gesture_recognition_tlt_deepstream:一个项目,演示如何训练您自己的手势识别深度学习管道。 我们从预先训练的检测模型开始,使用Transfer Learning Toolkit 3.0将其重新用于手部检测,然后将其与专用手势识别模型一起使用。 经过培训后,我们将使用Deepstream SDK在NVIDIA:registered:Jetson:trade_mark:上部署此模型-源码

上传者: 42106299 | 上传时间: 2021-08-26 15:23:37 | 文件大小: 257KB | 文件类型: ZIP
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使用NVIDIA预训练模型和Transfer Learning Toolkit 3.0与机器人创建基于手势的交互 在这个项目中,我们演示如何训练您自己的手势识别深度学习管道。 我们从预先训练的检测模型开始,使用Transfer Learning Toolkit 3.0将其重新用于手部检测,然后将其与专用手势识别模型一起使用。 经过培训后,我们将在NVIDIA:registered:Jetson:trade_mark:上部署此模型。 可以将这种手势识别应用程序部署在机器人上以理解人类手势并与人类进行交互。 该演示可以作为点播网络研讨会提供: : 第1部分。训练对象检测网络 1.环境设置 先决条件 Ubuntu 18.04 LTS python> = 3.6.9 = 19.03.5 docker-API 1.40 nvidia-container-toolkit> = 1.3.0-1

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