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NVR with realtime local object detection for IP cameras
aicameragoogle-coralhome-assistanthome-automationhomeautomationmqttnvrobject-detectionrealtimertsptensorflow
d0f44de6bc
* hide camera overrides badge from system sections * show empty card on camera metrics page when no cameras are defined * fix enabled camera state switch after adding via wizard Cameras added mid-session have no WS state until the dispatcher publishes camera_activity (which only happens on a fresh onConnect). Fall back to the config's enabled value so the switch reflects reality immediately after the wizard closes. * guard camera enabled access console would throw errors after adding via camera wizard * fix useOptimisticState dropping debounced setState under StrictMode * use openvino on cpu as default model - faster than tflite on cpu - add to default generated config * use an enum for model_size the frontend will then render this as a select dropdown because of the changes in the json schema * i18n * sync object filter entries with tracked labels in camera config form Filter sub-collapsibles in the camera Objects section are driven by `filters` dict keys, but profile merges and live track-switch edits don't add matching entries, so newly tracked labels (like from a profile override) had no collapsible. Synthesize default filter entries from `track` in the form data so every tracked label renders a collapsible; baseline data also gets the synthesized entries, so save payloads are unchanged. * revalidate raw paths cache after config save so CameraPathWidget shows fresh credentials * fix test * restore masked ffmpeg credentials when persisting camera config * formatting * rebuild ffmpeg commands when enabling recording for the first time Toggling record.enabled from the config UI updated the in-memory config but left ffmpeg running with its original command, so the record output args were never wired in and nothing landed in the cache for the maintainer to move. The record config update now rebuilds ffmpeg_cmds when enabled_in_config transitions, and the camera watchdog restarts ffmpeg on a false to true transition so the record output gets wired in. MQTT toggles, which only flip record.enabled at runtime, are unaffected and continue to work via the maintainer's drop/keep gate. * keep record toggle switch in single camera view disabled until enabled in config * fix override detection for sections unset in the global config Override badges and the blue dot now compare against schema defaults for sections like motion that the API serializes as null when omitted from the global YAML, instead of treating any populated camera config as an override * add support for config-aware patterns in section hiddenFields Section configs can now declare dynamic hidden-field entries as functions of the loaded config; objects.ts uses this to hide auto-populated attribute filters (DHL, face, license_plate, etc.) from the form, save flow, and override popover when those labels aren't user-settable * siimplify object filters handling live updating was getting very messy. users will just need to save once they enable a new object in order to see filters for that object * tweaks * update docs for new detector default * make genai provider required and add special case for UI prevent validation errors from appearing on initial creation of genai provider by setting the first option in the select dropdown as default |
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| config | ||
| docker | ||
| docs | ||
| frigate | ||
| migrations | ||
| notebooks | ||
| testing-scripts | ||
| web | ||
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| .pylintrc | ||
| audio-labelmap.txt | ||
| CODEOWNERS | ||
| CONTRIBUTING.md | ||
| cspell.json | ||
| docker-compose.yml | ||
| generate_config_translations.py | ||
| labelmap.txt | ||
| LICENSE | ||
| Makefile | ||
| netlify.toml | ||
| package-lock.json | ||
| pyproject.toml | ||
| README_CN.md | ||
| README.md | ||
| TRADEMARK.md | ||
Frigate NVR™ - Realtime Object Detection for IP Cameras
EnglishA 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 GPU or AI accelerator is highly recommended. AI accelerators will outperform even the best CPUs with very little overhead. See Frigate's supported object detectors.
- 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.
License
This project is licensed under the MIT License.
- Code: The source code, configuration files, and documentation in this repository are available under the MIT License. You are free to use, modify, and distribute the code as long as you include the original copyright notice.
- Trademarks: The "Frigate" name, the "Frigate NVR" brand, and the Frigate logo are trademarks of Frigate, Inc. and are not covered by the MIT License.
Please see our Trademark Policy for details on acceptable use of our brand assets.
Screenshots
Live dashboard
Streamlined review workflow
Multi-camera scrubbing
Built-in mask and zone editor
Translations
We use Weblate to support language translations. Contributions are always welcome.
Copyright © 2026 Frigate, Inc.