Traceback (most recent call last): File "D:\yolov7-lpr\yolov7_plate-master\models\lprnet_plate_recognition.py", line 50, in <module> out_data = model(img_tensor) # out_data.shape == [1, 68, 18] File "D:\Anaconda\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl return forward_call(*input, **kwargs) File "D:\yolov7-lpr\yolov7_plate-master\models\LPRNet.py", line 62, in forward x = layer(x) File "D:\Anaconda\lib\site-packages\torch\nn\modules\module.py", line 1102, in _call_impl return forward_call(*input, **kwargs) File "D:\Anaconda\lib\site-packages\torch\nn\modules\conv.py", line 446, in forward return self._conv_forward(input, self.weight, self.bias) File "D:\Anaconda\lib\site-packages\torch\nn\modules\conv.py", line 442, in _conv_forward return F.conv2d(input, weight, bias, self.stride, TypeError: conv2d() received an invalid combination of arguments - got (Tensor, Parameter, Parameter, tuple, tuple, tuple, int), but expected one of: * (Tensor input, Tensor weight, Tensor bias, tuple of ints stride, tuple of ints padding, tuple of ints dilation, int groups) didn't match because some of the arguments have invalid types: (Tensor, !Parameter!, !Parameter!, !tuple!, !tuple!, !tuple!, int) * (Tensor input, Tensor weight, Tensor bias, tuple of ints stride, str padding, tuple of ints dilation, int groups) didn't match because some of the arguments have invalid types: (Tensor, !Parameter!, !Parameter!, !tuple!, !tuple!, !tuple!, int)

这个错误是由于在使用`F.conv2d()`函数时传入了一个`Parameter`类型的参数，但是这个函数期望传入的是一个`Tensor`类型参数。

可能的原因是在模型定义时使用了`nn.Parameter`来定义权重或偏置，而在调用模型进行推理时未将其转换为`Tensor`类型。

解决方法是将权重和偏置参数转换为`Tensor`类型，可以使用`nn.Parameter.detach()`方法将其转换为`Tensor`类型。具体来说，可以在模型定义中将`nn.Parameter`改为`nn.Tensor`，或者在模型调用时使用`nn.Parameter.detach()`方法转换为`Tensor`类型。

相关问题

Traceback (most recent call last): File "D:/yolov7-lpr/yolov7_plate-master/plate_recognition/lprnet_plate_recognition.py", line 41, in <module> result = lprnet_plate_recognition("D:\yolov7-lpr\yolov7_plate-master\imgs\police.jpg", "D:\yolov7-lpr\yolov7_plate-master\weights\Final_LPRNet_model.pth") File "D:/yolov7-lpr/yolov7_plate-master/plate_recognition/lprnet_plate_recognition.py", line 10, in lprnet_plate_recognition model.eval() AttributeError: 'collections.OrderedDict' object has no attribute 'eval'这段报错是什么意思

这报错意味着你的代码中使用了一个名为"model"的对象，但它是一个有序字典（OrderedDict）类型的对象，该类型没有名为"eval"的属性。这通常表示你的模型没有被正确加载或初始化。你需要检查你的代码，确保正确加载了你的模型，并且确保模型是PyTorch的nn.Module类型的对象，才能调用eval()方法。

Traceback (most recent call last): File "D:/yolov7-lpr/yolov7_plate-master/detect_rec_plate.py", line 9, in <module> from models.experimental import attempt_load File "D:\yolov7-lpr\yolov7_plate-master\models\experimental.py", line 7, in <module>

这个错误提示不够完整，无法判断具体原因。但是根据错误提示的第9行和第7行可以判断，这段代码引用了自定义的模块，并且该自定义模块依赖于其他模块或库。可能是你没有正确安装或配置这些依赖项导致的错误。建议你检查一下依赖项是否都已经正确安装，并且确认路径是否正确。如果问题仍然存在，你可以提供更详细的错误信息，以便更好地诊断问题。