Photobooth app written in Python supporting DSLR, picamera2 and webcameras
Project description
Written in Python 🐍, coming along with a modern Vue frontend.
Installation - Documentation - PyPI package - 3d printed box
😍 Features
- 📹 camera live preview with shortest delay as possible, permanent video live view in background
- ⚡️ optimized for speed, live stream hardware accelerated on rpi, cpu load < 20%
- 🫶 several camera backends supported for high quality stills and livestream
- 💡 WLED support signaling photo countdown and feedback to the user when the photo is actually taken
- 🤝 Linux 🐧, Raspberry Pi 🍓 and Windows 🪟 platforms supported
📷 Supported Cameras
The photobooth app's Python backend allows to use different camera types on Linux and Windows platforms:
- Raspberry Pi Camera Module 1/2/3 (with or without autofocus)
- Arducam cameras (with or without autofocus)
- DSLR camera via
- gphoto2, Linux
- digicamcontrol, Windows (not yet implemented)
- webcams (via opencv2 or v4l)
The app controls camera's autofocus, handles led signaling when a photo is taken and streams live video to photobooth.
The reference photobooth box is made from 3d printed parts, see the 3d printed reference box over here.
🛫 Speed Optimized
The photobooth app uses libraries optimized for speed. Even a Raspberry Pi 3B+ is fine to use. Typically the photobooth app takes following times to process data:
| Task | RPI 3B+ | RPI 4B | Intel i7 |
|---|---|---|---|
| CPU load with picamera2 livestream and display | ~20% | ~20% | <1% |
| Postprocess: scale images for preview | <500ms | <350ms | <30ms |
| Postprocess: Stage "Remove Greenscreen" | 130ms | 90ms | 20ms |
| Postprocess: Stage "Add Text" | n/a | n/a | n/a |
| Postprocess: Stage "Apply Instagram-Like Filter" | n/a | <80ms | <30ms |
💅 Screenshots
Find screenshots in the documentation
🔧 Installation
See separate installation instructions in the documentation.
The photobooth app can be used standalone but is not feature complete yet. Anyway, it integrates well with the fully blown photobooth project, see description how to achieve integration.
©️ License
The software is licensed under the MIT license.
🎉 Donation
If you like my work and like to keep me motivated you can sponsor me:
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