forked from Github/frigate
a4e6d9ed9a
When running ffprobe, use `subprocess.run` rather than `subprocess.Popen`. This simplifies the handling that is needed to run and process the outputs. Here, filename parsing is also simplified by explicitly removing the file extension with `os.path.splitext` and forcing a single split into the camera name and the formatted date.
Frigate - NVR With Realtime Object Detection for IP Cameras
A complete and local NVR designed for HomeAssistant 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 HomeAssistant 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 clips of detected objects
- 24/7 recording
- Re-streaming via RTMP to reduce the number of connections to your camera
Documentation
View the documentation at https://blakeblackshear.github.io/frigate
Donations
If you would like to make a donation to support development, please use Github Sponsors.
Screenshots
Integration into HomeAssistant
Also comes with a builtin UI:
