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NVR with realtime local object detection for IP cameras
aicameragoogle-coralhome-assistanthome-automationhomeautomationmqttnvrobject-detectionrealtimertsptensorflow
4e800e19ff
* Only show back button text on desktop * Add mobile camera drawer to separate component * Use bottom sheet for export on mobile * Add intermediary mobile bottom sheet * fix filter * Fix mobile layout jumping * Fix desktop vertical camera view * Fix horizontal camera list * Add overlay instead of using same button for timeline exports * Don't use native hls for now * Fix export bottom sheet * Fix scrolling * Simplify checks * Adjust hls compat approach * Fix events shadow * Make corners consistent * Make corners consistent * fix max drawer height * Use separate buttons for export control * Add icons * Fix list views * Fix new items to review * bottom padding on bottom sheets * bottom padding on bottom sheets |
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config | ||
docker | ||
docs | ||
frigate | ||
migrations | ||
web | ||
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.pylintrc | ||
audio-labelmap.txt | ||
benchmark_motion.py | ||
benchmark.py | ||
CODEOWNERS | ||
docker-compose.yml | ||
labelmap.txt | ||
LICENSE | ||
Makefile | ||
netlify.toml | ||
process_clip.py | ||
pyproject.toml | ||
README.md |
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: