PatchDataset#

class deepinv.datasets.PatchDataset(imgs, patch_size=6, stride=1, transform=None, shape=(-1,))[source]#

Builds the dataset of all patches from a tensor of images.

Parameters:

imgs (torch.Tensor) – Tensor of images of shape (B, C, H, W).
patch_size (int | tuple[int, int]) – size of patches to extract. If int, the same value is used for height and width.
stride (int | tuple[int, int]) – stride between patches. If int, the same value is used for height and width.
transform (Callable) – data augmentation. A callable object, set to None for no augmentation.
shape (tuple) – shape of the returned tensor. If None, returns (C, h, w) where h and w are height and width of the patch. The default shape is (-1,) (flatten).

Examples using `PatchDataset`:#