Implementation of MagViT2 Tokenizer in Pytorch
Tokenizers for 2D and 3D medical images: VQ, LFQ, FSQ, Residual FSQ, VAE, and AE quantizers behind one backbone.
Compress 2D/3D medical images into latents or discrete tokens with interchangeable quantizers (VQ, LFQ, FSQ, VAE, AE) for flexible generative modeling.
Add a description, image, and links to the finite-scalar-quantization topic page so that developers can more easily learn about it.
To associate your repository with the finite-scalar-quantization topic, visit your repo's landing page and select "manage topics."