segmentation_models

PyTorch Segmentation Models Zoo

All models here were either written from scratch or refactored from open-source implementations. All models here use Activated Normalization layers instead of traditional Normalization followed by Activation. It makes changing activation function and normalization layer easy and convenient. It also allows using Inplace Activated Batch Norm from the box, which is essential for reducing memory footprint in segmentation tasks.

Encoders

All models could be used as feature extractors (aka backbones) for segmentation architectures. Almost all combinations of backbones and segm.model are supported.

Features

• Unified API. Create Unet, SegmentaionFPN, HRnet models using the same code
• Support for custom number of input channels in pretrained encoders
• All core functionality covered with tests

Repositories used

• Torch Vision Main Repo
• Cadene pretrained models
• Ross Wightman models
• Pytorch Toolbelt by @BloodAxe
• Segmentation Models py @qubvel
• Original HRNet for Segmentation