selected images.

           Default values: 'nb_angles=2', 'start_angle=45',
            'angle_range=180', 'length=30', 'threshold=3',
            'opacity=0.03', 'bgfactor=0', 'density=0.6',
            'sharpness=0.1', 'anisotropy=0.6', 'smoothness=0.25',
             'coherence=1', 'is_boost=0' and 'is_curved=1'.

           Example:
             [#1] image.jpg +sketchbw 1 reverse blur[-1] 3 blend[-2,-1]
       overlay

         sponge:
             _size>0

           Apply sponge effect on selected images.

           Default value: 'size=13'.

           Example:
             [#1] image.jpg sponge ,

         stained_glass:
             _edges[%]>=0, shading>=0, is_thin_separators={ 0 | 1 }

           Generate stained glass from selected images.

           Default values: 'edges=40%', 'shading=0.2' and
            'is_precise=0'.

           Example:
             [#1] image.jpg stained_glass 20%,1 cut 0,20

         stars:
             _density[%]>=0,_depth>=0,_size>0,_nb_branches>=1,0<=_thickness<=1,
               _smoothness[%]>=0,_R,_G,_B,_opacity

           Add random stars to selected images.

           Default values: 'density=10%', 'depth=1',
            'size=32', 'nb_branches=5', 'thickness=0.38',
            'smoothness=0.5', 'R=G=B=200' and 'opacity=1'.

           Example:
             [#1] image.jpg stars ,

         stencil:
             _radius[%]>=0,_smoothness>=0,_iterations>=0

           Apply stencil filter on selected images.

           Default values: 'radius=3', 'smoothness=1' and
            'iterations=8'.

           Example:
             [#1] image.jpg +norm stencil. 2,1,4 +mul rm[0]

         stencilbw:
             _edges>=0,_smoothness>=0

           Apply B&W stencil effect on selected images.

           Default values: 'edges=15' and 'smoothness=10'.

           Example:
             [#1] image.jpg +stencilbw 40,4

         stylize:
             [style_image],_fidelity_finest,_fidelity_coarsest,
               _fidelity_smoothness_finest>=0,_fidelity_smoothnes_coarsest>=0,
               0<=_fidelity_chroma<=1,_init_type,_init_resolution>=0,
               init_max_gradient>=0,_patch_size_analysis>0,_patch_size_synthesis>0,
               _patch_size_synthesis_final>0,_nb_matches_finest>=0,
               _nb_matches_coarsest>=0,_penalize_repetitions>=0,
               _matching_precision>=0,_scale_factor>1,_skip_finest_scales>=0,
               _"image_matching_command"

           Transfer colors and textures from specified style image to selected
       images,
            using a multi-scale patch-mathing algorithm.
           If instant display window[0] is opened, the steps of the image
       synthesis
           are displayed on it.
           'init_type' can be { 0:best-match | 1:identity | 2:randomized
           }.

           Default values: 'fidelity_finest=0.5',
            'fidelity_coarsest=2', 'fidelity_smoothness_finest=3',
            'fidelity_smoothness_coarsest=0.5', 'fidelity_chroma=0.1',
            'init_type=0', 'init_resolution=16',
            'init_max_gradient=0', 'patch_size_analysis=5',
            'patch_size_synthesis=5', 'patch_size_synthesis_final=5',
            'nb_matches_finest=2', 'nb_matchesc_coarsest=30',
            'penalize_repetitions=2', 'matching_precision=2',
            'scale_factor=1.85', 'skip_finest_scales=0' and
            'image_matching_command'="s c,-3 match_pca[0] [2] b[0,2] xy,0.7
       n[0,2]
            0,255 n[1,2] 0,200 a[0,1] c a[1,2] c"'.

         tetris:
             _scale>0

           Apply tetris effect on selected images.

           Default value: 'scale=10'.

           Example:
             [#1] image.jpg +tetris 10

         warhol:
             _M>0,_N>0,_smoothness>=0,_color>=0

           Create MxN Andy Warhol-like artwork from selected images.

           Default values: 'M=3', 'N=M', 'smoothness=2' and
            'color=20'.

           Example:
             [#1] image.jpg warhol 3,3,3,40

         weave:
             _density>=0,0<=_thickness<=100,0<=_shadow<=100,_shading>=0,
               _fibers_amplitude>=0,_fibers_smoothness>=0,_angle,
               -1<=_x_curvature<=1,-1<=_y_curvature<=1

           Apply weave effect to the selected images.
           'angle' can be { 0:0 deg. | 1:22.5 deg. | 2:45 deg. | 3:67.5 deg.
           }.

           Default values: 'density=6', 'thickness=65',
            'shadow=40', 'shading=0.5', 'fibers_amplitude=0',
            _'fibers_smoothness=0', 'angle=0' and 'curvature_x=curvature_y
            =0'

           Example:
             [#1] image.jpg weave ,

         whirls:
             _texture>=0,_smoothness>=0,_darkness>=0,_lightness>=0

           Add random whirl texture to selected images.

           Default values: 'texture=3', 'smoothness=6',
            'darkness=0.5' and 'lightness=1.8'.

           Example:
             [#1] image.jpg whirls ,

         11.17. Warpings
                --------

         deform:
             _amplitude>=0,_interpolation

           Apply random smooth deformation on selected images.
           'interpolation' can be { 0:none | 1:linear | 2:bicubic }.

           Default value: 'amplitude=10'.

           Example:
             [#1] image.jpg +deform[0] 10 +deform[0] 20

         euclidean2polar:
             _center_x[%],_center_y[%],_stretch_factor>0,_boundary_conditions={
               0:dirichlet | 1:neumann | 2:periodic | 3:mirror }

           Apply euclidean to polar transform on selected images.

           Default values: 'center_x=center_y=50%',
            'stretch_factor=1' and 'boundary_conditions=3'.

           Example:
             [#1] image.jpg +euclidean2polar ,

         equirectangular2nadirzenith:

           Transform selected equirectangular images to nadir/zenith
       rectilinear
           projections.

         fisheye:
             _center_x,_center_y,0<=_radius<=100,_amplitude>=0

           Apply fish-eye deformation on selected images.

           Default values: 'x=y=50', 'radius=50' and
            'amplitude=1.2'.

           Example:
             [#1] image.jpg +fisheye ,

         flower:
             _amplitude,_frequency,_offset_r[%],_angle,_center_x[%],_center_y[%],
               _boundary_conditions={ 0:dirichlet | 1:neumann | 2:periodic |
               3:mirror }

           Apply flower deformation on selected images.

           Default values: 'amplitude=30', 'frequency=6',
            'offset_r=0', 'angle=0', 'center_x=center_y=50%' and
            'boundary_conditions=3'.

           Example:
             [#1] image.jpg +flower ,

         kaleidoscope:
             _center_x[%],_center_y[%],_radius,_angle,_boundary_conditions={
               0:dirichlet | 1:neumann | 2:periodic | 3:mirror }

           Create kaleidoscope effect from selected images.

           Default values: 'center_x=center_y=50%', 'radius=100',
            'angle=30' and 'boundary_conditions=3'.

           Example:
             [#1] image.jpg kaleidoscope ,

         map_sphere:
             _width>0,_height>0,_radius,_dilation>0,_fading>=0,_fading_power>=0

           Map selected images on a sphere.

