self.model, self.ckpt = attempt_load_one_weight(weights) File "E:\anaconda3\envs\yolov10\lib\site-packages\ultralytics\nn\tasks.py", line 912, in attempt_load_one_weight ckpt, weight = torch_safe_load(weight) # load ckpt File "E:\anaconda3\envs\yolov10\lib\site-packages\ultralytics\nn\tasks.py", line 839, in torch_safe_load ckpt = torch.load(file, map_location="cpu") File "E:\anaconda3\envs\yolov10\lib\site-packages\ultralytics\utils\patches.py", line 86, in torch_load return _torch_load(*args, **kwargs) File "E:\anaconda3\envs\yolov10\lib\site-packages\torch\serialization.py", line 791, in load with _open_file_like(f, 'rb') as opened_file: File "E:\anaconda3\envs\yolov10\lib\site-packages\torch\serialization.py", line 271, in _open_file_like return _open_file(name_or_buffer, mode) File "E:\anaconda3\envs\yolov10\lib\site-packages\torch\serialization.py", line 252, in __init__ super().__init__(open(name, mode)) OSError: [Errno 22] Invalid argument: 'rE:\\gesture\\experiment\\YOLO-xiaorong\\mpdiou\\YOLOv11-mecd\\runs\\best.pt'

时间: 2025-07-15 09:47:09 浏览: 5
<think>嗯,用户遇到了一个错误,看起来是在尝试加载模型权重的时候出现的。错误信息里提到了OSError,具体是Invalid argument,路径里有奇怪的'rE:\\...',看起来像是路径前面多了一个'r'。用户可能是在使用YOLO相关的代码,比如Ultralytics的YOLOv5或v10,调用attempt_load_one_weight函数时出了问题。 首先,我需要分析错误信息。错误发生在torch.load的时候,系统找不到指定的文件。路径显示为'rE:\\gesture\\experiment\\YOLO-xiaorong\\mpdiou\\YOLOv11-mecd\\runs\\best.pt',这里明显路径前面多了一个'r',可能是字符串转义的问题。比如,用户可能在代码里用了反斜杠没有正确处理,导致Python把路径中的某些部分当成了转义字符,比如'\r'被解释成回车符,所以路径被错误地拼接成了'rE:\\...'。 然后,我应该考虑用户可能的操作步骤。用户可能是在加载预训练权重时,传入的weights参数路径不正确。比如,用户可能使用了相对路径,或者路径字符串中有转义字符没有处理。例如,在Windows系统中,路径分隔符是反斜杠,而Python中反斜杠是转义字符,所以如果没有使用原始字符串或者双反斜杠,就会导致路径解析错误。 接下来,我需要想解决方案。首先,检查文件路径是否正确,确认文件是否存在。然后,确保路径字符串在代码中被正确转义,比如使用双反斜杠或者前缀r来声明原始字符串。例如,路径应该是'E:\\gesture\\...'或者用r'E:\gesture\...'来避免转义。另外,用户可能是在代码中拼接路径的时候,不小心在路径开头多加了'r',导致系统尝试访问'rE:\\...'这个不存在的路径。 另外,用户的环境问题也需要考虑,比如文件权限或者文件是否被其他程序占用,但根据错误信息,更可能的是路径字符串的问题。可能用户传入的weights参数含有转义字符,或者在生成路径时字符串处理有误,导致路径不正确。 最后,总结可能的原因和解决方案,建议用户检查路径字符串是否正确转义,使用原始字符串或双反斜杠,确认文件存在,并检查路径拼接是否有误。这样用户就能逐步排查并解决问题了。</think>这个错误是由于PyTorch加载模型权重时**路径格式异常**导致的,具体表现为路径字符串中出现了非预期的转义符`\r`。以下是关键问题解析和解决方案: --- ### 🔍 错误分析 1. **路径异常** 错误路径显示为`'rE:\\gesture\\...\\best.pt'`,实际有效路径应为`'E:\\gesture\\...\\best.pt'`。 问题根源在于路径字符串被错误拼接,导致开头的`r`字符被附加到盘符前(如`rE:\\`),可能是由于: - **转义符处理错误**:Windows路径中的反斜杠`\`未正确转义 - **字符串拼接错误**:代码中手动拼接路径时误添加了`r`前缀 2. **函数调用栈** 错误发生在`torch.load()`尝试加载权重文件时,关键报错点: ```python OSError: [Errno 22] Invalid argument: 'rE:\\gesture\\...\\best.pt' ``` --- ### 🛠️ 解决方案 1. **检查路径转义** 将路径字符串中的单反斜杠`\`替换为双反斜杠`\\`,或使用**原始字符串前缀**`r`: ```python # 正确格式(推荐) weights = r"E:\gesture\experiment\YOLO-xiaorong\mpdiou\YOLOv11-mecd\runs\best.pt" ``` 2. **验证文件存在性** 手动检查文件路径是否有效: ```python import os print(os.path.exists(r"E:\gesture\experiment\YOLO-xiaorong\mpdiou\YOLOv11-mecd\runs\best.pt")) # 应输出True ``` 3. **修正路径拼接逻辑** 如果路径通过代码动态生成,确保拼接时未引入额外字符: ```python # 错误示例(路径开头误加"r") base_path = "rE:\\gesture\\..." # 正确示例 base_path = "E:\\gesture\\..." ``` --- ### 📌 补充建议 - 若使用相对路径,需确保**工作目录**正确(可通过`os.getcwd()`验证) - 检查文件权限,确认`.pt`文件未被其他进程占用 - 对于Ultralytics框架,建议通过`yolo detect train`等CLI命令加载权重,而非直接调用底层函数 该错误通常通过路径格式修正即可解决,若仍存在问题,可提供完整代码片段进一步分析。
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Freezing layer 'model.22.dfl.conv.weight' AMP: running Automatic Mixed Precision (AMP) checks with YOLOv8n... Traceback (most recent call last): File "C:\Users\14480\Desktop\毕设\ultralytics\ultralytics-main\train.py", line 12, in <module> model.train(data="C://Users//14480//Desktop//毕设//ultralytics//ultralytics-main//dataset//data.yaml", File "C:\Users\14480\Desktop\毕设\ultralytics\ultralytics-main\ultralytics\engine\model.py", line 650, in train self.trainer.train() File "C:\Users\14480\Desktop\毕设\ultralytics\ultralytics-main\ultralytics\engine\trainer.py", line 205, in train self._do_train(world_size) File "C:\Users\14480\Desktop\毕设\ultralytics\ultralytics-main\ultralytics\engine\trainer.py", line 324, in _do_train self._setup_train(world_size) File "C:\Users\14480\Desktop\毕设\ultralytics\ultralytics-main\ultralytics\engine\trainer.py", line 263, in _setup_train self.amp = torch.tensor(check_amp(self.model), device=self.device) File "C:\Users\14480\Desktop\毕设\ultralytics\ultralytics-main\ultralytics\utils\checks.py", line 663, in check_amp assert amp_allclose(YOLO("yolov8n.pt"), im) File "C:\Users\14480\Desktop\毕设\ultralytics\ultralytics-main\ultralytics\models\yolo\model.py", line 23, in __init__ super().__init__(model=model, task=task, verbose=verbose) File "C:\Users\14480\Desktop\毕设\ultralytics\ultralytics-main\ultralytics\engine\model.py", line 149, in __init__ self._load(model, task=task) File "C:\Users\14480\Desktop\毕设\ultralytics\ultralytics-main\ultralytics\engine\model.py", line 230, in _load self.model, self.ckpt = attempt_load_one_weight(weights) File "C:\Users\14480\Desktop\毕设\ultralytics\ultralytics-main\ultralytics\nn\tasks.py", line 948, in attempt_load_one_weight ckpt, weight = torch_safe_load(weight) # load ckpt File "C:\Users\14480\Desktop\毕设\ultralytics\ultralytics-main\ultralytics\nn\tasks.py", line 874, in torch_safe_load ckpt = torch.load(file, map_location="cpu") File "E:\anaconda\envs\cycy\lib\site-packages\torch\serialization.py", line 1470, in load raise pickle.UnpicklingError(_get_wo_message(str(e))) from None _pickle.UnpicklingError: Weights only load failed. This file can still be loaded, to do so you have two options, do those steps only if you trust the source of the checkpoint. (1) In PyTorch 2.6, we changed the default value of the weights_only argument in torch.load from False to True. Re-running torch.load with weights_only set to False will likely succeed, but it can result in arbitrary code execution. Do it only if you got the file from a trusted source. (2) Alternatively, to load with weights_only=True please check the recommended steps in the following error message. WeightsUnpickler error: Unsupported global: GLOBAL ultralytics.nn.tasks.DetectionModel was not an allowed global by default. Please use torch.serialization.add_safe_globals([DetectionModel]) or the torch.serialization.safe_globals([DetectionModel]) context manager to allowlist this global if you trust this class/function. Check the documentation of torch.load to learn more about types accepted by default with weights_only https://pytorch.org/docs/stable/generated/torch.load.html.

