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mask2former-satellite

Hugging Face model mfaytin/mask2former-satellite (image-segmentation)

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What's in it

Data offered docs-verified
land cover classification into 9 classes: Background, Bareland, Grass, Pavement, Road, Tree, Water, Cropland, Building
Formats docs-verified
Safetensors (model weights) · PyTorch tensor output (H, W class IDs)
Access docs-verified
Open model: licence MIT; no API key required (per catalogue auth field)

Useful for

Use cases llm-inferred
Impermeable-surface screening (Road, Pavement, Building classes) from aerial imagery as drainage/SuDS runoff inputs · Baseline vegetation and water mapping (Tree, Grass, Water) for ecological or BNG habitat screening · Land cover constraint layers from aerial imagery for planning or GIS site screening
Audience llm-inferred
drainage engineers · ecologists · GIS analysts · remote sensing specialists · planners

Limitations

Constraints docs-verified
Geographic bias: trained primarily on OpenEarthMap imagery from specific regions, UK coverage not stated · Resolution sensitivity: best performance on imagery similar to training resolution · May require fine-tuning for other satellite sensors or aerial platforms · Performance may vary with season or weather · Reported best mIoU is 0.5202, so class accuracy is moderate · Not deployed by any Inference Provider; requires local or custom inference setup
Licence
mit
Authentication
No API key required (repository README, auto-extracted; check upstream requirements)
GitHub stars
Unknown
Last commit
Unknown
Last successful page check
14/10/2026
Page health
healthy
Package
Not recorded
Verification
Not independently verified

Provenance & evidence

Verified 2026-10-15 via HF API: exists; 788 downloads/30d, 8 likes.

Metadata observed 14/10/2026 · research sweep: manual-2026-10-15 (Hugging Face models)