           Default values: 'width=height=512', 'radius=100',
            'dilation=0.5', 'fading=0' and 'fading_power=0.5'.

           Example:
             [#1] image.jpg map_sphere ,

         nadirzenith2equirectangular:

           Transform selected nadir/zenith rectilinear projections to
       equirectangular
           images.

         polar2euclidean:
             _center_x[%],_center_y[%],_stretch_factor>0,_boundary_conditions={
               0:dirichlet | 1:neumann | 2:periodic | 3:mirror }

           Apply euclidean to polar transform on selected images.

           Default values: 'center_x=center_y=50%',
            'stretch_factor=1' and 'boundary_conditions=3'.

           Example:
             [#1] image.jpg +euclidean2polar ,

         raindrops:
             _amplitude,_density>=0,_wavelength>=0,_merging_steps>=0

           Apply raindrops deformation on selected images.

           Default values: 'amplitude=80','density=0.1',
            'wavelength=1' and 'merging_steps=0'.

           Example:
             [#1] image.jpg +raindrops ,

         ripple:
             _amplitude,_bandwidth,_shape={ 0:block | 1:triangle | 2:sine |
       3:sine+ |
               4:random },_angle,_offset

           Apply ripple deformation on selected images.

           Default values: 'amplitude=10', 'bandwidth=10',
            'shape=2', 'angle=0' and 'offset=0'.

           Example:
             [#1] image.jpg +ripple ,

         rotoidoscope:
             _center_x[%],_center_y[%],_tiles>0,_smoothness[%]>=0,
               _boundary_conditions={ 0:dirichlet | 1:neumann | 2:periodic |
               3:mirror }

           Create rotational kaleidoscope effect from selected images.

           Default values: 'center_x=center_y=50%', 'tiles=10',
            'smoothness=1' and 'boundary_conditions=3'.

           Example:
             [#1] image.jpg +rotoidoscope ,

         spherize:
             _radius[%]>=0,_strength,_smoothness[%]>=0,_center_x[%],_center_y[%],
               _ratio_x/y>0,_angle,_interpolation

           Apply spherize effect on selected images.

           Default values: 'radius=50%', 'strength=1',
            'smoothness=0', 'center_x=center_y=50%',
            'ratio_x/y=1', 'angle=0' and 'interpolation=1'.

           Example:
             [#1] image.jpg grid 5%,5%,0,0,0.6,255 spherize ,

         symmetrize:
             _x[%],_y[%],_angle,_boundary_conditions={ 0:dirichlet | 1:neumann
       |
               2:periodic | 3:mirror },_is_antisymmetry={ 0 | 1
       },_swap_sides={ 0
               | 1 }

           Symmetrize selected images regarding specified axis.

           Default values: 'x=y=50%', 'angle=90',
            'boundary_conditions=3', 'is_antisymmetry=0' and
            'swap_sides=0'.

           Example:
             [#1] image.jpg +symmetrize 50%,50%,45 +symmetrize[-1] 50%,50%,-45

         transform_polar:
             "expr_radius",_"expr_angle",_center_x[%],_center_y[%],
               _boundary_conditions={ 0:dirichlet | 1:neumann | 2:periodic |
               3:mirror }

           Apply user-defined transform on polar representation of selected
       images.

           Default values: 'expr_radius=R-r', 'expr_rangle=a',
            'center_x=center_y=50%' and 'boundary_conditions=3'.

           Example:
             [#1] image.jpg +transform_polar[0] R*(r/R)^2,a
       +transform_polar[0] r,2*a

         twirl:
             _amplitude,_center_x[%],_center_y[%],_boundary_conditions={
       0:dirichlet |
               1:neumann | 2:periodic | 3:mirror }

           Apply twirl deformation on selected images.

           Default values: 'amplitude=1', 'center_x=center_y=50%'
            and 'boundary_conditions=3'.

           Example:
             [#1] image.jpg twirl 0.6

         warp (+):
             [warping_field],_mode,_interpolation,_boundary_conditions,_nb_frames>0

           Warp selected images with specified displacement field.
           'mode' can be { 0:backward-absolute | 1:backward-relative |
           2:forward-absolute | 3:forward-relative }.
           'interpolation' can be { 0:nearest-neighbor | 1:linear | 2:cubic
           }.
           'boundary_conditions' can be { 0:dirichlet | 1:neumann |
           2:periodic | 3:mirror }.

           Default values: 'mode=0', 'interpolation=1',
            'boundary_conditions=0' and 'nb_frames=1'.

           Example:
             [#1] image.jpg
       100%,100%,1,2,'X=x/w-0.5;Y=y/h-0.5;R=(X*X+Y*Y)^0.5;A=atan
              2(Y,X);130*R*(!c?cos(4*A):sin(8*A))' warp[-2] [-1],1,1,0
              quiver[-1] [-1],10,1,1,1,100

           Tutorial: https://gmic.eu/oldtutorial/_warp

         warp_patch:
             [warping_field],patch_width>=1,_patch_height>=1,_patch_depth>=1,
               _std_factor>0,_boundary_conditions.

           Patch-warp selected images, with specified 2D or 3D displacement
       field (in
           backward-absolute mode).
           Argument 'std_factor' sets the std of the gaussian weights for the
           patch overlap,
           equal to 'std = std_factor*patch_size'.
           'boundary_conditions' can be { 0:dirichlet | 1:neumann |
           2:periodic | 3:mirror }.

           Default values: 'std_factor=0.3' and
            'boundary_conditions=3'.

         warp_perspective:
             _x-angle,_y-angle,_zoom>0,_x-center,_y-
       center,_boundary_conditions={
               0:dirichlet | 1:neumann | 2:periodic | 3:mirror }

           Warp selected images with perspective deformation.

           Default values: 'x-angle=1.5', 'y-angle=0',
            'zoom=1', 'x-center=y-center=50' and
            'boundary_conditions=2'.

           Example:
             [#1] image.jpg warp_perspective ,

         warp_rbf:
             xs0[%],ys0[%],xt0[%],yt0[%],...,xsN[%],ysN[%],xtN[%],ytN[%]

           Warp selected images using RBF-based interpolation.
           Each argument (xsk,ysk)-(xtk,ytk) corresponds to the coordinates of
       a
           keypoint
           respectively on the source and target images. The set of all
       keypoints
           define the overall image deformation.

           Example:
             [#1] image.jpg +warp_rbf
       0,0,0,0,100%,0,100%,0,100%,100%,100%,100%,0,
              100%,0,100%,50%,50%,70%,50%,25%,25%,25%,75%

         water:
             _amplitude,_smoothness>=0,_angle

           Apply water deformation on selected images.

           Default values: 'amplitude=30', 'smoothness=1.5' and
            'angle=45'.

           Example:
             [#1] image.jpg water ,

         wave:
             _amplitude>=0,_frequency>=0,_center_x,_center_y

           Apply wave deformation on selected images.

           Default values: 'amplitude=4', 'frequency=0.4' and
            'center_x=center_y=50'.

           Example:
             [#1] image.jpg wave ,

         wind:
             _amplitude>=0,_angle,0<=_attenuation<=1,_threshold

           Apply wind effect on selected images.

           Default values: 'amplitude=20', 'angle=0',
            'attenuation=0.7' and 'threshold=20'.

           Example:
             [#1] image.jpg +wind ,

         zoom:
             _factor,_cx,_cy,_cz,_boundary_conditions={ 0:dirichlet |
       1:neumann |
               2:periodic | 3:mirror }

           Apply zoom factor to selected images.

           Default values: 'factor=1', 'cx=cy=cz=0.5' and
            'boundary_conditions=0'.

           Example:
             [#1] image.jpg +zoom[0] 0.6 +zoom[0] 1.5

         11.18. Degradations
                ------------

         cracks:
             0<=_density<=100,_is_relief={ 0 | 1 },_opacity,_color1,...

           Draw random cracks on selected images with specified color.

           Default values: 'density=25', 'is_relief=0',
            'opacity=1' and 'color1=0'.

           Example:
             [#1] image.jpg +cracks ,

         light_patch:
             _density>0,_darkness>=0,_lightness>=0

           Add light patches to selected images.

           Default values: 'density=10', 'darkness=0.9' and
            'lightness=1.7'.

           Example:
             [#1] image.jpg +light_patch 20,0.9,4

         noise_hurl:
             _amplitude>=0

           Add hurl noise to selected images.

           Default value: 'amplitude=10'.

           Example:
             [#1] image.jpg +noise_hurl ,

         pixelize:
             _scale_x>0,_scale_y>0,_scale_z>0

           Pixelize selected images with specified scales.

           Default values: 'scale_x=20' and 'scale_y=scale_z=scale_x
            '.

           Example:
             [#1] image.jpg +pixelize ,

         scanlines:
             _amplitude,_bandwidth,_shape={ 0:block | 1:triangle | 2:sine |
       3:sine+ |
               4:random },_angle,_offset

           Apply ripple deformation on selected images.

           Default values: 'amplitude=60', 'bandwidth=2',
            'shape=0', 'angle=0' and 'offset=0'.

           Example:
             [#1] image.jpg +scanlines ,

         shade_stripes:
             _frequency>=0,_direction={ 0:horizontal | 1:vertical
       },_darkness>=0,
               _lightness>=0

           Add shade stripes to selected images.

           Default values: 'frequency=5', 'direction=1',
            'darkness=0.8' and 'lightness=2'.

           Example:
             [#1] image.jpg +shade_stripes 30

         shadow_patch:
             _opacity>=0

           Add shadow patches to selected images.

           Default value: 'opacity=0.7'.

           Example:
             [#1] image.jpg +shadow_patch 0.4

         spread:
             _dx>=0,_dy>=0,_dz>=0

           Spread pixel values of selected images randomly along x,y and z.

           Default values: 'dx=3', 'dy=dx' and 'dz=0'.

           Example:
             [#1] image.jpg +spread 3

         stripes_y:
             _frequency>=0

           Add vertical stripes to selected images.

           Default value: 'frequency=10'.

           Example:
             [#1] image.jpg +stripes_y ,

         texturize_canvas:
             _amplitude>=0,_fibrousness>=0,_emboss_level>=0

           Add paint canvas texture to selected images.

           Default values: 'amplitude=20', 'fibrousness=3' and
            'emboss_level=0.6'.

           Example:
             [#1] image.jpg +texturize_canvas ,

         texturize_paper:

           Add paper texture to selected images.

           Example:
             [#1] image.jpg +texturize_paper

         vignette:
             _strength>=0,0<=_radius_min<=100,0<=_radius_max<=100

           Add vignette effect to selected images.

           Default values: 'strength=100', 'radius_min=70' and
            'radius_max=90'.

           Example:
             [#1] image.jpg vignette ,

         watermark_visible:
             _text,0<_opacity<1,_{ size>0 | font },_angle,_mode={ 0:remove |
       1:add },
               _smoothness>=0

           Add or remove a visible watermark on selected images (value range
       must be
           [0,255]).

           Default values: 'text=(c) G'MIC', 'opacity=0.3',
            'size=53', 'angle=25', 'mode=1' and
            'smoothness=0'.

           Example:
             [#1] image.jpg watermark_visible ,0.7

         11.19. Blending and Fading
                -------------------

         blend:
             [layer],blending_mode,_opacity[%],_selection_is={ 0:base-layers |
               1:top-layers } |
             blending_mode,_opacity[%]

           Blend selected G,GA,RGB or RGBA images by specified layer or blend
       all
           selected images together,
           using specified blending mode.
           'blending_mode' can be { add | alpha | and | average | blue | burn
       |
           darken | difference |
           divide | dodge | edges | exclusion | freeze | grainextract |
       grainmerge |
           green | hardlight |
           hardmix | hue | interpolation | lchlightness | lighten | lightness
       |
           linearburn | linearlight | luminance |
           multiply | negation | or | overlay | pinlight | red | reflect |
       saturation
           |
           screen | seamless | seamless_mixed | shapeareamax | shapeareamax0 |
           shapeareamin | shapeareamin0 |
           shapeaverage | shapeaverage0 | shapemedian | shapemedian0 |
       shapemin |
           shapemin0 | shapemax | shapemax0 |
           shapeprevalent | softburn | softdodge | softlight | stamp |
       subtract |
           value | vividlight | xor }.
           'opacity' must be in range '[0,1]' (or '[0%,100%]').

           Default values: 'blending_mode=alpha', 'opacity=1' and
            'selection_is=0'.

           Example:
             [#1] image.jpg +drop_shadow , rescale2d[-1] ,200 rotate[-1] 20
       +blend
              alpha display_rgba[-2]
             [#2] image.jpg testimage2d {w},{h} blend overlay
             [#3] command "ex : $""=arg repeat $""# +blend[0,1] ${arg{$>+1}}
              text_outline[-1] Mode:
              image.jpg testimage2d {w},{h} ex add,alpha,and,average,blue,
              burn,darken
             [#4] command "ex : $""=arg repeat $""# +blend[0,1] ${arg{$>+1}}
              text_outline[-1] Mode:
              image.jpg testimage2d {w},{h} ex difference,divide,dodge,
              exclusion,freeze,grainextract,grainmerge
             [#5] command "ex : $""=arg repeat $""# +blend[0,1] ${arg{$>+1}}
              text_outline[-1] Mode:
              image.jpg testimage2d {w},{h} ex green,hardlight,hardmix,hue,
              interpolation,lighten,lightness
             [#6] command "ex : $""=arg repeat $""# +blend[0,1] ${arg{$>+1}}
              text_outline[-1] Mode:
              image.jpg testimage2d {w},{h} ex linearburn,linearlight,
              luminance,multiply,negation,or,overlay
             [#7] command "ex : $""=arg repeat $""# +blend[0,1] ${arg{$>+1}}
              text_outline[-1] Mode:
              image.jpg testimage2d {w},{h} ex pinlight,red,reflect,
              saturation,screen,shapeaverage,softburn
             [#8] command "ex : $""=arg repeat $""# +blend[0,1] ${arg{$>+1}}
              text_outline[-1] Mode:
              image.jpg testimage2d {w},{h} ex softdodge,softlight,stamp,
              subtract,value,vividlight,xor

         blend_edges:
             smoothness[%]>=0

           Blend selected images togethers using 'edges' mode.

