Krita and Scripting
Krita is a painting and image editing application for KOffice.
The plugin consist of following parts;
- The ScriptingPart class which implements a KParts plugin that is loaded by Krita on startup and which is responsible for displaying the ScriptingDocker and the setup of the scripting environment.
- The kritacore module offers an interface to scripting backends to deal with the Krita internals. The Scripting::Module class is the entry point for your script to communicate with Krita.
The Krita Scripting Handbook contains a full reference of all objects and methods accessible from within the scripting backends.
The Handbook is generated from the sourcecode using doxygen and the doxy2doc.py Python script as postprocessor to create visible output from the by doxygen produced XML files.
- Krita Homepage
- Krita Wiki
- Krita Scripting Plugin code
- Krita Scripting Plugin ReadMe
- Kross Homepage
- Kross Wiki Page
- Kross Tutorial
The following screenshot shows Krita running with it's on the right half displayed scripting-docker that is used to display scripts and fastly execute scripts. The image itself was created using the Random painting Ruby script.
Those extensions are also accessible from within the "Scripts"-menu and are distributed with Krita, so some default extensions are installed together with Krita as part of it, or could be later added and configured on demand using the "Script Manager".
Following sections try to provide an overview of the per default with Krita distributed scripting extensions.
Import and Export
The following screenshot shows the "Python Imaging Library Import" Python script pilimport.py once executed.
Most parts of the pilimport.py Python script are related to GUI and preparation of the import-proccess. The core part of that script, so the part that does actualy do the import, looks like;
# import needed modules and initialize PIL import Krita, Image, ImageFile Image.init() # read the imagefile and convert to RGB pilimage = Image.open("/home/myusername/myimage.jpg") pilimage = pilimage.convert("RGB") # fetch the Krita layer we like to import to krtlayer = Krita.image().activePaintLayer() # scale the loaded image to fit pilimage = pilimage.resize((krtlayer.width(), krtlayer.height())) # let's use the progressbar Krita.progress().setProgressTotalSteps(krtlayer.width() * krtlayer.height()) # finally do the import krtlayer.beginPainting("PIL import") it = krtlayer.createRectIterator(0, 0, krtlayer.width(), krtlayer.height()) while (not it.isDone()): data = pilimage.getpixel((it.x(), it.y())) it.setPixel(list(data)) Krita.progress().incProgress() it.next() krtlayer.endPainting()
The pilexport.py Python script which does export a Krita image to a by the Python Imaging Library supported image-format looks then like;
# import needed modules and initialize PIL import Krita, Image, ImageFile Image.init() # fetch the Krita layer we like to export krtlayer = Krita.image().activePaintLayer() # let's use the progressbar Krita.progress().setProgressTotalSteps(krtlayer.width() * krtlayer.height()) # create the PIL image pilimage = Image.new("RGB", (krtlayer.width(), krtlayer.height())) # finally do the export it = krtlayer.createRectIterator(0, 0, krtlayer.width(), krtlayer.height()) finesh = it.isDone() while (not finesh): pilimage.putpixel((it.x(),it.y()), tuple(it.pixel())) Krita.progress().incProgress() finesh = it.next() # and save the result pilimage.save("/home/myusername/myimage.jpg")
- The randompaint.rb Ruby script demonstrates how to use the Painter scripting API and paints random shape on the screen.
- The torture-painting.rb Ruby script tortures Krita with painting.
- The changecs.rb Ruby script demonstrates how to change the colorspace.
- The invert.rb Ruby script inverts the pixel of an image.
- The invert.py Python script inverts the pixel of an image.
- The filterstest.rb Ruby script tests the Krita filters.
- The torture-filters.rb Ruby script tortures Krita with filters.
- The reshapehisto.py Python script is an experimental script to try to reshape histogram, while the results are far to be convincing yet it is still an example on how to use histogram in a script.