meetps/pytorch-semseg

Health v2 · maintenance only

Adoption not part of the score

3402 stars · 787 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

A PyTorch library implementing popular semantic segmentation architectures such as FCN, U-Net, SegNet, PSPNet, ICNet, FRRN, and LinkNet, with dataloaders for common segmentation datasets. It provides configuration-driven training and validation for pixel-wise dense classification tasks.

Use cases

• train a semantic segmentation model in pytorch
• implement FCN or U-Net for pixel-wise image classification
• segment images on Pascal VOC or Cityscapes datasets
• compare semantic segmentation architectures like PSPNet and SegNet
• run image segmentation with pretrained encoder backbones
• fine-tune a segmentation network on a custom dataset

When to choose

• you need reference implementations of classic segmentation architectures in PyTorch
• you want config-driven training on standard segmentation benchmarks like Cityscapes or ADE20K
• you are researching or benchmarking encoder-decoder segmentation models

When to avoid

• you need state-of-the-art transformer-based segmentation models like SegFormer or Mask2Former
• you require active maintenance and support for recent PyTorch versions
• you want production-ready inference serving rather than research code

Facets

library · maturity maintenance

deep-learning machine-learning image-processing computer-vision computer-vision deep-learning machine-learning image-processing python windows semantic-segmentation pytorch fcn unet pspnet segnet linknet icnet frrn computer-vision linux macos gpu

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markdown · JSON · MCP: product_card(name="meetps/pytorch-semseg")