Spaces:
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README.md
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# Drone Landing Site Safety
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Analyze aerial RGB imagery to detect safe drone landing sites. Combines monocular depth estimation, promptable hazard segmentation, and geometric heuristics to flag flat, obstacle-free areas, with overlays and metrics that show why a spot is safe.
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<p align="center">
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<img src="examples/build/visloc_03_0001/rgb.jpg" alt="RGB reference" width="80%" />
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<br/>
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<img src="examples/build/visloc_03_0001/composed.png" alt="Safety overlay" width="80%" />
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</p>
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## What’s inside
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- **Main app (`app.py`)** — runs full inference with adjustable thresholds, overlays, and camera assumptions; requires >8GB VRAM (assuming default 1024 px processing resolution); runtime is ~2000 ms per image.
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---
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title: Drone Landing Site Safety
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emoji: 🛰️
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colorFrom: blue
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sdk: gradio
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sdk_version: 6.0.0
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app_file: app.py
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pinned: false
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---
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# Drone Landing Site Safety
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Analyze aerial RGB imagery to detect safe drone landing sites. Combines monocular depth estimation, promptable hazard segmentation, and geometric heuristics to flag flat, obstacle-free areas, with overlays and metrics that show why a spot is safe.
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## What’s inside
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- **Main app (`app.py`)** — runs full inference with adjustable thresholds, overlays, and camera assumptions; requires >8GB VRAM (assuming default 1024 px processing resolution); runtime is ~2000 ms per image.
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