E:\ANACONDA\envs\SHIXI\python.exe D:\ultralytics-8.0.50\ultralytics\yolo\train.py Traceback (most recent call last): File "D:\ultralytics-8.0.50\ultralytics\yolo\train.py", line 49, in <module> main() File "D:\ultralytics-8.0.50\ultralytics\yolo\train.py", line 5, in main model = YOLO('D:/ultralytics-8.0.50/runs/detect/train2/weights/best.pt') ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\ultralytics-8.0.50\ultralytics\yolo\engine\model.py", line 96, in __init__ self._load(model, task) File "D:\ultralytics-8.0.50\ultralytics\yolo\engine\model.py", line 135, in _load self.model, self.ckpt = attempt_load_one_weight(weights) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\ultralytics-8.0.50\ultralytics\nn\tasks.py", line 401, in attempt_load_one_weight ckpt, weight = torch_safe_load(weight) # load ckpt ^^^^^^^^^^^^^^^^^^^^^^^ File "D:\ultralytics-8.0.50\ultralytics\nn\tasks.py", line 341, in torch_safe_load return torch.load(file, map_location='cpu'), file # load ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "E:\ANACONDA\envs\SHIXI\Lib\site-packages\torch\serialization.py", line 1470, in load raise pickle.UnpicklingError(_get_wo_message(str(e))) from None _pickle.UnpicklingError: Weights only load failed. This file can still be loaded, to do so you have two options, do those steps only if you trust the source of the checkpoint. (1) In PyTorch 2.6, we changed the default value of the weights_only argument in torch.load from False to True. Re-running torch.load with weights_only set to False will likely succeed, but it can result in arbitrary code execution. Do it only if you got the file from a trusted source. (2) Alternatively, to load with weights_only=True please check the recommended steps in the following error message. WeightsUnpickler error: Unsupported global: GLOBAL ultralytics.nn.tasks.DetectionModel was not a

Namespace(weights='runs/train/exp/weights/best.pt', source='D:/Code/yolov5/detect1.jpg', img_size=640, conf_thres=0.25, iou_thres=0.45, device='', view_img=False , save_txt=False, save_conf=False, nosave=False, classes=None, agnostic_nms=False, augment=False, update=False, project='runs/detect', name='exp', exist_ok=False) YOLOv5 2021-4-11 torch 2.7.1+cpu CPU Traceback (most recent call last): File "D:\Code\yolov5\detect.py", line 180, in <module> detect() File "D:\Code\yolov5\detect.py", line 34, in detect model = attempt_load(weights, map_location=device) # load FP32 model ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\Code\yolov5\models\experimental.py", line 118, in attempt_load ckpt = torch.load(w, map_location=map_location) # load ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\Editor\anaconda3\envs\yolov5-5.0\Lib\site-packages\torch\serialization.py", line 1524, in load raise pickle.UnpicklingError(_get_wo_message(str(e))) from None _pickle.UnpicklingError: Weights only load failed. This file can still be loaded, to do so you have two options, do those steps only if you trust the source of the checkpoint. (1) In PyTorch 2.6, we changed the default value of the weights_only argument in torch.load from False to True. Re-running torch.load with weights_only set to False will likely succeed, but it can result in arbitrary code execution. Do it only if you got the file from a trusted source. (2) Alternatively, to load with weights_only=True please check the recommended steps in the following error message. WeightsUnpickler error: Unsupported global: GLOBAL numpy._core.multiarray._reconstruct was not an allowed global by default. Please use torch.serializat ion.add_safe_globals([numpy._core.multiarray._reconstruct]) or the torch.serialization.safe_globals([numpy._core.multiarray._reconstruct]) context manager to allowlist this global if you trust this class/function.

