Metadata-Version: 2.1
Name: daltonlens
Version: 0.1.3
Summary: Utility to help colorblind people by providing color filters and highlighting tools.
Home-page: https://github.com/DaltonLens/DaltonLens-Python
Author: Nicolas Burrus
Author-email: nicolas@burrus.name
License: UNKNOWN
Project-URL: Bug Tracker, https://github.com/DaltonLens/DaltonLens-Python/issues
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.7
Description-Content-Type: text/markdown
License-File: LICENSE

# DaltonLens-Python

[![Unit Tests](https://github.com/DaltonLens/DaltonLens-Python/actions/workflows/unit_tests.yml/badge.svg)](https://github.com/DaltonLens/DaltonLens-Python/actions/workflows/unit_tests.yml)

This python package is a companion to the desktop application [DaltonLens](https://github.com/DaltonLens/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

```python
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)
```


