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rt-detr-finetuned-for-satellite-image-roofs-detection

Hugging Face model Yifeng-Liu/rt-detr-finetuned-for-satellite-image-roofs-detection (object-detection)

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What's in it

Data offered docs-verified
roof detections (object detection on satellite imagery)
Formats docs-verified
Safetensors model weights · Python transformers API (image array input via cv2)
Access docs-verified
Open weights under MIT licence; runs locally via Hugging Face transformers and PyTorch; no API key stated in DOCS

Useful for

Use cases llm-inferred
Roof count and footprint screening for flood risk exposure inventories · Impermeable roof area estimate as an input to drainage strategy runoff calculations · Pre-survey roof mapping for site appraisal or planning context reports
Audience llm-inferred
flood consultants · drainage engineers · GIS analysts · planners

Limitations

Constraints llm-inferred
Small-object accuracy is much lower than large-object accuracy (self-reported AP 0.248 small vs 0.632 large) · Reported evaluation is on a single dataset, keremberke/satellite-building-segmentation (self-reported) · DOCS Limitations section is generic and documents no specific risks or geographic coverage · Not deployed by any Inference Provider; requires self-hosted inference with Python, torch, transformers and cv2 · Interactive demo and MCP access depend on third-party Hugging Face Spaces and Gradio hosting
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; 2154 downloads/30d, 18 likes.

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