cocoon

Python colorspace co(o)nversion and color manipulation library.

Mostly wrap colour to provide a different interface.

Warning

cocoon is a personal experimental project, shared without any guarantee. It is not aimed to be widely used and maintained out of my personal scope. API can break at any time.

What it is.

Cocoon allow to use, interract and create RGB colorspaces in the context of building python software.

Cocoon vastly depends on colour and wrap its existing API to provide a different way to interract with colorspaces.

Cocoon also provide object to make the manipulation of colors easier, as converting between different color models or encodings.

difference with colors for color-management

• Monolithic RGB_Colorspace class split in multiple classes (called ColorspaceComponent) :
  • Whitepoint class
  • Gamut class
  • TransferFunctions class
  • RgbColorspace which regroup the above
• Immutability for all ColorspaceComponents
  • you can't edit attributes of an instance once created
  • methods to edit a specirfic attribute by returning a new instance are provided
• Hashing and equality for all ColorspaceComponents
• Conversion of ColorspaceComponents instances to dict objects
• More "metadata" about RgbColorspace stored.
  • description and categories
  • mostly useful in the GUI context of listing instances
• mechanism to create "linear" variant of any colorspace
• retrieving a colorspace is done through the get_colorspace function instead of using a global dict object.
• retrieving a colorspace by name is case-sensitive, though aliases and a "simplified representation of the name" are provided.

the cooon specific RgbColorspace class can be converted to and from a colour.RGB_Colorspace instance.

issues implied

• an update on the colour library require an update on the cocoon side (example: new colorspace added)
• cocoon RgbColorspace class design allow multiple attributes to be None which usually implied more code to interract with it (conditional checks).
• increased complexity

demo

Basic conversion

import numpy
import cocoon

some_image = numpy.array()
image_colorspace = cocoon.get_colorspace("sRGB", force_linear=True)
# linear sRGB is enough common it has a constant
image_colorspace = cocoon.sRGB_LINEAR_COLORSPACE
target_colorspace = cocoon.get_colorspace("ACEScg")

converted_image = cocoon.colorspace_to_colorspace(
  some_image,
  source_colorspace=image_colorspace,
  target_colorspace=target_colorspace,
  chromatic_adaptation_transform=cocoon.ChromaticAdaptationTransform.get_default()
)

Creating a frankestein sRGB colorspace with ACES whitepoint.

import cocoon

acescg_colorspace = cocoon.get_colorspace("ACEScg")

new_colorspace = cocoon.sRGB_COLORSPACE.with_whitepoint(
    new_whitepoint=acescg_colorspace.whitepoint,
    matrix_to_XYZ=None,
    matrix_from_XYZ=None,
)
# recompute the matrices as the whitepoint changed
new_colorspace = new_colorspace.with_derived_matrices()

roadmap

• improve package structure
• should colour conversion methods be moved outside classes, just simpel conversion functions ?
• change to_dict to serialize and create its inverse from_serialized
• build a dataset of whitepoints