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* Add combined motion and object Birdseye mode Add a motion_objects mode that keeps Birdseye active when motion is detected or a confirmed tracked object is present, including stationary objects. Wire the mode through configuration, runtime commands, API schemas, documentation, and UI labels. Exclude false-positive trackers and add regression coverage for Birdseye activation and MQTT validation. * Refactor Birdseye activity types as booleans Replace combination-specific Birdseye modes with composable boolean activity types for motion, active objects, stationary objects, and continuous display. Preserve legacy single-mode configuration and MQTT inputs, support canonical comma-separated MQTT combinations, and allow scalar YAML values to be replaced by nested settings through the config API. * Preserve OpenVINO config translations Regenerate the configuration translations with the OpenVINO detector schema available so the unrelated production detector labels remain intact. * Preserve partial Birdseye mode overrides Allow an empty activity selection with a canonical NONE MQTT state so partial camera and profile overrides can disable inherited flags without failing validation. Add regression coverage for camera and profile inheritance, document the NONE contract, and keep the generated schema fixture scoped to Birdseye. * Address Birdseye activity review feedback Move scalar mode compatibility into the 0.18-1 config migration and reject empty activity selections instead of publishing a NONE state. Pass activity signals through a frozen dataclass, preserve existing active-object tracker behavior, and require confirmed stationary objects. Revert the generic YAML mutation and cover migration, inheritance, MQTT, and activation regressions. * Move Birdseye migration to 0.19 Use the 0.19-0 configuration revision for converting scalar Birdseye modes to composable activity flags, and update the migration regression coverage accordingly. * Remove Birdseye migration test Drop the dedicated config migration test as requested during review while retaining the 0.19-0 migration implementation.
Frigate NVR™ - Realtime Object Detection for IP Cameras
[English] | 简体中文
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 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.