0.1.25 — 2024-07-05

Features

• Image encoders are imported now only from timm models.
• Add enc_out_indices to model classes, to enable selecting which layers to use as the encoder outputs.

Removed

• Removed SAM and DINOv2 original implementation image-encoders from this repo. These can be found from timm models these days.
• Removed cellseg_models_pytorch.training module which was left unused after example notebooks were updated.

Examples

• Updated example notebooks.
• Added new example notebooks utilizing UNI foundation model from the MahmoodLab.
• Added new example notebooks utilizing the Prov-GigaPath foundation model from the Microsoft Research.
• NOTE: These examples use the huggingface model hub to load the weights. Permission to use the model weights is required to run these examples.

Chore

• Update timm version to above 1.0.0.

Breaking changes

• Lose support for python 3.9
• The self.encoder in each model is new, thus, models with trained weights from previous versions of the package will not work with this version.