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* Move each camera to a separate card and show per process info * Install top * Add support for cpu usage stats * Use cpu usage stats in debug * Increase number of runs to ensure good results * Add ffprobe endpoint * Get ffprobe for multiple inputs * Copy ffprobe in output * Add fps to camera metrics * Fix lint errors * Update stats config * Add ffmpeg pid * Use grid display so more cameras can take less vertical space * Fix hanging characters * Only show the current detector * Fix bad if statement * Return full output of ffprobe process * Return full output of ffprobe process * Don't specify rtsp_transport * Make ffprobe button show dialog with output and option to copy * Adjust ffprobe api to take paths directly * Add docs for ffprobe api
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:
