This repo performs color correction and texture analysis using Colour and scikit-image libraries. The color correction also uses opencv to automatically find color correction charts embedded in images.
To run the examples the easiest thing to do is to start with a clean virtual environment. After you clone the repo, create the virtual environment and install the requirements.
python3 -m venv color-venv
source color-venv/bin/activate
pip install -r requirements.txt
then start jupyter and you should be able to run the code in photo_transform.ipynb
and texture_assement.ipynb
.
jupyter notebook
SpyderCHECKR24.py
: This defines the colors used in the SpyderCHECKR24 color calibration chartColorCorrect.py
: This is a convienence function which calls thecolour.colour_correction
, as well as handling color space transformations.batch_colorcorrect.py
: This is a script to loop through all images inJPG_uncorrected
and performing color correction on them.photo_transform.ipynb
: This is an example color correction calculation.texture_assessment.ipynb
: This is an example texture calculation.