forked from Github/frigate
c2465a46a8
* Set up for http tests * Setup basics for testing and first test * Add testing consts * Cleanup db creation * Add one more check to test * Get event that does not exist * Get events working with cleaner db * Test retain / un-retain * Test setting and deleting sub label * Test getting list of sub labels * Fix bug caught in tests * Test deleting event * Test geting list of events * Expand test * Test more event filters * Write version module so tests don't fail on version import * Test config * Test recordings endpoint * Formatting * Remove unused imports * Test stats * Add cleanup files in const * Add name to match other checks
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:
