Comments (2)
@iliasprc Okay, I have solved this problem, thank you!
from medicalzoopytorch.
Hello,
The param load=True uses presegmented patches from medical images that you have created when load=False.
I think if you move the line ( self.affine=....) above the if loop the code should work fine
from medicalzoopytorch.
Related Issues (20)
- Version 1.0
- Something trouble with inference.py HOT 4
- About img_nii shape in method 'load_medical_image' HOT 1
- Sharing pre-trained model weights.
- RuntimeError: Expected 5-dimensional input for 5-dimensional weight 8 4 3 3, but got 4-dimensional input of size [4, 256, 64, 64] instead HOT 8
- Example command lines for running COVID segmentation example?
- AttributeError: 'Namespace' object has no attribute 'loadData' HOT 1
- question about train HOT 6
- About the format of using my own data
- About
- MICCAI_BraTS_2018_Data_Training/brats2018-list-' + mode + '-samples-' + str(samples) + '.txt' HOT 1
- Low validation DSC when training on Brats2018 HOT 3
- Hi, How to get this kind of results using highresnet?
- The OutputTransition of the VNet model exists with one more than Conv3D
- full_volume.shape ==> "None type has no attribute shape" HOT 1
- Data size into the model
- 没看懂数据的结构
- The error message "Expected 5-dimensional input for 5-dimensional weight [8, 3, 3, 3, 3], but got 4-dimensional input of size [4, 384, 128, 48] instead" indicates that there is a mismatch between the expected input dimensions (5-dimensional) and the actual input dimensions provided (4-dimensional). HOT 2
- Data directory structure HOT 1
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