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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
```bash
python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
```
## Run
```bash
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:
```bash
make run
```
Other commands:
```bash
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.
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