This repository contains code for randomly generating colorblind-friendly color sets. To generate the color sets, color vision deficiency simulations for various types of deficiencies are performed, and a minimum perceptual difference for the simulated colors is enforced using the CAM02-UCS perceptually uniform color space (where each type of deficiency is treated separately), as is a minimum lightness distance (for grayscale).
Pregenerated color sets are included in the color-sets directory. The following parameters were used:
$ python3 gen_color_cycles.py --num-colors 6 --cvd-severity 100 --min-color-dist 20 --num-sets 10000
10000 color sets generated in 31235.150347471237s using 28 jobs
$ python3 gen_color_cycles.py --num-colors 8 --cvd-severity 100 --min-color-dist 18 --num-sets 10000
10000 color sets generated in 68176.89465022087s using 28 jobs
$ python3 gen_color_cycles.py --num-colors 10 --cvd-severity 100 --min-color-dist 16 --num-sets 10000
10000 color sets generated in 295049.9100484848s using 28 jobs
The code contained in this repository is distributed under the MIT License.
The included CVD simulation and color distance calculation implementation is based on Colorspacious, which is MIT licensed.
The resulting color sets generated are released into the public domain using the CC0 1.0 Public Domain Dedication.
- Matthew Petroff, Original author
- Colorspacious, Basis for CVD simulation and color distance calculations
CVD simulation is based on:
G. M. Machado, M. M. Oliveira and L. A. F. Fernandes, "A Physiologically-based Model for Simulation of Color Vision Deficiency," in IEEE Transactions on Visualization and Computer Graphics, vol. 15, no. 6, pp. 1291-1298, Nov.-Dec. 2009. doi:10.1109/TVCG.2009.113
CIECAM02 and CAM02-UCS overview:
Luo M.R., Li C. (2013) CIECAM02 and Its Recent Developments. In: Fernandez-Maloigne C. (eds) Advanced Color Image Processing and Analysis. Springer, New York, NY. doi:10.1007/978-1-4419-6190-7_2