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* Add object ratio config parameters Issue: #2948 * Add config test for object filter ratios Issue: #2948 * Address review comments - Accept `ratio` default - Rename `bounds` to `box` for consistency - Add migration for new field Issue: #2948 * Fix logical errors - field migrations require default values - `clipped` referenced the wrong index for region, since it shifted - missed an inclusion of `ratio` for detections in `process_frames` - revert naming `o[2]` as `box` since it is out of scope! This has now been test-run against a video, so I believe the kinks are worked out. Issue: #2948 * Update contributing notes for `make` Issue: #2948 * Fix migration - Ensure that defaults match between Event and migration script - Deconflict migration script number (from rebase) Issue: #2948 * Filter objects out of ratio bounds Issue: #2948 * Update migration file to 009 Issue: #2948
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:
