yolov5-onnxruntime

yolov5-onnxruntime

link

README.md
yolov5-onnxruntime
C++ YOLO v5 onNX Runtime inference code for object detection.

Dependecies:
OpenCV 4.x
onNXRuntime 1.7+
OS: Tested on Windows 10 and Ubuntu 20.04
CUDA 11+ [Optional]
Build
To build the project you should run the following commands, don’t forget to change ONNXRUNTIME_DIR cmake option:

mkdir build
cd build
cmake … -DONNXRUNTIME_DIR=path_to_onnxruntime -DCMAKE_BUILD_TYPE=Release
cmake --build .
Run
Before running the executable you should convert your PyTorch model to onNX if you haven’t done it yet. Check the official tutorial.

On Windows: to run the executable you should add OpenCV and onNX Runtime libraries to your environment path or put all needed libraries near the executable (onnxruntime.dll and opencv_world.dll).

Run from CLI:

./yolo_ort --model_path yolov5.onnx --image bus.jpg --class_names coco.names --gpu

On Windows ./yolo_ort.exe with arguments as above

Demo