detect: weights=D:\\yolov5-master\best.pt, source=D:\\yolov5\data\images\test1, data=data\my.yaml, imgsz=[640, 640], conf_thres=0.4, iou_thres=0.45, max_det=1000, device=cuda:0, view_img=False, save_txt=False, save_conf=False, save_crop=False, nosave=False, classes=None, agnostic_nms=False, augment=False, visualize=True, update=False, project=runs\detect, name=exp, exist_ok=False, line_thickness=3, hide_labels=False, hide_conf=False, half=False, dnn=False, vid_stride=1 YOLOv5 2023-1-3 Python-3.8.20 torch-2.4.1 CUDA:0 (NVIDIA GeForce RTX 3050 Ti Laptop GPU, 4096MiB) D:\论文\yolov5-master\models\experimental.py:79: FutureWarning: You are using torch.load with weights_only=False (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for weights_only will be flipped to True. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via torch.serialization.add_safe_globals. We recommend you start setting weights_only=True for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature. ckpt = torch.load(attempt_download(w), map_location='cpu') # load Traceback (most recent call last): File "D:\论文\yolov5-master\detect.py", line 262, in <module> main(opt) File "D:\论文\yolov5-master\detect.py", line 257, in main run(**vars(opt)) File "D:\Anaconda\yingyong\envs\yolov5\lib\site-packages\torch\utils\_contextlib.py", line 116, in decorate_context return func(*args, **kwargs) File "D:\论文\yolov5-master\detect.py", line 99, in run model = DetectMultiBackend(weights, de

Traceback (most recent call last): File "D:\联想安卓下载\yolov5-6.2\detect.py", line 257, in <module> main(opt) File "D:\联想安卓下载\yolov5-6.2\detect.py", line 252, in main run(**vars(opt)) File "D:\anaconda3\envs\taotaopytorch3\Lib\site-packages\torch\utils\_contextlib.py", line 116, in decorate_context return func(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^ File "D:\联想安卓下载\yolov5-6.2\detect.py", line 93, in run model = DetectMultiBackend(weights, device=device, dnn=dnn, data=data, fp16=half) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\联想安卓下载\yolov5-6.2\models\common.py", line 330, in __init__ model = attempt_load(weights if isinstance(weights, list) else w, device=device, inplace=True, fuse=fuse) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\联想安卓下载\yolov5-6.2\models\experimental.py", line 80, in attempt_load ckpt = torch.load(attempt_download(w), map_location='cpu') # load ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\anaconda3\envs\taotaopytorch3\Lib\site-packages\torch\serialization.py", line 1524, in load raise pickle.UnpicklingError(_get_wo_message(str(e))) from None _pickle.UnpicklingError: Weights only load failed. This file can still be loaded, to do so you have two options, do those steps only if you trust the source of the checkpoint. (1) In PyTorch 2.6, we changed the default value of the weights_only argument in torch.load from False to True. Re-running torch.load with weights_only set to False will likely succeed, but it can result in arbitrary code execution. Do it only if you got the file from a trusted source. (2) Alternatively, to load with weights_only=True please check the recommended steps in the following error message. WeightsUnpickler error: Unsupported global: GLOBAL models.yolo.Model was not an allowed global by default. Please use to

YOLOv5 2025-6-5 torch 2.6.0+cu126 CUDA:0 (NVIDIA GeForce RTX 2060, 6144MiB) YOLOv5 2025-6-5 torch 2.6.0+cu126 CUDA:0 (NVIDIA GeForce RTX 2060, 6144MiB) Traceback (most recent call last): File "D:\custom\nongjiyuan\QtProject\src\process_image.py", line 155, in <module> main() File "D:\custom\nongjiyuan\QtProject\src\process_image.py", line 152, in main process.process_image(img, True, False, model_path_2, model2_data) File "D:\custom\nongjiyuan\QtProject\src\process_image.py", line 77, in process_image run( File "D:\software\anaconda3\envs\nongjiyuan\Lib\site-packages\torch\utils\_contextlib.py", line 116, in decorate_context