""" Export a YOLOv8 PyTorch model to other formats. TensorFlow exports authored by https://github.com/zldrobit Format | `format=argument` | Model --- | --- | --- PyTorch | - | yolov8n.pt TorchScript | `torchscript` | yolov8n.torchscript ONNX | `onnx` | yolov8n.onnx OpenVINO | `openvino` | yolov8n_openvino_model/ TensorRT | `engine` | yolov8n.engine CoreML | `coreml` | yolov8n.mlmodel TensorFlow SavedModel | `saved_model` | yolov8n_saved_model/ TensorFlow GraphDef | `pb` | yolov8n.pb TensorFlow Lite | `tflite` | yolov8n.tflite TensorFlow Edge TPU | `edgetpu` | yolov8n_edgetpu.tflite TensorFlow.js | `tfjs` | yolov8n_web_model/ PaddlePaddle | `paddle` | yolov8n_paddle_model/ Requirements: $ pip install ultralytics[export] Python: from ultralytics import YOLO model = YOLO('yolov8n.pt') results = model.export(format='onnx') CLI: $ yolo mode=export model=yolov8n.pt format=onnx Inference: $ yolo predict model=yolov8n.pt # PyTorch yolov8n.torchscript # TorchScript yolov8n.onnx # ONNX Runtime or OpenCV DNN with --dnn yolov8n_openvino_model # OpenVINO yolov8n.engine # TensorRT yolov8n.mlmodel # CoreML (macOS-only) yolov8n_saved_model # TensorFlow SavedModel yolov8n.pb # TensorFlow GraphDef yolov8n.tflite # TensorFlow Lite yolov8n_edgetpu.tflite # TensorFlow Edge TPU yolov8n_paddle_model # PaddlePaddle TensorFlow.js: $ cd .. && git clone https://github.com/zldrobit/tfjs-yolov5-example.git && cd tfjs-yolov5-example $ npm install $ ln -s ../../yolov5/yolov8n_web_model public/yolov8n_web_model $ npm start """
RKNN:yolov8模型转换与板端推理流程
2024-01-12 17:34:02 36 阅读