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NVR with realtime local object detection for IP cameras
aicameragoogle-coralhome-assistanthome-automationhomeautomationmqttnvrobject-detectionrealtimertsptensorflow
57864f2be6
Generally eliminate the `while True` loops while waiting for a stop event and prefer to condition the loops on if the stop event is set, blocking on that where it makes sense. This generally comes in 3 flavors. First and simplest, when there is a sleep and the stop event is the only thing the loop blocks on, instead do a check using `stop_event.wait(timeout)` to instead block on the stop event for the designated amount of time. Second, when there is a different event that is blocking in the loop, condition the loop on `stop_event.is_set()` rather than breaking when it is set. Finally, when there is a separate internal condition that requires a counter, have the loop iterate over the counter and use `if stop_event.wait(timeout)` internal to the loop. |
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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: