Source code for torchio.data.sampler.uniform
from typing import Generator
from typing import Optional
import torch
from ...data.subject import Subject
from .sampler import RandomSampler
[docs]
class UniformSampler(RandomSampler):
"""Randomly extract patches from a volume with uniform probability.
Args:
patch_size: See :class:`~torchio.data.PatchSampler`.
"""
def get_probability_map(self, subject: Subject) -> torch.Tensor:
return torch.ones(1, *subject.spatial_shape)
def _generate_patches(
self,
subject: Subject,
num_patches: Optional[int] = None,
) -> Generator[Subject, None, None]:
valid_range = subject.spatial_shape - self.patch_size
patches_left = num_patches if num_patches is not None else True
while patches_left:
i, j, k = tuple(int(torch.randint(x + 1, (1,)).item()) for x in valid_range)
index_ini = i, j, k
yield self.extract_patch(subject, index_ini)
if num_patches is not None:
patches_left -= 1