forked from Github/frigate
ce3a544ecd
* Add auto configuration for height, width and fps in detect role
* Add auto-configuration for detect width, height, and fps for input roles with detect in the CameraConfig class in config.py
* Refactor code to retrieve video properties from input stream in CameraConfig class and add optional parameter to retrieve video duration in get_video_properties function
* format
* Set default detect dimensions to 1280x720 and update DetectConfig to use the defaults
* Revert "Set default detect dimensions to 1280x720 and update DetectConfig to use the defaults"
This reverts commit a1aed0414d.
* Add default detect dimensions if autoconfiguration failed and log a warning message
* fix warn message spelling on frigate/config.py
Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
* Ensure detect height and width are not None before using them in camera configuration
* docs: initial commit
* rename streamInfo to stream_info
Co-authored-by: Blake Blackshear <blakeb@blakeshome.com>
* Apply suggestions from code review
Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
* Update docs
* handle case then get_video_properties returns 0x0 dimension
* Set detect resolution based on stream properties if available, else apply default values
* Update FrigateConfig to set default values for stream_info if resolution detection fails
* Update camera detection dimensions based on stream information if available
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Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
Co-authored-by: Blake Blackshear <blakeb@blakeshome.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:
