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* utility functions * backend config * backend object speed tracking * draw speed on debug view * basic frontend zone editor * remove line sorting * fix types * highlight line on canvas when entering value in zone edit pane * rename vars and add validation * ensure speed estimation is disabled when user adds more than 4 points * pixel velocity in debug * unit_system in config * ability to define unit system in config * save max speed to db * frontend * docs * clarify docs * utility functions * backend config * backend object speed tracking * draw speed on debug view * basic frontend zone editor * remove line sorting * fix types * highlight line on canvas when entering value in zone edit pane * rename vars and add validation * ensure speed estimation is disabled when user adds more than 4 points * pixel velocity in debug * unit_system in config * ability to define unit system in config * save max speed to db * frontend * docs * clarify docs * fix duplicates from merge * include max_estimated_speed in api responses * add units to zone edit pane * catch undefined * add average speed * clarify docs * only track average speed when object is active * rename vars * ensure points and distances are ordered clockwise * only store the last 10 speeds like score history * remove max estimated speed * update docs * update docs * fix point ordering * improve readability * docs inertia recommendation * fix point ordering * check object frame time * add velocity angle to frontend * docs clarity * add frontend speed filter * fix mqtt docs * fix mqtt docs * don't try to remove distances if they weren't already defined * don't display estimates on debug view/snapshots if object is not in a speed tracking zone * docs * implement speed_threshold for zone presence * docs for threshold * better ground plane image * improve image zone size * add inertia to speed threshold example
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 RTSP to reduce the number of connections to your camera
- WebRTC & MSE support for low-latency live view
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.