           Example:
             [#1] image.jpg testimage2d {w},{h} +blend_edges 0.8

         blend_fade:
             [fading_shape]

           Blend selected images together using specified fading shape.

           Example:
             [#1] image.jpg testimage2d {w},{h} 100%,100%,1,1,'cos(y/10)'
              normalize[-1] 0,1 +blend_fade[0,1] [2]

         blend_median:

           Blend selected images together using 'median' mode.

           Example:
             [#1] image.jpg testimage2d {w},{h} +mirror[0] y +blend_median

         blend_seamless:
             _is_mixed_mode={ 0 | 1 },_inner_fading[%]>=0,_outer_fading[%]>=0

           Blend selected images using a seamless blending mode (Poisson-
       based).

           Default values: 'is_mixed=0', 'inner_fading=0' and
            'outer_fading=100%'.

         fade_diamond:
             0<=_start<=100,0<=_end<=100

           Create diamond fading from selected images.

           Default values: 'start=80' and 'end=90'.

           Example:
             [#1] image.jpg testimage2d {w},{h} +fade_diamond 80,85

         fade_linear:
             _angle,0<=_start<=100,0<=_end<=100

           Create linear fading from selected images.

           Default values: 'angle=45', 'start=30' and
            'end=70'.

           Example:
             [#1] image.jpg testimage2d {w},{h} +fade_linear 45,48,52

         fade_radial:
             0<=_start<=100,0<=_end<=100

           Create radial fading from selected images.

           Default values: 'start=30' and 'end=70'.

           Example:
             [#1] image.jpg testimage2d {w},{h} +fade_radial 30,70

         fade_x:
             0<=_start<=100,0<=_end<=100

           Create horizontal fading from selected images.

           Default values: 'start=30' and 'end=70'.

           Example:
             [#1] image.jpg testimage2d {w},{h} +fade_x 30,70

         fade_y:
             0<=_start<=100,0<=_end<=100

           Create vertical fading from selected images.

           Default values: 'start=30' and 'end=70'.

           Example:
             [#1] image.jpg testimage2d {w},{h} +fade_y 30,70

         fade_z:
             0<=_start<=100,0<=_end<=100

           Create transversal fading from selected images.

           Default values: 'start=30' and 'end=70'.

         sub_alpha:
             [base_image],0<=_minimize_alpha<=1

           Compute the alpha-channel difference (opposite of alpha blending)
       between
           the selected images
           and the specified base image.
           The alpha difference A-B is defined as the image having 'minimal'
           opacity, such that alpha_blend(B,A-B) = A.
           The 'min_alpha' argument is used to relax the alpha minimality
           constraint. When set to '1', alpha is constrained to be minimal.
       When
           set to '0', alpha is maximal (i.e. '255').

           Default value: 'minimize_alpha=1'.

           Example:
             [#1] image.jpg testimage2d {w},{h} +sub_alpha[0] [1] display_rgba

         11.20. Image Sequences and Videos
                --------------------------

         animate:
             filter_name,"param1_start,...,paramN_start","param1_end,...,paramN_end",
               nb_frames>=0,_output_frames={ 0 | 1 },_output_filename |
             delay>0,_back and forth={ 0 | 1 }

           Animate filter from starting parameters to ending parameters or
       animate
           selected images
           in a display window.

           Default value: 'delay=30'.

           Example:
             [#1] image.jpg animate flower,"0,3","20,8",9

         apply_camera:
             _"command",_camera_index>=0,_skip_frames>=0,_output_filename

           Apply specified command on live camera stream, and display it on
       display
           window [0].
           This command requires features from the OpenCV library (not enabled
       in
           G'MIC by default).

           Default values: 'command=""', 'camera_index=0' (default
            camera), 'skip_frames=0' and 'output_filename=""'.

         apply_files:
             "filename_pattern",_"command",_first_frame>=0,_last_frame={ >=0 |
       -1=last
               },_frame_step>=1,_output_filename

           Apply a G'MIC command on specified input image files, in a streamed
       way.
           If a display window is opened, rendered frames are displayed in it
       during
           processing.
           The output filename may have extension '.avi' or '.mp4' (saved
           as a video), or any other usual image file
           extension (saved as a sequence of images).

           Default values: 'command=(undefined)', 'first_frame=0',
            'last_frame=-1', 'frame_step=1' and
            'output_filename=(undefined)'.

         apply_video:
             video_filename,_"command",_first_frame>=0,_last_frame={ >=0 |
       -1=last },
               _frame_step>=1,_output_filename

           Apply a G'MIC command on all frames of the specified input video
       file, in
           a streamed way.
           If a display window is opened, rendered frames are displayed in it
       during
           processing.
           The output filename may have extension '.avi' or '.mp4' (saved
           as a video), or any other usual image
           file extension (saved as a sequence of images).
           This command requires features from the OpenCV library (not enabled
       in
           G'MIC by default).

           Default values: 'first_frame=0', 'last_frame=-1',
            'frame_step=1' and 'output_filename=(undefined)'.

         average_files:
             "filename_pattern",_first_frame>=0,_last_frame={ >=0 | -1=last },
               _frame_step>=1,_output_filename

           Average specified input image files, in a streamed way.
           If a display window is opened, rendered frames are displayed in it
       during
           processing.
           The output filename may have extension '.avi' or '.mp4' (saved
           as a video), or any other usual image
           file extension (saved as a sequence of images).

           Default values: 'first_frame=0', 'last_frame=-1',
            'frame_step=1' and 'output_filename=(undefined)'.

         average_video:
             video_filename,_first_frame>=0,_last_frame={ >=0 | -1=last },
               _frame_step>=1,_output_filename

           Average frames of specified input video file, in a streamed way.
           If a display window is opened, rendered frames are displayed in it
       during
           processing.
           The output filename may have extension '.avi' or '.mp4' (saved
           as a video), or any other usual image
           file extension (saved as a sequence of images).
           This command requires features from the OpenCV library (not enabled
       in
           G'MIC by default).

           Default values: 'first_frame=0', 'last_frame=-1',
            'frame_step=1' and 'output_filename=(undefined)'.

         fade_files:
             "filename_pattern",_nb_inner_frames>0,_first_frame>=0,_last_frame={
       >=0 |
               -1=last },_frame_step>=1,_output_filename

           Generate a temporal fading from specified input image files, in a
       streamed
           way.
           If a display window is opened, rendered frames are displayed in it
       during
           processing.
           The output filename may have extension 'avi' or 'mp4' (saved
           as a video), or any other usual image
           file extension (saved as a sequence of images).

           Default values: 'nb_inner_frames=10', 'first_frame=0',
            'last_frame=-1', 'frame_step=1' and
            'output_filename=(undefined)'.

         fade_video:
             video_filename,_nb_inner_frames>0,_first_frame>=0,_last_frame={
       >=0 |
               -1=last },_frame_step>=1,_output_filename

           Create a temporal fading sequence from specified input video file,
       in a
           streamed way.
           If a display window is opened, rendered frames are displayed in it
       during
           processing.
           This command requires features from the OpenCV library (not enabled
       in
           G'MIC by default).

           Default values: 'nb_inner_frames=10', 'first_frame=0',
            'last_frame=-1', 'frame_step=1' and
            'output_filename=(undefined)'.

         files2video:
             "filename_pattern",_output_filename,_fps>0,_codec

           Convert several files into a single video file.

           Default values: 'output_filename=output.mp4', 'fps=25'
            and 'codec=mp4v'.

         median_files:
             "filename_pattern",_first_frame>=0,_last_frame={ >=0 | -1=last },
               _frame_step>=1,_frame_rows[%]>=1,_is_fast_approximation={ 0 | 1
       }

           Compute the median frame of specified input image files, in a
       streamed way.
           If a display window is opened, rendered frame is displayed in it
       during
           processing.

           Default values: 'first_frame=0', 'last_frame=-1',
            'frame_step=1', 'frame_rows=20%' and
            'is_fast_approximation=0'.

         median_video:
             video_filename,_first_frame>=0,_last_frame={ >=0 | -1=last },
               _frame_step>=1,_frame_rows[%]>=1,_is_fast_approximation={ 0 | 1
       }

           Compute the median of all frames of an input video file, in a
       streamed way.
           If a display window is opened, rendered frame is displayed in it
       during
           processing.
           This command requires features from the OpenCV library (not enabled
       in
           G'MIC by default).

           Default values: 'first_frame=0', 'last_frame=-1',
            'frame_step=1', 'frame_rows=100%' and
            'is_fast_approximation=1'.

         morph:
             nb_inner_frames>=1,_smoothness>=0,_precision>=0

           Create morphing sequence between selected images.

           Default values: 'smoothness=0.1' and 'precision=4'.

           Example:
             [#1] image.jpg +rotate 20,1,1,50%,50% morph 9

         morph_files:
             "filename_pattern",_nb_inner_frames>0,_smoothness>=0,_precision>=0,
               _first_frame>=0,_last_frame={ >=0 | -1=last },_frame_step>=1,
               _output_filename

           Generate a temporal morphing from specified input image files, in a
           streamed way.
           If a display window is opened, rendered frames are displayed in it
       during
           processing.
           The output filename may have extension '.avi' or '.mp4' (saved
           as a video), or any other usual image
           file extension (saved as a sequence of images).

           Default values: 'nb_inner_frames=10', 'smoothness=0.1',
            'precision=4', 'first_frame=0', 'last_frame=-1',
            'frame_step=1' and 'output_filename=(undefined)'.

         morph_rbf:
             nb_inner_frames>=1,xs0[%],ys0[%],xt0[%],yt0[%],...,xsN[%],ysN[%],xtN[%],
               ytN[%]

           Create morphing sequence between selected images, using RBF-based
           interpolation.
           Each argument (xsk,ysk)-(xtk,ytk) corresponds to the coordinates of
       a
           keypoint
           respectively on the source and target images. The set of all
       keypoints
           define the overall image deformation.

         morph_video:
             video_filename,_nb_inner_frames>0,_smoothness>=0,_precision>=0,
               _first_frame>=0,_last_frame={ >=0 | -1=last },_frame_step>=1,
               _output_filename

           Generate a temporal morphing from specified input video file, in a
           streamed way.
           If a display window is opened, rendered frames are displayed in it
       during
           processing.
           The output filename may have extension '.avi' or '.mp4' (saved
           as a video), or any other usual image
           file extension (saved as a sequence of images).
           This command requires features from the OpenCV library (not enabled
       in
           G'MIC by default).

           Default values: 'nb_inner_frames=10', 'smoothness=0.1',
            'precision=4', 'first_frame=0', 'last_frame=-1',
            'frame_step=1' and 'output_filename=(undefined)'.

         register_nonrigid:
             [destination],_smoothness>=0,_precision>0,_nb_scale>=0

           Register selected source images with specified destination image,
       using
           non-rigid warp.

           Default values: 'smoothness=0.2', 'precision=6' and
            'nb_scale=0(auto)'.

           Example:
             [#1] image.jpg +rotate 20,1,1,50%,50% +register_nonrigid[0] [1]

         register_rigid:
             [destination],_smoothness>=0,_boundary_conditions={ 0:dirichlet |
               1:neumann | 2:periodic | 3:mirror }

           Register selected source images with specified destination image,
       using
           rigid warp (shift).

           Default values: 'smoothness=0.1%' and
            'boundary_conditions=0'.

           Example:
             [#1] image.jpg +shift 30,20 +register_rigid[0] [1]

         transition:
             [transition_shape],nb_added_frames>=0,100>=shading>=0,_single_frame_only={
               -1=disabled | >=0 }

           Generate a transition sequence between selected images.

           Default values: 'shading=0' and 'single_frame_only=-1'.

           Example:
             [#1] image.jpg +mirror c 100%,100% plasma[-1] 1,1,6
       transition[0,1] [2],
              5

         transition3d:
             _nb_frames>=2,_nb_xtiles>0,_nb_ytiles>0,_axis_x,_axis_y,_axis_z,
               _is_antialias={ 0 | 1 }

           Create 3D transition sequence between selected consecutive images.
           'axis_x', 'axis_y' and 'axis_z' can be set as
           mathematical expressions, depending on 'x' and 'y'.

           Default values: 'nb_frames=10', 'nb_xtiles=nb_ytiles=3',
            'axis_x=1', 'axis_y=1', 'axis_z=0' and
            'is_antialias=1'.

           Example:
             [#1] image.jpg +blur 5 transition3d 9 display_rgba

         video2files:
             input_filename,_output_filename,_first_frame>=0,_last_frame={ >=0
       |
               -1=last },_frame_step>=1

           Split specified input video file into image files, one for each
       frame.
           First and last frames as well as step between frames can be
       specified.

           Default values: 'output_filename=frame.png',
            'first_frame=0', 'last_frame=-1' and 'frame_step=1'.

         11.21. Convenience Functions
                ---------------------

         add_copymark:

           Add copymark suffix in names of selected images.

         alert:
             _title,_message,_label_button1,_label_button2,...

           Display an alert box and wait for user's choice.
           If a single image is in the selection, it is used as an icon for
       the alert
           box.

           Default values: 'title=[G'MIC Alert]' and 'message=This is an alert
            box.'.

         arg:
             n>=1,_arg1,...,_argN

           Return the n-th argument of the specified argument list.

         arg0:
             n>=0,_arg0,...,_argN

           Return the n-th argument of the specified argument list (where 'n'
           starts from '0').

         arg2img:
             argument_1,...,argument_N

           Split specified list of arguments and return each as a new image
       (as a
           null-terminated string).

         arg2var:
             variable_name,argument_1,...,argument_N

           For each i in [1...N], set 'variable_name$i=argument_i'.
           The variable name should be global to make this command useful
       (i.e.
           starts by an underscore).

         autocrop_coords:
             value1,value2,... | auto

           Return coordinates (x0,y0,z0,x1,y1,z1) of the autocrop that could
       be
           performed on the latest
           of the selected images.

           Default value: 'auto'

         average_vectors:

           Return the vector-valued average of the latest of the selected
       images.

         base642img:
             "base64_string"

           Decode given base64-encoded string as a newly inserted image at the
       end of
           the list.
           The argument string must have been generated using command
           'img2base64'.

         base642uint8:
             "base64_string"

           Decode given base64-encoded string as a newly inserted 1-column
       image at
           the end of the list.
           The argument string must have been generated using command
           'uint82base64'.

         basename:
             file_path,_variable_name_for_folder

           Return the basename of a file path, and opt. its folder location.
           When specified 'variable_name_for_folder' must starts by an
           underscore
           (global variable accessible from calling function).

         bin:
             binary_int1,...

           Print specified binary integers into their octal, decimal,
       hexadecimal and
           string representations.

         bin2dec:
             binary_int1,...

           Convert specified binary integers into their decimal
       representations.

         cat:
             filename,_display_line_numbers={ 0 | 1 },_line_selection,

           Print specified line selection of given filename on stdout.

           Default values: 'display_line_numbers=1' and
            'line_selection=^'.

         color2name:
             R,G,B

           Return the name (as a string, in English) that most matches the
       specified
           color.

         covariance_vectors:
             _avg_outvarname

           Return the covariance matrix of the vector-valued colors in the
       latest of
           the selected images
           (for arbitrary number of channels).
           Parameter 'avg_outvarname' is used as a variable name that takes
       the
           value of the average vector-value.

         da_freeze:

           Convert each of the selected dynamic arrays into a 1-column image
       whose
           height is the number of array elements.

         dec:
             decimal_int1,...

           Print specified decimal integers into their binary, octal,
       hexadecimal and
           string representations.

         dec2str:
             decimal_int1,...

           Convert specifial decimal integers into its string representation.

         dec2bin:
             decimal_int1,...

           Convert specified decimal integers into their binary
       representations.

         dec2hex:
             decimal_int1,...

           Convert specified decimal integers into their hexadecimal
       representations.

         dec2oct:
             decimal_int1,...

           Convert specified decimal integers into their octal
       representations.

         fibonacci:
             N>=0

           Return the Nth number of the Fibonacci sequence.

           Example:
             [#1] echo ${"fibonacci 10"}


             [gmic]-0./ Start G'MIC interpreter.
             [gmic]-0./ 55
             [gmic]-0./ End G'MIC interpreter.

         file_mv:
             filename_src,filename_dest

           Rename or move a file from a location $1 to another location $2.

         filename:
             filename,_number1,_number2,...,_numberN

           Return a filename numbered with specified indices.

         filename_rand:

           Return a random filename for storing temporary data.

         filename_dated:
             filename

           Convert specified filename to one stamped with the current date
           ('filename_YYYYMMDD_HHMMSS.ext').

         files (+):
             _mode,path

           Return the list of files and/or subfolders from specified path.
           'path' can be eventually a matching pattern.
           'mode' can be { 0:files only | 1:folders only | 2:files + folders
           }.
           Add '3' to 'mode' to return full paths instead of filenames
           only.

           Default value: 'mode=5'.

         files2img:
             _mode,path

           Insert a new image where each vector-valued pixel is a string
       encoding the
           filenames returned by command files.
           Useful to manage list of filenames containing characters that have
       a
           special meaning in the G'MIC language,such as spaces or commas.

         fitratio_wh:
             min_width,min_height,ratio_wh

           Return a 2D size 'width,height' which is bigger than 'min_width,
           min_height' and has the specified w/h ratio.

         fitscreen:
             width,height,_depth,_minimal_size[%],_maximal_size[%] |
             [image],_minimal_size[%],_maximal_size[%]

           Return the 'ideal' size WxH for a window intended to display an
           image of specified size on screen.

           Default values: 'depth=1', 'minimal_size=128' and
            'maximal_size=85%'.

         fontchart:
             display_mode.

           Insert G'MIC font chart at the end of the image list.
           'display_mode' can be { 0: List of characters | N: List of fonts
           with height 'N'}.

           Default value: 'display_mode=0'.

           Example:
             [#1] fontchart 0 fontchart 64

         fps:

           Return the number of time this function is called per second, or -1
       if
           this info is not yet available.
           Useful to display the framerate when displaying animations.

         hex:
             hexadecimal_int1,...

           Print specified hexadecimal integers into their binary, octal,
       decimal and
           string representations.

         hex2dec:
             hexadecimal_int1,...

           Convert specified hexadecimal integers into their decimal
       representations.

         hex2img:
             "hexadecimal_string"

           Insert new image 1xN at the end of the list with values specified
       by the
           given hexadecimal-encoded string.

         hex2str:
             hexadecimal_string

           Convert specified hexadecimal string into a string.
           See also: str2hex.

         img2base64:
             _encoding={ 0:base64 | 1:base64url },_store_names={ 0 | 1 }

           Encode selected images as a base64-encoded string.
           The images can be then decoded using command 'base642img'.

           Default values: 'encoding=0' and 'store_names=1'.

         img2hex:

           Return representation of last image as an hexadecimal-encoded
       string.
           Input image must have values that are integers in [0,255].

         img2str:

           Return the content of the selected images, as special G'MIC input
       strings.

         img2text:
             _line_separator

           Return text contained in a multi-line image.

           Default value: 'line_separator= '.

         is_mesh3d:

           Return 1 if all of the selected images are 3D meshes, 0 otherwise.

         is_change:
             _value={ 0:false | 1:true }

           Set or unset the 'is_change' flag associated to the image list.
           This flag tells the interpreter whether or not the image list
       should be
           displayed when the pipeline ends.

           Default value: 'value=1'.

         is_half:

           Return 1 if the type of image pixels is limited to half-float.

         is_ext:
             filename,_extension

           Return 1 if specified filename has a given extension.

         is_image_arg:
             string

           Return 1 if specified string looks like '[ind]'.

         is_pattern:
             string

           Return 1 if specified string looks like a drawing pattern
       '0x......'.

         is_varname:
             string

           Return 1 if specified string can be considered as a valid variable
       name.

         is_videofilename:
             filename

           Return 1 if extension of specified filename is typical from video
       files.

         is_macos:

           Return 1 if current computer OS is Darwin (MacOS), 0 otherwise.

         is_windows:

           Return 1 if current computer OS is Windows, 0 otherwise.

         lof:
             feature

           Return the list of specified features (separated by commas) for
       each
           selected images.

         math_lib:

           Return string that defines a set of several useful macros for the
       embedded
           math evaluator.

         mad:

           Return the MAD (Maximum Absolute Deviation) of the last selected
       image.
           The MAD is defined as MAD = med_i|x_i-med_j(x_j)|

         max_w:

           Return the maximal width between selected images.

         max_h:

           Return the maximal height between selected images.

         max_d:

           Return the maximal depth between selected images.

         max_s:

           Return the maximal spectrum between selected images.

         max_wh:

           Return the maximal wxh size of selected images.

         max_whd:

           Return the maximal wxhxd size of selected images.

         max_whds:

           Return the maximal wxhxdxs size of selected images.

         median_vectors:

           Return the median vector value of the last selected image (median
       computed
           channel by channel)

         min_w:

           Return the minimal width between selected images.

         min_h:

           Return the minimal height between selected images.

         min_d:

           Return the minimal depth between selected images.

         min_s:

           Return the minimal s size of selected images.

         min_wh:

           Return the minimal wxh size of selected images.

         min_whd:

           Return the minimal wxhxd size of selected images.

         min_whds:

           Return the minimal wxhxdxs size of selected images.

         name2color:
             name

           Return the R,G,B color that matches the specified color name.

         nmd (+):
             Shortcut for command 'named'.

         named (+):
             _mode,"name1","name2",...

           Return the set of indices corresponding to images of the selection
       with
           specified names.
           After this command returns, the status contains a list of indices
           (unsigned integers),
           separated by commas (or an empty string if no images with those
       names have
           been found).
           (equivalent to shortcut command 'nmd').

           'mode' can be { 0:all indices (default) | 1:lowest index |
           2:highest index | 3:all indices (case insensitive) | 4:lowest index
       (case
           insensitive) | 5:highest index (case insensitive)}

         narg:
             arg1,arg2,...,argN

           Return number of specified arguments.

         normalize_filename:
             filename

           Return a "normalized" version of the specified filename, without
       spaces
           and capital letters.

         oct:
             octal_int1,...

           Print specified octal integers into their binary, decimal,
       hexadecimal and
           string representations.

         oct2dec:
             octal_int1,...

           Convert specified octal integers into their decimal
       representations.

         padint:
             number,_size>0

           Return a integer with 'size' digits (eventually left-padded with
           '0').

         path_cache:

           Return a path to store G'MIC data files for one user (whose value
       is
           OS-dependent).

         path_current:

           Return current folder from where G'MIC has been run.

         path_gimp:

           Return a path to store GIMP configuration files for one user (whose
       value
           is OS-dependent).

         path_tmp:

           Return a path to store temporary files (whose value is OS-
       dependent).

         remove_copymark:

           Remove copymark suffix in names of selected images.

         reset:

           Reset global parameters of the interpreter environment.

         rgb:

           Return a random int-valued RGB color.

         rgba:

           Return a random int-valued RGBA color.

         shell_cols:

           Return the estimated number of columns of the current shell.

         size_value:

           Return the size (in bytes) of image values.

         std_noise:

           Return the estimated noise standard deviation of the last selected
       image.

         str:
             string

           Print specified string into its binary, octal, decimal and
       hexadecimal
           representations.

         strbuffer:
             buffer_size

           Return a string describing a size for the specified buffer size.

         str2hex:
             "string"

           Convert specified string argument into a sequence of hexadecimal
       values
           (returned as a string).
           See also: hex2str.

           Example:
             [#1] hex=${"str2hex


             [gmic]-0./ Start G'MIC interpreter.
             [gmic]-0./ 48656c6c6f206d7920667269656e6473
             [gmic]-0./ End G'MIC interpreter.

         strcapitalize:
             string

           Capitalize specified string.

         strcontains:
             string1,string2

           Return 1 if the first string contains the second one.

         strclut:
             "string"

           Return simplified version of the specified string that can be used
       as a
           CLUT name.

         strlen:
             string1

           Return the length of specified string argument.

         strreplace:
             string,search,replace

           Search and replace substrings in an input string.

         strlowercase:
             string

           Return a lower-case version of the specified string.

         struppercase:
             string

           Return an upper-case version of the specified string.

         strvar:
             "string"

           Return a simplified version of the specified string, that can be
       used as a
           variable name.
           (version that creates a lowercase result, no longer than 128
       chars).

         strcasevar:
             "string"

           Return a simplified version of the specified string, that can be
       used as a
           variable name.
           (version that keeps original case of specified string, no longer
       than 128
           chars).

         strver:
             _version,_prerelease

           Return the specified version number of the G'MIC interpreter, as a
       string.

           Default value: 'version=$_version' and 'prerelease='.

         tic:

           Initialize tic-toc timer.
           Use it in conjunction with 'toc'.

         toc:

           Display elapsed time of the tic-toc timer since the last call to
           'tic'.
           This command returns the elapsed time in the status value.
           Use it in conjunction with 'tic'.

         uint82base64:
             _encoding={ 0:base64 | 1:base64url }

           Encode the values of the latest of the selected images as a
       base64-encoded
           string.
           The string can be decoded using command 'base642uint8'.
           Selected images must have values that are integers in [0,255].

           Default values: 'encoding=0'.

         11.22. Other Interactive Commands
                --------------------------

         demos:
             _run_in_parallel={ 0:no | 1:yes | 2:auto }

           Show a menu to select and view all G'MIC interactive demos.

         tixy:
             "expression"

           Animate specified mathematical expression with a 16x16 grid of
       circles,
           using the rules described at https://tixy.land.

         x_2048:

           Launch the 2048 game.

         x_blobs:

           Launch the blobs editor.
           ../img/x_blobs.jpg [image: 'x_blobs']

         x_bouncing:

           Launch the bouncing balls demo.

         x_color_curves:
             _colorspace={ rgb | cmy | cmyk | hsi | hsl | hsv | lab | lch |
       ycbcr |
               last }

           Apply color curves on selected RGB[A] images, using an interactive
       window.
           Set 'colorspace' to 'last' to apply last defined color curves
           without opening interactive windows.

           Default value: 'colorspace=rgb'.

         x_colorize:
             _is_lineart={ 0 | 1 },_max_resolution={ 0 | >=128 },
               _multichannels_output={ 0 | 1
       },_[palette1],_[palette2],_[grabber1]

           Colorized selected B&W images, using an interactive window.
           When >0, argument 'max_resolution' defines the maximal image
           resolution used in the interactive window.

           Default values: 'is_lineart=1', 'max_resolution=1024'
            and 'multichannels_output=0'.

         x_connect4:

           Launch the Connect Four game.

         xz:
             Shortcut for command 'x_crop'.

         x_crop:

           Crop selected images interactively.
           If multiple input images are selected, the same crop is applied to
       all
           images.
           (equivalent to shortcut command 'xz').

         x_cut:

           Cut selected images interactively.

         x_fire:

           Launch the fire effect demo.

         x_fireworks:

           Launch the fireworks demo.

         x_fisheye:

           Launch the fish-eye effect demo.

         x_fourier:

           Launch the fourier filtering demo.

         x_grab_color:
             _variable_name

           Open a color grabber widget from the first selected image.
           Argument 'variable_name' specifies the variable that contains the
           selected color values at any time.
           Assigning '-1' to it forces the interactive window to close.

           Default values: 'variable_name=xgc_variable'.

         x_hanoi:

           Launch the Tower of Hanoi game.

         x_histogram:

           Launch the histogram demo.

         x_hough:

           Launch the hough transform demo.

         x_jawbreaker:
             0<_width<20,0<_height<20,0<_balls<=8

           Launch the Jawbreaker game.

         x_landscape:

           Launch the virtual landscape demo.

         x_life:

           Launch the game of life.

         x_light:

           Launch the light effect demo.

         x_mandelbrot:
             _julia={ 0 | 1 },_c0r,_c0i

           Launch Mandelbrot/Julia explorer.

         x_mask_color:
             _colorspace={ all | rgb | lrgb | ycbcr | lab | lch | hsv | hsi |
       hsl | cmy
               | cmyk | yiq },_spatial_tolerance>=0,_color_tolerance>=0

           Interactively select a color, and add an alpha channel containing
       the
           corresponding color mask.
           Argument 'colorspace' refers to the color metric used to compute
           color similarities, and can be basically
           one of { rgb | lrgb | ycbcr | lab | lch | hsv | hsi | hsl | cmy |
       cmyk
           | yiq }.
           You can also select one one particular channel of this colorspace,
       by
           setting 'colorspace' as
           'colorspace_channel' (e.g. 'hsv_h' for the hue).

