forked from Github/frigate
88fc0fac8f
* Basic functionality
* Threaded motion estimator
* Revert "Threaded motion estimator"
This reverts commit 3171801607.
* Don't detect motion when ptz is moving
* fix motion logic
* fix mypy error
* Add threaded queue for movement for slower ptzs
* Move queues per camera
* Move autotracker start to app.py
* iou value for tracked object
* mqtt callback
* tracked object should be initially motionless
* only draw thicker box if autotracking is enabled
* Init if enabled when initially disabled in config
* Fix init
* Thread names
* Always use motion estimator
* docs
* clarify fov support
* remove size ratio
* use mp event instead of value for ptz status
* update autotrack at half fps
* fix merge conflict
* fix event type for mypy
* clean up
* Clean up
* remove unused code
* merge conflict fix
* docs: update link to object_detectors page
* Update docs/docs/configuration/autotracking.md
Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
* clarify wording
* pass actual instances directly
* default return preset
* fix type
* Error message when onvif init fails
* disable autotracking if onvif init fails
* disable autotracking if onvif init fails
* ptz module
* verify required_zones in config
* update util after dev merge
---------
Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
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.
Screenshots
Integration into Home Assistant
Also comes with a builtin UI:
