transform_linear_transformation: Transform a tensor image with a square transformation matrix...

In torchvision: Models, Datasets and Transformations for Images

Transform a tensor image with a square transformation matrix and a mean_vector computed offline

Description

Given transformation_matrix and mean_vector, will flatten the torch_tensor and subtract mean_vector from it which is then followed by computing the dot product with the transformation matrix and then reshaping the tensor to its original shape.

Usage

transform_linear_transformation(img, transformation_matrix, mean_vector)

Arguments

img	A magick-image, array or torch_tensor.
transformation_matrix	(Tensor): tensor ⁠[D x D]⁠, D = C x H x W.
mean_vector	(Tensor): tensor D, D = C x H x W.

Applications

whitening transformation: Suppose X is a column vector zero-centered data. Then compute the data covariance matrix ⁠[D x D]⁠ with torch.mm(X.t(), X), perform SVD on this matrix and pass it as transformation_matrix.

See Also

Other unitary_transforms: transform_adjust_brightness(), transform_adjust_contrast(), transform_adjust_gamma(), transform_adjust_hue(), transform_adjust_saturation(), transform_affine(), transform_center_crop(), transform_convert_image_dtype(), transform_crop(), transform_grayscale(), transform_hflip(), transform_normalize(), transform_pad(), transform_perspective(), transform_resize(), transform_rgb_to_grayscale(), transform_rotate(), transform_to_tensor(), transform_vflip()

torchvision documentation built on Nov. 6, 2025, 9:07 a.m.