daltonlens 0.1.2

Utility to help colorblind people by providing color filters and highlighting tools.

DaltonLens-Python

This python package is a companion to the desktop application DaltonLens. Its main goal is to help the research and development of better color filters for people with color vision deficiencies. The current features include:

• Simulate color vision deficiencies using the Viénot 1999, Brettel 1997 or Machado 2009 models.
• Provide conversion functions to/from sRGB, linear RGB and LMS
• Implement several variants of the LMS model
• Generate Ishihara-like test images

Install

python3 -m pip install daltonlens

How to use

From the command line

daltonlens-python --help
usage: daltonlens-python [-h] [--model MODEL] [--filter FILTER] [--deficiency DEFICIENCY] [--severity SEVERITY] input_image output_image

Toolbox to simulate and filter color vision deficiencies.

positional arguments:
  input_image           Image to process.
  output_image          Output image

optional arguments:
  -h, --help            show this help message and exit
  --model MODEL, -m MODEL
                        Color model to apply: vienot, brettel, machado or auto (default: auto)
  --filter FILTER, -f FILTER
                        Filter to apply: simulate or daltonize. (default: simulate)
  --deficiency DEFICIENCY, -d DEFICIENCY
                        Deficiency type: protan, deutan or tritan (default: protan)
  --severity SEVERITY, -s SEVERITY
                        Severity between 0 and 1 (default: 1.0)

From code

from daltonlens import convert, simulate, generate
import PIL
import numpy as np

# Generate a test image that spans the RGB range
im = np.asarray(PIL.Image.open("test.png").convert('RGB'))

# Create a simulator using the Viénot 1999 algorithm.
simulator = simulate.Simulator_Vienot1999()

# Apply the simulator to the input image to get a simulation of protanomaly
protan_im = simulator.simulate_cvd (im, simulate.Deficiency.PROTAN, severity=0.8)