basicsr.data.transforms

basicsr.data.transforms.augment(imgs, hflip=True, rotation=True, flows=None, return_status=False)[source]

Augment: horizontal flips OR rotate (0, 90, 180, 270 degrees).

We use vertical flip and transpose for rotation implementation. All the images in the list use the same augmentation.

Parameters:

  • imgs (list[ndarray] | ndarray) – Images to be augmented. If the input is an ndarray, it will be transformed to a list.

  • hflip (bool) – Horizontal flip. Default: True.

  • rotation (bool) – Ratotation. Default: True.

  • (list[ndarray] (flows) – Flows to be augmented. If the input is an ndarray, it will be transformed to a list. Dimension is (h, w, 2). Default: None.

  • return_status (bool) – Return the status of flip and rotation. Default: False.

Returns:

Augmented images and flows. If returned

results only have one element, just return ndarray.

Return type:

list[ndarray] | ndarray

basicsr.data.transforms.img_rotate(img, angle, center=None, scale=1.0)[source]

Rotate image.

Parameters:

  • img (ndarray) – Image to be rotated.

  • angle (float) – Rotation angle in degrees. Positive values mean counter-clockwise rotation.

  • center (tuple[int]) – Rotation center. If the center is None, initialize it as the center of the image. Default: None.

  • scale (float) – Isotropic scale factor. Default: 1.0.

basicsr.data.transforms.mod_crop(img, scale)[source]

Mod crop images, used during testing.

Parameters:

  • img (ndarray) – Input image.

  • scale (int) – Scale factor.

Returns:

Result image.

Return type:

ndarray

basicsr.data.transforms.paired_random_crop(img_gts, img_lqs, gt_patch_size, scale, gt_path=None)[source]

Paired random crop. Support Numpy array and Tensor inputs.

It crops lists of lq and gt images with corresponding locations.

Parameters:

  • img_gts (list[ndarray] | ndarray | list[Tensor] | Tensor) – GT images. Note that all images should have the same shape. If the input is an ndarray, it will be transformed to a list containing itself.

  • img_lqs (list[ndarray] | ndarray) – LQ images. Note that all images should have the same shape. If the input is an ndarray, it will be transformed to a list containing itself.

  • gt_patch_size (int) – GT patch size.

  • scale (int) – Scale factor.

  • gt_path (str) – Path to ground-truth. Default: None.

Returns:

GT images and LQ images. If returned results

only have one element, just return ndarray.

Return type:

list[ndarray] | ndarray