DeepStream-Yolo-Pose

NVIDIA DeepStream SDK 8.0 / 7.1 / 7.0 / 6.4 / 6.3 / 6.2 / 6.1.1 / 6.1 / 6.0.1 / 6.0 application for YOLO-Pose models

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YOLO object detection models and other infos: https://github.com/marcoslucianops/DeepStream-Yolo

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Important: Please export the ONNX model with the new export file, generate the TensorRT engine again with the updated files, and use the new config_infer_primary file according to your model

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Getting started

• Supported models
• Instructions
• YOLOv7-Pose usage
• YOLOv8-Pose usage
• YOLO11-Pose usage
• YOLO-NAS-Pose usage
• NMS configuration
• Detection threshold configuration

Supported models

• YOLO-NAS-Pose
• YOLO11-Pose
• YOLOv8-Pose
• YOLOv7-Pose

Instructions

1. Download the DeepStream-Yolo-Pose repo

git clone https://github.com/marcoslucianops/DeepStream-Yolo-Pose.git
cd DeepStream-Yolo-Pose

2. Compile the libs

2.1. Set the CUDA_VER according to your DeepStream version

export CUDA_VER=XY.Z

• x86 platform

  DeepStream 8.0 = 12.8
  DeepStream 7.1 = 12.6
  DeepStream 7.0 / 6.4 = 12.2
  DeepStream 6.3 = 12.1
  DeepStream 6.2 = 11.8
  DeepStream 6.1.1 = 11.7
  DeepStream 6.1 = 11.6
  DeepStream 6.0.1 / 6.0 = 11.4
  

• Jetson platform

  DeepStream 8.0 = 13.0
  DeepStream 7.1 = 12.6
  DeepStream 7.0 / 6.4 = 12.2
  DeepStream 6.3 / 6.2 / 6.1.1 / 6.1 = 11.4
  DeepStream 6.0.1 / 6.0 = 10.2
  

2.2. Make the libs

make -C nvdsinfer_custom_impl_Yolo_pose clean && make -C nvdsinfer_custom_impl_Yolo_pose
make clean && make

NOTE: To use the Python code, you need to install the DeepStream Python bindings.

Reference: https://github.com/NVIDIA-AI-IOT/deepstream_python_apps

• x86 platform:

  pip3 install https://github.com/NVIDIA-AI-IOT/deepstream_python_apps/releases/download/v1.2.2/pyds-1.2.2-cp312-cp312-linux_x86_64.whl
  

• Jetson platform:

  pip3 install https://github.com/NVIDIA-AI-IOT/deepstream_python_apps/releases/download/v1.2.2/pyds-1.2.2-cp312-cp312-linux_aarch64.whl
  

NOTE: It is recommended to use Python virtualenv.

NOTE: The steps above only work on DeepStream 8.0. For previous versions, please check the files on the NVIDIA-AI-IOT/deepstream_python_apps repo.

3. Run

• C code

  ./deepstream -s file:///opt/nvidia/deepstream/deepstream/samples/streams/sample_1080p_h264.mp4 -c config_infer_primary_yoloV8_pose.txt
  

• Python code

  python3 deepstream.py -s file:///opt/nvidia/deepstream/deepstream/samples/streams/sample_1080p_h264.mp4 -c config_infer_primary_yoloV8_pose.txt
  

NOTE: The TensorRT engine file may take a very long time to generate (sometimes more than 10 minutes).

NOTE: To change the source

-s file:// or rtsp:// or http://
--source file:// or rtsp:// or http://

NOTE: To change the infer config file (example for config_infer.txt file)

-c config_infer.txt
--infer-config config_infer.txt

NOTE: To change the nvstreammux batch-size (example for 2; default: 1)

-b 2
--streammux-batch-size 2

NOTE: To change the nvstreammux width (example for 1280; default: 1920)

-w 1280
--streammux-width 1280

NOTE: To change the nvstreammux height (example for 720; default: 1080)

-e 720
--streammux-height 720

NOTE: To change the GPU id (example for 1; default: 0)

-g 1
--gpu-id 1

NOTE: The DeepStream-Yolo-Pose requires

[property]
...
maintain-aspect-ratio=1
symmetric-padding=1
...

NMS configuration

For now, the nms-iou-threshold is fixed to 0.45.

NOTE: Make sure to set cluster-mode=4 in the config_infer file.

Detection threshold configuration

[class-attrs-all]
pre-cluster-threshold=0.25

My projects: https://www.youtube.com/MarcosLucianoTV