return func(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^ File "D:\custom\nongjiyuan\QtProject\damage_detect\detect.py", line 97, in run model = DetectMultiBackend(weights, device=device, dnn=dnn, data=data, fp16=half) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\custom\nongjiyuan\QtProject\damage_detect\models\common.py", line 589, in __init__ model = attempt_load(weights if isinstance(weights, list) else w, map_location=device) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\custom\nongjiyuan\QtProject\damage_detect\models\experimental.py", line 96, in attempt_load ckpt = torch.load(attempt_download(w), map_location=map_location, weights_only=False) # load ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\software\anaconda3\envs\nongjiyuan\Lib\site-packages\torch\serialization.py", line 1471, in load return _load( ^^^^^^ File "D:\software\anaconda3\envs\nongjiyuan\Lib\site-packages\torch\serialization.py", line 1964, in _load result = unpickler.load() ^^^^^^^^^^^^^^^^ File "D:\software\anaconda3\envs\nongjiyuan\Lib\site-packages\torch\serialization.py", line 1953, in find_class return super().find_class(mod_name, name) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ ModuleNotFoundError: No module named 'ultralytics'

YOLOv5 2025-6-5 torch 2.6.0+cu126 CUDA:0 (NVIDIA GeForce RTX 2060, 6144MiB) YOLOv5 2025-6-5 torch 2.6.0+cu126 CUDA:0 (NVIDIA GeForce RTX 2060, 6144MiB) Traceback (most recent call last): File "D:\custom\nongjiyuan\QtProject\src\process_image.py", line 155, in <module> main() File "D:\custom\nongjiyuan\QtProject\src\process_image.py", line 152, in main process.process_image(img, True, False, model_path_2, model2_data) File "D:\custom\nongjiyuan\QtProject\src\process_image.py", line 77, in process_image run( File "D:\software\anaconda3\envs\nongjiyuan\Lib\site-packages\torch\utils\_contextlib.py", line 116, in decorate_context return func(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^ File "D:\custom\nongjiyuan\QtProject\damage_detect\detect.py", line 97, in run model = DetectMultiBackend(weights, device=device, dnn=dnn, data=data, fp16=half) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\custom\nongjiyuan\QtProject\damage_detect\models\common.py", line 589, in __init__ model = attempt_load(weights if isinstance(weights, list) else w, map_location=device) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\custom\nongjiyuan\QtProject\damage_detect\models\experimental.py", line 96, in attempt_load ckpt = torch.load(attempt_download(w), map_location=map_location) # load ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\software\anaconda3\envs\nongjiyuan\Lib\site-packages\torch\serialization.py", line 1470, in load raise pickle.UnpicklingError(_get_wo_message(str(e))) from None _pickle.UnpicklingError: Weights only load failed. This file can still be loaded, to do so you have two options, do those steps only if you trust the source of the checkpoint. (1) In PyTorch 2.6, we changed the default value of the weights_only argument in torch.load from False to True. Re-running torch.load with weights_only set to False will likely succeed, but it can result in arbitrary code execution. Do it only if you got the file from a trusted source. (2) Alternatively, to load with weights_only=True please check the recommended steps in the following error message. WeightsUnpickler error: Unsupported global: GLOBAL ultralytics.nn.tasks.DetectionModel was not an allowed global by default. Please use torch.serialization.add_safe_globals([DetectionModel]) or the torch.serialization.safe_globals([DetectionModel]) context manager to allowlist this global if you trust this class/function. Check the documentation of torch.load to learn more about types accepted by default with weights_only https://pytorch.org/docs/stable/generated/torch.load.html.

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