Closed kimtaeuk-AI closed 2 years ago
Hi kimtaeuk-AI, the transforms can be customized. If you would not like to use Spacingd, you can remove that transform. But the current GPUs are difficult to handle [480, 480, 360] as input size. The tutorial cropped the CT volumes into [96, 96, 96] using the RandCropByNegPosPair. You can customized the crop size as the input shape and modify the model accordingly.
RandCropByPosNegLabeld(
keys=["image", "label"],
label_key="label",
spatial_size=(96, 96, 96),
pos=1,
neg=1,
num_samples=4,
image_key="image",
image_threshold=0,
),
You can try remove the Spacingd, the original data shape will be remained and use the [96,96,96] as the crop size. Thank you.
Hellow tangy5, :) Thanks to you, the problem was solved. Have a nice day~!
My data image shape [480,480,360] but during training process my data shape transform the [121,121,191].
How to hold my data shape during the training process and test process.