output = torch.squeeze(model(img)) predict = torch.softmax(output, dim=0) predict_cla = torch.argmax(predict).numpy() print(class_indict[str(predict_cla)], predict[predict_cla].numpy()) plt.show() 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. ...
TypeError: img should be PIL Image. Got <class ‘numpy.ndarray‘> 所以我们要在转换中先转换为PIL格式。 transforms.ToPILImage() https://blog.csdn.net/wacebb/article/details/108003306 https://blog.csdn.net/qq_40178291/article/details/101108327 PIL.JpegImagePlugin.JpegImageFile与numpy.ndarray的相互...
torch.onnx.export(model, args, f, export_params=True, verbose=False, training=<TrainingMode.EVAL: 0>, input_names=None, output_names=None, operator_export_type=<OperatorExportTypes.ONNX: 0>, opset_version=None, do_constant_folding=True, dynamic_axes=None, keep_initializers_as_inputs=None...
🐛 Describe the bug The expected output is a (1, 224, 224) tensor. When input is an numpy.ndarray, transforms.Resize raises TypeError: Unexpected type <class 'numpy.ndarray'> While transforms.v2.Resize silently runs the code without resiz...
print(f"Epochs [{epoch}/{epochs}],Steps [{i}/{steps}], Loss:{loss.asnumpy():.4f}, Acc:{acc:.2f}%%") TypeError: unsupported format string passed to numpy.ndarray.format 我尝试忽略这个错误继续往下运行试试 xiefangqi 3年前 啊这,忘了忘了。
numpy() return voxels, coordinates, num_points 重点看spconv的类VoxelGeneratorV2 位于:spconv/utils/__init__.py class VoxelGeneratorV2: def __init__(self, voxel_size, point_cloud_range, max_num_points, max_voxels=20000, full_mean=False, block_filtering=False, block_factor=8, block_size=...
import numpy as np import torchvision from torchvision import datasets, models, transforms import matplotlib.pyplot as plt import time import os import copy # 定义模型 class TheModelClass(nn.Module): def __init__(self): super(TheModelClass, self).__init__() ...
"device: Optional[DeviceLikeType] = None", "copy: Optional[_bool] = None", "requires_grad: _bool = False", ] ) ) ], "from_numpy": ["def from_numpy(ndarray) -> Tensor: ..."], "frombuffer": [ "def frombuffer({}) -> Tensor: ...".format( ...
[2],# which is the traceback, because otherwise you will run into the traceback# reference cycle problem, i.e., the traceback holding reference to the frame,# and the frame (which holds reference to all the object in its temporary scope)# holding reference the traceback.classExcepti...
We read every piece of feedback, and take your input very seriously. Include my email address so I can be contacted Cancel Submit feedback Saved searches Use saved searches to filter your results more quickly Cancel Create saved search Sign in Sign up Reseting focus {...