DeepStream-Yolo-Seg

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-Seg 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
• YOLOv5-Seg usage
• YOLOv7-Seg usage
• YOLOv7-Mask usage
• YOLOv8-Seg usage
• YOLO11-Seg usage
• RF-DETR-Seg usage
• NMS configuration
• Detection threshold configuration

Supported models

• RF-DETR-Seg
• YOLO11-Seg
• YOLOv8-Seg
• YOLOv7-Mask
• YOLOv7-Seg
• YOLOv5-Seg

Instructions

1. Download the DeepStream-Yolo-Seg repo

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

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_seg clean && make -C nvdsinfer_custom_impl_Yolo_seg

3. Run

deepstream-app -c deepstream_app_config.txt

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

NMS configuration

For now, the NMS is configured in the ONNX exporter file.

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

Detection threshold configuration

The minimum detection confidence threshold is configured in the ONNX exporter file. The pre-cluster-threshold should be >= the value used in the ONNX model.

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

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