Comments (1)
Your volumes (input to resize_sample
) are expected to be 4D arrays of shape [n_slices x slice_height x slice_width x n_channels].
Masks should be 3D arrays of shape [n_slices x slice_height x slice_width].
from brain-segmentation-pytorch.
Related Issues (20)
- Reproducibility issue HOT 5
- how to train on my dataset HOT 5
- in_channels parameter change causes size mismatch HOT 5
- Retraining on own dataset HOT 1
- ValueError: Sample larger than population or is negative HOT 2
- Example on Colab not segmenting the tumor HOT 13
- A puzzle about the code HOT 1
- How can I run the docker container if my GPU isn't nvidia
- Very large images on my dataset
- Run on the test data HOT 3
- Can I run the code on test folder without the masks??
- google colab
- how can I apply other loss functions
- IoU of the model
- Negative loss value HOT 3
- After UNet Inference, how to overlay / superimpose the different size predicted masks to the original image size?
- dice
- Error
- manifest for nvidia/cuda:10.0-cudnn7-devel-ubuntu18.04 not found: manifest unknown: manifest unknown
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from brain-segmentation-pytorch.