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Btw, I'm currently using Concat dataset to do the job. grid_samplers = []
for i in range(len(subjects)):
grid_sampler = tio.inference.GridSampler(
subjects[i],
self.patch_size,
(4,4,4),
)
grid_samplers.append(grid_sampler)
return torch.utils.data.ConcatDataset(grid_samplers) But I was wondering maybe there is already some more elegant way of doing this? |
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Hi Fernando and everyone,
Is there any way by which I can get all the patches with certain overlap (similar to Grid sampler) with Patch Queue?
Or is there something like a "Queue of Grid Samplers" OR "Grid sampler of Subjects"?
My motivation is to be able to use during validate stage, so I'm not gonna be using Grid aggregator. But I need to be able to sample all the patches, and not randomly.
Any suggestions?
Thanks.
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