yassouali/pytorch-segmentation

Health v2 · maintenance only

Adoption not part of the score

1818 stars · 389 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A PyTorch library implementing multiple semantic segmentation models (DeepLab V3+, PSPNet, U-Net, SegNet, FCN, ENet, and others) with datasets, losses, LR schedulers, and data augmentation. It is configured via JSON config files and includes training and inference scripts plus a Colab tutorial.

Use cases

• train a semantic segmentation model in pytorch
• implement deeplab v3+ for image segmentation
• segment images with u-net
• compare semantic segmentation architectures
• run inference with a pretrained segmentation model
• learn how semantic segmentation models are implemented

When to choose

• you need a reference implementation of classic segmentation models in PyTorch
• you want a simple, config-driven training pipeline for segmentation research
• you are learning how models like DeepLab or PSPNet work internally

When to avoid

• you need production-grade, actively maintained segmentation tooling like MMSegmentation or Detectron2
• you need the latest transformer-based segmentation models (SegFormer, Mask2Former)
• you need instance or panoptic segmentation rather than semantic segmentation

Facets

library · maturity maintenance

machine-learning deep-learning image-processing computer-vision computer-vision deep-learning machine-learning image-processing python cross-platform semantic-segmentation pytorch deeplab unet pspnet fcn segnet research-code gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="yassouali/pytorch-segmentation")