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* Initial re-implementation of semantic search * put docker-compose back and make reindex match docs * remove debug code and fix import * fix docs * manually build pysqlite3 as binaries are only available for x86-64 * update comment in build_pysqlite3.sh * only embed objects * better error handling when genai fails * ask ollama to pull requested model at startup * update ollama docs * address some PR review comments * fix lint * use IPC to write description, update docs for reindex * remove gemini-pro-vision from docs as it will be unavailable soon * fix OpenAI doc available models * fix api error in gemini and metadata for embeddings
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.