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# Frigate - NVR With Realtime Object Detection for IP Cameras
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\[English\] | [简体中文](https://github.com/blakeblackshear/frigate/README_CN.md)
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A complete and local NVR designed for [Home Assistant](https://www.home-assistant.io) 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 highly recommended. The Coral will outperform even the best CPUs and can process 100+ FPS with very little overhead.
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<p align="center">
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<img align="center" alt="logo" src="docs/static/img/frigate.png">
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</p>
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# Frigate - 一个具有实时目标检测的本地NVR
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[English](https://github.com/blakeblackshear/frigate) | \[简体中文\]
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一个完整的本地网络视频录像机(NVR),专为[Home Assistant](https://www.home-assistant.io)设计,具备AI物体检测功能。使用OpenCV和TensorFlow在本地为IP摄像头执行实时物体检测。
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强烈推荐使用可选配件:[Google Coral加速器](https://coral.ai/products/)。在该场景下,Coral的性能甚至超过目前的顶级CPU,并且可以以极低的电力开销轻松处理100 以上的画面帧。
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- 通过[自定义组件](https://github.com/blakeblackshear/frigate-hass-integration)与Home Assistant紧密集成
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- 设计上通过仅在必要时和必要地点寻找物体,最大限度地减少资源使用并最大化性能
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- 大量利用多进程处理,强调实时性而非处理每一帧
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- 使用非常低开销的运动检测来确定运行物体检测的位置
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- 使用TensorFlow进行物体检测,运行在单独的进程中以达到最大FPS
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- 通过MQTT进行通信,便于集成到其他系统中
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- 根据检测到的物体设置保留时间进行视频录制
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- 24/7全天候录制
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- 通过RTSP重新流传输以减少摄像头的连接数
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- 支持WebRTC和MSE,实现低延迟的实时观看
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## 文档(英文)
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你可以在这里查看文档 https://docs.frigate.video
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## 赞助
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如果您想通过捐赠支持开发,请使用 [Github Sponsors](https://github.com/sponsors/blakeblackshear)。
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## 截图
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### 实时监控面板
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<div>
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<img width="800" alt="实时监控面板" src="https://github.com/blakeblackshear/frigate/assets/569905/5e713cb9-9db5-41dc-947a-6937c3bc376e">
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</div>
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### 简单的审查工作流程
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<div>
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<img width="800" alt="简单的审查工作流程" src="https://github.com/blakeblackshear/frigate/assets/569905/6fed96e8-3b18-40e5-9ddc-31e6f3c9f2ff">
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</div>
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### 多摄像头可按时间轴查看
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<div>
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<img width="800" alt="多摄像头可按时间轴查看" src="https://github.com/blakeblackshear/frigate/assets/569905/d6788a15-0eeb-4427-a8d4-80b93cae3d74">
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</div>
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### 内置遮罩和区域编辑器
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<div>
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<img width="800" alt="内置遮罩和区域编辑器" src="https://github.com/blakeblackshear/frigate/assets/569905/d7885fc3-bfe6-452f-b7d0-d957cb3e31f5">
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</div>
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