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YOLOv9 + ByteTracker

This project integrates YOLOv9 and ByteTracker for real-time, TensorRT-optimized object detection and tracking, extending the existing TensorRT-Yolov9 implementation.

Usage

  • CPP(TensorRT):
cd build/release
yolov9-bytetrack-trt.exe yolov9-c.engine test.mp4 # the video path
  • Python(ONNX):
cd python
python yolov9_bytetrack.py --model yolov9-c-converted.onnx --video_path test_video.mp4 --output_video_path result.mp4

What is next?

  • Python(TensorRT)

Setup

Python:

cd python
pip install -r requirement.txt

CPP:

Refer to our docs/INSTALL.md for detailed installation instructions. Note that Bytetracker is directly integrated without any modification.

Requirement

  • TensorRT
  • CUDA, CudaNN
  • Eigen 3.3
  • C++ compiler with C++17 or higher support
  • CMake 3.14 or higher
  • OpenCV

Acknowledgement

This project is based on the following awesome projects:

  • YOLOv9 - YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information.
  • ByteTrack - C++ implementation of ByteTrack algorithm.
  • TensorRT-Yolov9 - C++ implementation of YOLOv9 using TensorRT API.