README.md

metadata

title: Solar Wind Fault Detection
emoji: 🐠
colorFrom: purple
colorTo: indigo
sdk: streamlit
sdk_version: 1.45.0
app_file: app.py
pinned: false
license: apache-2.0

Thermal Anomaly Monitoring Dashboard

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.

Features

• Live video feed with fault detection (bounding boxes and labels).
• Live logs, metrics, and anomaly trends.
• Predictive anomaly detection based on trends.
• Videos stored in the data folder.

Setup

1. Place .mp4 videos in the data folder.
2. Install dependencies: pip install -r requirements.txt.
3. Run the app: streamlit run app.py.
4. Deploy on Hugging Face Spaces.

Notes

• Fine-tune YOLOv5 models for accurate fault detection.
• Update class IDs in detection_service.py based on your model.

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference