基于EdgeYOLO+ROS2物体检测包源码+文档说明

# EdgeYOLO-ROS [EdgeYOLO](https://github.com/LSH9832/edgeyolo) + ROS 2 Inference DEMO ## Supported List - ONNXRuntime C++ and Python - TensorRT C++ - OpenVINO C++ ※ TFLite inference demo code has been uploaded but not tested. ## Requirements - ROS 2 Foxy or Humble - OpenCV - ONNXRuntime or TensorRT or OpenVINO - bbox_ex_msgs - v4l2-camera (for Webcam Demo) ## Build ```bash cd ros2_ws/src git clone https://github.com/Ar-Ray-code/bbox_ex_msgs git clone https://github.com/fateshelled/EdgeYOLO-ROS cd ../ # for C++ colcon build --symlink-install --packages-up-to edgeyolo_ros_cpp bbox_ex_msgs # for python colcon build --symlink-install --packages-up-to edgeyolo_ros_py bbox_ex_msgs ``` ## Model Download - Model download from [PINTO_model_zoo](https://github.com/PINTO0309/PINTO_model_zoo/blob/main/356_EdgeYOLO/download_nopost.sh) - use nopost model ## Webcam DEMO ### ONNXRuntime ```bash # Run C++ Node ros2 launch edgeyolo_ros_cpp edgeyolo_onnxruntime.launch.py \ model_path:=edgeyolo_tiny_coco_416x416.onnx # Run Python Node ros2 launch edgeyolo_ros_py edgeyolo_onnxruntime.launch.py \ model_path:=edgeyolo_tiny_coco_416x416.onnx ``` ### OpenVINO ```bash # model convert mo.py --input_model edgeyolo_tiny_coco_416x416.onnx \ --input_shape [1,3,416,416] \ --output_dir ./openvino_model # Run C++ Node ros2 launch edgeyolo_ros_cpp edgeyolo_openvino.launch.py \ model_path:=./openvino_model/edgeyolo_tiny_coco_416x416.xml ``` ### TensorRT ```bash # model convert trtexec --onnx=edgeyolo_tiny_coco_416x416.onnx \ --saveEngine=edgeyolo_tiny_coco_416x416.engine # Run C++ Node ros2 launch edgeyolo_ros_cpp edgeyolo_tensorrt.launch.py \ model_path:=edgeyolo_tiny_coco_416x416.engine ``` ## Reference - [EdgeYOLO](https://github.com/LSH9832/edgeyolo) - [YOLOX-ROS](https://github.com/Ar-Ray-code/YOLOX-ROS) - [PINTO_model_zoo](https://github.com/PINTO0309/PINTO_model_zoo)