28 lines
725 B
Markdown
28 lines
725 B
Markdown
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# Construction Site Monitoring
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VIMS instance for construction-site.
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## Related Article
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[/insights/the-future-of-infrastructure-monitoring/](https://landvex.com/insights/the-future-of-infrastructure-monitoring/)
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## Anomaly Classes
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- safety_violation
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- equipment_idle
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- material_waste
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- progress_delay
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- unauthorized_access
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## Quick Start
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1. Add training images to `data/raw/`
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2. Annotate using LabelImg (YOLO format)
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3. Run preprocessing: `python src/detector.py`
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4. Train model: `python src/detector.py --train`
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5. Run inference: `python src/detector.py --predict data/test/image.jpg`
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## API
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Once deployed, access via:
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- REST: `POST /api/construction-site/predict`
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- WebSocket: `ws://host/ws/construction-site/alerts`
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