# from export import export_formats sf = list(export_formats().Suffix) + ['.xml'] # export suffixes check_suffix(p, sf) # checks p = Path(p).name # eliminate trailing separators pt, jit, onnx, xml, engine, coreml, saved_model...
from export import export_formats File "C:\Users\USER/.cache\torch\hub\ultralytics_yolov5_master\export.py", line 64, in ROOT = Path(os.path.relpath(ROOT, Path.cwd())) # relative File "C:\Users\USER\AppData\Local\Programs\Python\Python39\lib\ntpath.py", line 703, in relpath ...
from utils.dataloaders import IMG_FORMATS, VID_FORMATS, LoadImages, LoadStreams from utils.augmentations import letterbox from utils.general import (LOGGER, check_file, check_img_size, check_imshow, check_requirements, colorstr, cv2, increment_path, non_max_suppression, print_args, scale_coords,...
from utils.torch_utils import select_device def export_formats(): # YOLOv5 export formats x = [ ['PyTorch', '-', '.pt', True, True], ['TorchScript', 'torchscript', '.torchscript', True, True], ['ONNX', 'onnx', '.onnx', True, True], ['OpenVINO', 'openvino'...
打开export.py,修改参数【‘–data’】数据集的.yaml文件为自己对应的.yaml文件地址,博主是CCPD.yamll;修改参数【‘–weights’】为自己训练好的权重文件地址,博主是runs/train/exp5/weights/best.pt(最后导出的模型文件也在此目录下);参数【‘–include’】,default参数修改为torchscript。
"""Exports a YOLOv5 *.pt model to ONNX and TorchScript formats Usage: $ export PYTHONPATH="$PWD" && python models/export.py --weights ./weights/yolov5s.pt --img 640 --batch 1 """importargparseimporttorchfromutils.google_utilsimportattempt_downloadfromutils.generalimportset_loggingif__nam...
"""Exports a YOLOv5 *.pt model to ONNX and TorchScript formatsUsage:$ export PYTHONPATH="$PWD" && python models/export.py --weights ./weights/yolov5s.pt--img 640 --batch 1"""importargparseimportsysimporttimesys.path.append('./')# to run '$ python *.py' files in subdirectoriesimp...
GPU Export Benchmarks: Benchmark (mAP and speed) all YOLOv5 export formats withpython utils/benchmarks.py --weights yolov5s.pt --device 0for GPU benchmarks or--device cpufor CPU benchmarks (#6963by@glenn-jocher). Training Reproducibility: Single-GPU YOLOv5 training withtorch>=1.12.0is...
"""Exports a YOLOv5 *.pt model to ONNX and TorchScript formatsUsage:$ export PYTHONPATH="$PWD" && python models/export.py --weights ./weights/yolov5s.pt --img 640 --batch 1"""import argparseimport torchimport torch.nn as nnimport modelsfrom models.experimental import attempt_loadfrom ...
注意:在Windows操作系统上,import onnx 必须要先于 import torch,否则export.py导出onnx会crash掉。 导出onnx模型,可以参考如下代码: """Exports a YOLOv5 *.pt model to ONNX and TorchScript formatsUsage:$ export PYTHONPATH="$PWD" && python models/export.py --weights ./weights/yolov5s.pt --img...