openseg-group/openseg.pytorch

Health v2 · maintenance only

Adoption not part of the score

1237 stars · 141 forks observed · 2026-08-28

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

Official PyTorch implementations of semantic segmentation models OCNet, OCRNet, and SegFix, achieving state-of-the-art results on benchmarks like Cityscapes, ADE20K, and PASCAL-Context. It provides training and evaluation code with distributed and mixed-precision support for scene parsing research.

Use cases

• train a semantic segmentation model on cityscapes
• implement OCRNet for scene parsing
• run SegFix boundary refinement on segmentation masks
• reproduce state-of-the-art results on ADE20K
• fine-tune a segmentation model with HRNet backbone
• evaluate segmentation models on PASCAL-Context

When to choose

• you need reference implementations of OCNet/OCRNet/SegFix for research
• you want to reproduce published segmentation benchmark results
• you need distributed or mixed-precision segmentation training in PyTorch

When to avoid

• you need a production-ready segmentation pipeline rather than research code
• you want a maintained framework with broad model coverage like MMSegmentation
• you work outside PyTorch or lack GPU resources

Facets

library · maturity maintenance

machine-learning deep-learning image-processing computer-vision computer-vision image-processing deep-learning machine-learning python cross-platform semantic-segmentation pytorch ocrnet ocnet segfix scene-parsing research-code hrnet linux gpu

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