README.md

metadata

title: Pyronear Wildfire Detection
emoji: 🏆
colorFrom: blue
colorTo: pink
sdk: streamlit
python_version: 3.11
app_file: app.py
pinned: false
license: apache-2.0

MP4 to 8 Frames + Wildfire Detection for Pyronear

Upload an MP4, extract evenly spaced frames, run wildfire detection on each, and display the main detections (one image per main detection).

Requirements

• Python 3.9+
• Packages listed in requirements.txt

Install

python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

Run

streamlit run app.py

Streamlit will print a local URL (for example, http://localhost:8501). Open it in your browser and upload an MP4. Detection starts automatically after upload.

Docker Compose + Make

Run with:

make run

Other commands:

make logs
make stop
make down

Then open http://127.0.0.1:7860 in your browser.

Notes

• The first run downloads the wildfire detection model from Hugging Face.
• ffmpeg/ffprobe are required for frame extraction.
• OpenCV is used for motion features and image processing.