Leetop Jetson Cloud Demo 5：DeepStream Container应用

在Leetop官网取得使用权限后，可以在设备端做如下测试。
支持设备：
Module Jetpack config Software other SW HW
Orin devkit module 35.0 EA V2 default DS + Full Jetpack + Pytorch + TF Todesk NV devkit
Orin 32G 35.0 EA V2 default DS + Full Jetpack + Pytorch + TF Todesk NV devkit
Orin devkit module 35.0 EA V2 default DS + Full Jetpack + Pytorch + TF Todesk Leetop carry board
Orin 32G 35.0 EA V2 default DS + Full Jetpack + Pytorch + TF Todesk Leetop carry board
Orin devkit 35.0 EA V2 Orin nx 16G DS + Full Jetpack + Pytorch + TF Todesk
Orin devkit 35.0 EA V2 Orin nx 8G DS + Full Jetpack + Pytorch + TF Todesk
Xavier devkit module 35.0 EA V2 default DS + Full Jetpack + Pytorch + TF Todesk NV devkit
Xavier 32G 35.0 EA V2 default DS + Full Jetpack + Pytorch + TF Todesk Leetop carry board
Xavier Industry 35.0 EA V2 default DS + Full Jetpack + Pytorch + TF Todesk Leetop carry board
Xavier Industry 35.0 EA V2 default DS + Full Jetpack + Pytorch + TF Todesk NV devkit
Xavier NX 35.0 EA V2 default DS + Full Jetpack + Pytorch + TF Todesk Leetop carry board
Xavier NX 16G 35.0 EA V2 default DS + Full Jetpack + Pytorch + TF Todesk Leetop carry board
Nano R 32.7.2 default DS + Full Jetpack + Pytorch + TF Todesk Leetop carry board
TX2 NX R 32.7.2 default DS + Full Jetpack + Pytorch + TF Todesk Leetop carry board
Xavier devkit module R 32.7.2 default DS + Full Jetpack + Pytorch + TF Todesk NV devkit
Xavier 32G R 32.7.2 default DS + Full Jetpack + Pytorch + TF Todesk Leetop carry board
Xavier Industry R 32.7.2 default DS + Full Jetpack + Pytorch + TF Todesk Leetop carry board
Xavier Industry R 32.7.2 default DS + Full Jetpack + Pytorch + TF Todesk NV devkit
Xavier NX R 32.7.2 default DS + Full Jetpack + Pytorch + TF Todesk Leetop carry board
Xavier NX 16G R 32.7.2 default DS + Full Jetpack + Pytorch + TF Todesk Leetop carry board

 DeepStream行人检测
此deepstream容器支持在4个视频文件输入流上运行人员检测。该容器中使用的模型是Resnet-18模型，该模型使用TensorFlow训练，并使用TensorRT在Jetson上优化运行。

 获取容器

$ sudo docker pull nvcr.io/nvidia/deepstream-peopledetection:r32.4.2

 运行容器

sudo xhost +si:localuser:root
$ sudo docker run -it --rm --net=host --runtime nvidia -e DISPLAY=$DISPLAY -v /tmp/.X11-unix/:/tmp/.X11-unix nvcr.io/nvidia/deepstream-peopledetection:r32.4.2  deepstream-test5-app -c deepstream-5.0/samples/configs/deepstream-app/sourceX_1080p_dec_infer-resnet_tracker_tiled_display_int8_hq_dla_nx.txt

未完待续