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30 lines
1.4 KiB
Markdown
30 lines
1.4 KiB
Markdown
---
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id: index
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title: Introduction
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slug: /
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---
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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.
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Use of a [Google Coral Accelerator](https://coral.ai/products/) is optional, but strongly recommended. CPU detection should only be used for testing purposes. The Coral will outperform even the best CPUs and can process 100+ FPS with very little overhead.
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- Tight integration with Home Assistant via a [custom component](https://github.com/blakeblackshear/frigate-hass-integration)
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- Designed to minimize resource use and maximize performance by only looking for objects when and where it is necessary
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- Leverages multiprocessing heavily with an emphasis on realtime over processing every frame
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- Uses a very low overhead motion detection to determine where to run object detection
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- Object detection with TensorFlow runs in separate processes for maximum FPS
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- Communicates over MQTT for easy integration into other systems
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- Recording with retention based on detected objects
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- Re-streaming via RTSP to reduce the number of connections to your camera
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- A dynamic combined camera view of all tracked cameras.
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## Screenshots
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