Blake Blackshear
c14f986fae
stop forcing detection all the way to stationary_threshold
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3 anos atrás | |
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| .devcontainer | 3 anos atrás | |
| .github | 3 anos atrás | |
| docker | 3 anos atrás | |
| docs | 3 anos atrás | |
| frigate | 3 anos atrás | |
| migrations | 3 anos atrás | |
| web | 3 anos atrás | |
| .dockerignore | 3 anos atrás | |
| .gitignore | 3 anos atrás | |
| .pylintrc | 4 anos atrás | |
| LICENSE | 4 anos atrás | |
| Makefile | 3 anos atrás | |
| README.md | 3 anos atrás | |
| benchmark.py | 4 anos atrás | |
| docker-compose.yml | 3 anos atrás | |
| labelmap.txt | 4 anos atrás | |
| process_clip.py | 3 anos atrás |
README.md
Frigate - NVR With Realtime Object Detection for IP Cameras
A complete and local NVR designed for Home Assistant with AI object detection. Uses OpenCV and Tensorflow to perform realtime object detection locally for IP cameras.
Use of a Google Coral Accelerator is optional, but highly recommended. The Coral will outperform even the best CPUs and can process 100+ FPS with very little overhead.
- Tight integration with Home Assistant via a custom component
- Designed to minimize resource use and maximize performance by only looking for objects when and where it is necessary
- Leverages multiprocessing heavily with an emphasis on realtime over processing every frame
- Uses a very low overhead motion detection to determine where to run object detection
- Object detection with TensorFlow runs in separate processes for maximum FPS
- Communicates over MQTT for easy integration into other systems
- Records video with retention settings based on detected objects
- 24/7 recording
- Re-streaming via RTMP to reduce the number of connections to your camera
Documentation
View the documentation at https://docs.frigate.video
Donations
If you would like to make a donation to support development, please use Github Sponsors.
Screenshots
Integration into Home Assistant
Also comes with a builtin UI:
