Decomposing an input image into different features.
The "src" folder contains the source code to train a colour-converting VQ-VAE. The "arguments.py" specifies the input arguments the "main.py" accepts.
For instance to train a standard VQ-VAE: python main.py --model vqvae --batch-size 2 --dataset imagenet --data_dir <PATH/TO/IMAGENET> --hidden 128 --k 128 --kl 128 --target_size 224 --max-epoch-samples 50000 --results-dir <PATH/TO/OUT> --colour_space rgb2rgb
The argument "colour_space" defines the input and output colous spaces. The first three letters are for the input. The last three letters are for the output.
Examples:
- rgb2dkl
- rgb2lab
- rgb2lms
- lms2dkl
- lms2rgb ...