Hugging Face's logo

Spaces:
DSatishchandra
/
solar_wind_fault_detection_Ver2
Sleeping

App Files Community
solar_wind_fault_detection_Ver2 / README.md
DSatishchandra's picture
DSatishchandra
Update README.md
3bc9e3d verified
preview code
|
raw
history blame
1.02 kB
metadata
title: solar wind fault detection Ver2
emoji: 🐠
colorFrom: indigo
colorTo: green
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