forked from Github/frigate
80f8256422
Use `np.unique` to determine the correct set of row/col pairs to iterate over when doing the object matching without needing to track which rows or columns have already been seen. Add to some of the accompanying documentation to clarify this algorithm. Also fix what looks to be an erroneous early return, and change this to a continue.
Frigate - NVR With Realtime Object Detection for IP Cameras
A complete and local NVR designed for HomeAssistant 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 HomeAssistant 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 clips of detected objects
- 24/7 recording
- Re-streaming via RTMP to reduce the number of connections to your camera
Documentation
View the documentation at https://blakeblackshear.github.io/frigate
Donations
If you would like to make a donation to support development, please use Github Sponsors.
Screenshots
Integration into HomeAssistant
Also comes with a builtin UI:
