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deepstream-people-flow-mqtt's Introduction

基于deepstream人流识别边缘计算

主要特性

  • 使用Jetson Nano进行边缘计算
  • 使用peoplenet训练模型进行推理
  • MsgConvBroker自定义实现
  • 数据通过MQTT协议提交到OneNET云平台

项目内容

  • 项目通过deepstream实现8条rtsp监控视频流推理,通过Gst-nvdsanalytics插件的ROI设置区域内人流计算。
  • 修改custom payload实现推理结果传送,通过msgconv和mqtt实现数据上传至云端
  • 由于jeston nano性能限制,推理速度只能到10fps左右,使用xavier可以达到300fps

参考

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