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NVR with realtime local object detection for IP cameras
aicameragoogle-coralhome-assistanthome-automationhomeautomationmqttnvrobject-detectionrealtimertsptensorflow
351bef936f
When cudaMemGetInfo cannot be called or returns an error, compute_cuda_mem_limit now returns None and the caller skips injecting gpu_mem_limit, leaving ORT to manage its own arena (grow-as-needed up to device capacity). Tradeoff documented in the docstring: - Old behavior returned a hardcoded 4 GB. That was wrong for low-VRAM devices (Jetson Nano 4 GB shared, Quadro K620 2 GB, GT 1030 2 GB) and broken /dev/nvidia* container passthroughs, where requesting 4 GB caused cudaErrorMemoryAllocation at session init. It was also wrong for big GPUs (24 GB RTX 3090 with 20 GB free), needlessly starving the session. - The leak vectors fixed elsewhere in this PR (mem_pattern + mallopt) are independent of the BFC arena cap, so dropping the cap on the failure path does not reintroduce the leak. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> |
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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.