YOLO11-Pose usage

NOTE: The yaml file is not required.

• Convert model
• Compile the lib
• Edit the config_infer_primary_yolo11_pose file

Convert model

1. Download the YOLO11 repo and install the requirements

git clone https://github.com/ultralytics/ultralytics.git
cd ultralytics
pip3 install -e .
pip3 install onnx onnxslim onnxruntime

NOTE: It is recommended to use Python virtualenv.

2. Copy conversor

Copy the export_yolo11_pose.py file from DeepStream-Yolo-Pose/utils directory to the ultralytics folder.

3. Download the model

Download the pt file from YOLO11 releases (example for YOLO11s-Pose)

wget https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo11s-pose.pt

NOTE: You can use your custom model.

4. Convert model

Generate the ONNX model file (example for YOLO11s-Pose)

python3 export_yolo11_pose.py -w yolo11s-pose.pt --dynamic

NOTE: To change the inference size (defaut: 640)

-s SIZE
--size SIZE
-s HEIGHT WIDTH
--size HEIGHT WIDTH

Example for 1280

-s 1280

or

-s 1280 1280

NOTE: To simplify the ONNX model

--simplify

NOTE: To use dynamic batch-size (DeepStream >= 6.1)

--dynamic

NOTE: To use static batch-size (example for batch-size = 4)

--batch 4

5. Copy generated files

Copy the generated ONNX model file and labels.txt file (if generated) to the DeepStream-Yolo-Pose folder.

Compile the lib

1. Open the DeepStream-Yolo-Pose folder and compile the lib

2. 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
  

3. Make the lib

make -C nvdsinfer_custom_impl_Yolo_pose clean && make -C nvdsinfer_custom_impl_Yolo_pose

Edit the config_infer_primary_yolo11_pose file

Edit the config_infer_primary_yolo11_pose.txt file according to your model (example for YOLO11s-Pose)

[property]
...
onnx-file=yolo11s-pose.onnx
...
num-detected-classes=80
...
parse-bbox-func-name=NvDsInferParseYoloPose
...

NOTE: The DeepStream-Yolo-Pose requires

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