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--- |
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title: solar wind fault detection Ver2 |
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emoji: 🐠 |
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colorFrom: indigo |
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colorTo: green |
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sdk: streamlit |
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sdk_version: 1.45.0 |
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app_file: app.py |
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pinned: false |
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license: apache-2.0 |
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--- |
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# Thermal Anomaly Monitoring Dashboard |
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A dashboard for real-time fault detection in solar panels and windmill turbines using drone or CCTV footage. Built with Streamlit and YOLOv5, deployed on Hugging Face Spaces. |
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## Features |
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- Live video feed with fault detection (bounding boxes and labels). |
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- Live logs, metrics, and anomaly trends. |
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- Predictive anomaly detection based on trends. |
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- Videos stored in the `data` folder. |
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## Setup |
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1. Place `.mp4` videos in the `data` folder. |
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2. Install dependencies: `pip install -r requirements.txt`. |
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3. Run the app: `streamlit run app.py`. |
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4. Deploy on Hugging Face Spaces. |
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## Notes |
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- Fine-tune YOLOv5 models for accurate fault detection. |
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- Update class IDs in `detection_service.py` based on your model. |
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference |