Colour blindness affects approximately 1 in 12 men (8%) and 1 in 200 women in the world. Worldwide, there are approximately 300 million people with colour blindness. However, most of developers don't have problems seeing color, they never stop to consider that their choices of colors or images make their website unusable and frustrating to those who can't see some shades of color. This problem of accessibility has grown ever since there has been an increase in focus on Data Science. This is majorly because a lot of your users/ clients/ co-workers may have difficulty in viewing certain visualizations when color is the only differentiating factor. Colors add uniqueness and beauty to everything that we see in our lives. But unfortunately, around ~4% of the world's population faces a condition called 'Color blindness' where they would not be able to see all the colors in the way it should be.

Colour blind people face many difficulties in everyday life which normally sighted people just aren’t aware of. Problems can arise in even the simplest of activities including choosing and preparing food, gardening, sport, driving a car and selecting which clothes to wear. Colour blind people can also find themselves in trouble because they haven’t been able to pick up a change in someone’s mood by a change in colour of their face, or not noticed their child getting sunburnt.

Colour blindness can affect access to education, exam grades and career choice. Worldwide relatively little research has been done into the effects of colour blindness in everyday life. This is because until now the general population has been unaware of the difficulties that colour blindness can cause on a daily basis. Society has therefore on the whole treated colour blind people no differently to people with normal colour vision. This needs to change – colour blind people learn to manage but this doesn’t mean that their needs can be ignored.

What it does

'Color For All' is an application which can simulate images for Protanopia, Deuteranopia, Tritanopia and Hybrid Color Blindness based on how people with the selected color blindness would perceive it naturally. It also has the option of varying the degree of color blindness for simulating.

Along with simulation it also corrects the input image in a way that a user with the selected color blindness can easily distiguish among colors present in the corrected image.

How we built it

This application would not have been possible without these tools:

  • OpenCV
  • Pillow
  • Numpy
  • Python

Challenges we ran into

  • This was our first time using openCV for transforming images
  • We had difficulty collaborating over a remote environment due to connectivity issues.

Accomplishments that we're proud of

  • Easy to setup and run
  • Simulates Protanopia, Deutranopia, Tritanopia and Hybrid Colorblindess (Protanopia+Deutranopia).
  • Corrects colors in images for Protanopia, Deutranopia and Hybrid Colorblindness.
  • An option to vary the degree of colorblindness for both Simulation and Correction!
  • The script runs extremely fast.
  • Can be easily accessed using the command line

What we learned

  • Using OpenCV for image simulation and correction
  • The different types of color blindness
  • Good team communication
  • Best-practices for our Github repository and code

What's next for Color For All

This is just the start for 'Color For All'. We aim to convert the application into a functional website where users can easily drag and drop any image for simulation and correction

Built With

Share this project: