I want to train a 3D network by using 3D images (
.nii.gz format). So the first step, I use the
nibabel lib to load 3d images in my dataloader class (see following codes).
import nibabel as nib ... class Data(Dataset): def __init__(...): ... def __getitem__(self, idx): image = nib.load(img_path) label = nib.load(label_path) image = torch.from_numpy(image).unsqueeze(0) label = torch.from_numpy(label).unsqueeze(0) return image, label
The I imported the
Data class to load training sets in my model training script. However, magical bug have appeared. That is, I got
ValueError: some of the strides of a given numpy array are negative. This is currently not supported, but will be added in future releases. The location where the bug appears is located to:
image = torch.from_numpy(image).unsqueeze(0)
This bug may appear when I first train and when I train some iterations, which means it doesn’t fix. My PyTorch version is
0.4.1. I am grateful for any suggestions.