           Default values: 'colorspace=all', 'spatial_tolerance=5'
            and 'color_tolerance=5'.

         x_metaballs3d:

           Launch the 3D metaballs demo.

         x_minesweeper:
             8<=_width=<20,8<=_height<=20

           Launch the Minesweeper game.

         x_minimal_path:

           Launch the minimal path demo.

         x_morph:
             _nb_frames>=2,_preview_fidelity={ 0:coarsest | 1:coarse |
       2:normal |
               3:fine | 4:finest }

           Launch the interactive image morpher.

           Default values: 'nb_frames=16' and 'preview_fidelity=3'.

         x_pacman:

           Launch pacman game.

         x_paint:

           Launch the interactive painter.

         x_plasma:

           Launch the plasma effect demo.

         x_quantize_rgb:
             _nbcolors>=2

           Launch the RGB color quantization demo.

         x_reflection3d:

           Launch the 3D reflection demo.

         x_rubber3d:

           Launch the 3D rubber object demo.

         x_segment:
             _max_resolution={ 0 | >=128 }

           Segment foreground from background in selected opaque RGB images,
           interactively.
           Return RGBA images with binary alpha-channels.

           Default value: 'max_resolution=1024'.

         x_select_color:
             _variable_name

           Display a RGB or RGBA color selector.
           Argument 'variable_name' specifies the variable that contains the
           selected color values (as R,G,B,[A])
           at any time.
           Its value specifies the initial selected color. Assigning '-1' to
       it
           forces the interactive window to close.

           Default value: 'variable_name=xsc_variable'.

         x_select_function1d:
             _variable_name,_background_curve_R,_background_curve_G,_background_curve_B

           Open an interactive window, where the user can defined its own 1D
       function.
           If an image is selected, it is used to display additional
       information :
              -  The first row defines the values of a background curve
       displayed on
           the window (e.g. an histogram).
              -  The 2nd, 3rd and 4th rows define the R,G,B color components
           displayed beside the X and Y axes.
           Argument 'variable_name' specifies the variable that contains the
           selected function keypoints at any time.
           Assigning '-1' to it forces the interactive window to close.

           Default values: 'variable_name=xsf_variable',
            'background_curve_R=220', 'background_curve_G=background_curve
            _B=background_curve_T'.

         x_select_palette:
             _variable_name,_number_of_columns={ 0:auto | >0 }

           Open a RGB or RGBA color selector widget from a palette.
           The palette is given as a selected image.
           Argument 'variable_name' specifies the variable that contains the
           selected color values (as R,G,B,[A])
           at any time.
           Assigning '-1' to it forces the interactive window to close.

           Default values: 'variable_name=xsp_variable' and
            'number_of_columns=2'.

         x_shadebobs:

           Launch the shade bobs demo.

         x_spline:

           Launch spline curve editor.

         x_starfield3d:

           Launch the 3D starfield demo.

         x_tetris:

           Launch tetris game.

         x_threshold:

           Threshold selected images interactively.

         x_tictactoe:

           Launch tic-tac-toe game.

         x_warp:
             _nb_keypoints_xgrid>=2,_nb_keypoints_ygrid>=2,_nb_keypoints_contours>=0,
               _preview_fidelity={ 0:coarsest | 1:coarse | 2:normal | 3:fine |
               4:finest },_[background_image],0<=_background_opacity<=1

           Launch the interactive image warper.

           Default values: 'nb_keypoints_xgrid=nb_keypoints_ygrid=2',
            'nb_keypoints_contours=0' and 'preview_fidelity=1'.

         x_waves:

           Launch the image waves demo.

         x_whirl:
             _opacity>=0

           Launch the fractal whirls demo.

           Default values: 'opacity=0.2'.

         12. Examples of Use
             ---------------

         'gmic' is a generic image processing tool which can be used in a wide
          variety of situations. The few examples below illustrate possible
       uses of
          this tool:

         ### View a list of images:

           $ gmic file1.bmp file2.jpeg

         ### Convert an image file:

           $ gmic input.bmp output output.jpg

         ### Create a volumetric image from a movie sequence:

           $ gmic input.mpg append z output output.hdr

         ### Compute image gradient norm:

           $ gmic input.bmp gradient_norm

         ### Denoise a color image:

           $ gmic image.jpg denoise 30,10 output denoised.jpg

         ### Compose two images using overlay layer blending:

           $ gmic image1.jpg image2.jpg blend overlay output blended.jpg

         ### Evaluate a mathematical expression:

           $ gmic echo "cos(pi/4)^2+sin(pi/4)^2={cos(pi/4)^2+sin(pi/4)^2}"

         ### Plot a 2D function:

           $ gmic 1000,1,1,2 fill "X=3*(x-500)/500;X^2*sin(3*X^2)+(!c?u(0,
          -1):cos(X*10))" plot

                             ../img/example_plot.png [image: '2D Plot']

         ### Plot a 3D elevated function in random colors:

           $ gmic 128,128,1,3,"u(0,255)" plasma 10,3 blur 4 sharpen 10000 n
       0,255
          elevation3d[-1]
       "'X=(x-64)/6;Y=(y-64)/6;100*exp(-(X^2+Y^2)/30)*abs(cos(X)*s
          in(Y))'"

                             ../img/example_elevation3d.png [image: '3D
          Elevation']

         ### Plot the isosurface of a 3D volume:

           $ gmic mode3d 5 moded3d 5 double3d 0 isosurface3d
          "'x^2+y^2+abs(z)^abs(4*cos(x*y*z*3))'",3

                             ../img/example_isosurface3d.png [image: '3D
          Isosurface']

         ### Render a G'MIC 3D logo:

           $ gmic 0 text G'MIC,0,0,53,1,1,1,1 expand_xy 10,0 blur 1 normalize
       0,
          100 +plasma 0.4 add blur 1 elevation3d -0.1 moded3d 4

                             ../img/example_logo.png [image: '3D G'MIC
          Logo']

         ### Generate a 3D ring of torii:

           $ gmic repeat 20 torus3d 15,2 color3d[-1]
       "{u(60,255)},{u(60,255)},{u(60,
          255)}" *3d[-1] 0.5,1 if "{$>%2}" rotate3d[-1] 0,1,0,90 fi add3d[-1]
       70
          add3d rotate3d 0,0,1,18 done moded3d 3 mode3d 5 double3d 0

                             ../img/example_torii.png [image: '3D Ring']

         ### Create a vase from a 3D isosurface:

           $ gmic moded3d 4 isosurface3d "'x^2+2*abs(y/2)*sin(2*y)^2+z^2-3',0"
          sphere3d 1.5 sub3d[-1] 0,5 plane3d 15,15 rotate3d[-1] 1,0,0,90
          center3d[-1] add3d[-1] 0,3.2 color3d[-1] 180,150,255 color3d[-2]
       128,255,0
          color3d[-3] 255,128,0 add3d

                             ../img/example_vase.png [image: '3D Vase']

         ### Launch a set of interactive demos:

           $ gmic demos


         ** G'MIC comes with ABSOLUTELY NO WARRANTY; for details visit:
       https://gmic.eu **

                                                                      G'MIC(1)