YOLOv8-使用ONNX+YOLOv8+Python实现目标检测-项目实战-附完整流程教程.zip

# ONNX YOLOv8 Object Detection # Important - The input images are directly resized to match the input size of the model. I skipped adding the pad to the input image, it might affect the accuracy of the model if the input image has a different aspect ratio compared to the input size of the model. Always try to get an input size with a ratio close to the input images you will use. # Requirements * Check the **requirements.txt** file. * For ONNX, if you have a NVIDIA GPU, then install the **onnxruntime-gpu**, otherwise use the **onnxruntime** library. # Installation ```shell git clone https://github.com/ibaiGorordo/ONNX-YOLOv8-Object-Detection.git cd ONNX-YOLOv8-Object-Detection pip install -r requirements.txt ``` ### ONNX Runtime For Nvidia GPU computers: `pip install onnxruntime-gpu` Otherwise: `pip install onnxruntime` # ONNX model Use the Google Colab notebook to convert the model: [](https://colab.research.google.com/drive/1-yZg6hFg27uCPSycRCRtyezHhq_VAHxQ?usp=sharing) You can convert the model using the following code after installing ultralitics (`pip install ultralytics`): ```python from ultralytics import YOLO model = YOLO("yolov8m.pt") model.export(format="onnx", imgsz=[480,640]) ``` [//]: # (The original models were converted to different formats (including .onnx) by [PINTO0309](https://github.com/PINTO0309). Download the models from **[his repository]**(https://github.com/PINTO0309/PINTO_model_zoo/tree/main/345_YOLOv8). For that, you can either run the `download_single_batch.sh` or copy the download link inside that script in your browser to manually download the file. Then, extract and copy the downloaded onnx models (for example `yolov8m_480x640.onnx`) to your **[models directory](https://github.com/ibaiGorordo/ONNX-YOLOv8-Object-Detection/tree/main/models)**, and fix the file name in the python scripts accordingly.) # Original YOLOv8 model The original YOLOv8 model can be found in this repository: [YOLOv8 Repository](https://github.com/ultralytics/ultralytics) - The License of the models is GPL-3.0 license: [License](https://github.com/ultralytics/ultralytics/blob/main/LICENSE) # Examples * **Image inference**: ```shell python image_object_detection.py ``` * **Webcam inference**: ```shell python webcam_object_detection.py ``` * **Video inference**: https://youtu.be/JShJpg8Mf7M ```shell python video_object_detection.py ```  *Original video: [https://youtu.be/Snyg0RqpVxY](https://youtu.be/Snyg0RqpVxY)* # References: * YOLOv8 model: [https://github.com/ultralytics/ultralytics](https://github.com/ultralytics/ultralytics) * YOLOv5 model: [https://github.com/ultralytics/yolov5](https://github.com/ultralytics/yolov5) * YOLOv6 model: [https://github.com/meituan/YOLOv6](https://github.com/meituan/YOLOv6) * YOLOv7 model: [https://github.com/WongKinYiu/yolov7](https://github.com/WongKinYiu/yolov7) * PINTO0309's model zoo: [https://github.com/PINTO0309/PINTO_model_zoo](https://github.com/PINTO0309/PINTO_model_zoo) * PINTO0309's model conversion tool: [https://github.com/PINTO0309/openvino2tensorflow](https://github.com/PINTO0309/openvino2tensorflow)