| transform_linear_transformation {torchvision} | R Documentation |
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 |
transformation_matrix |
(Tensor): tensor |
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 transforms:
transform_adjust_brightness(),
transform_adjust_contrast(),
transform_adjust_gamma(),
transform_adjust_hue(),
transform_adjust_saturation(),
transform_affine(),
transform_center_crop(),
transform_color_jitter(),
transform_convert_image_dtype(),
transform_crop(),
transform_five_crop(),
transform_grayscale(),
transform_hflip(),
transform_normalize(),
transform_pad(),
transform_perspective(),
transform_random_affine(),
transform_random_apply(),
transform_random_choice(),
transform_random_crop(),
transform_random_erasing(),
transform_random_grayscale(),
transform_random_horizontal_flip(),
transform_random_order(),
transform_random_perspective(),
transform_random_resized_crop(),
transform_random_rotation(),
transform_random_vertical_flip(),
transform_resize(),
transform_resized_crop(),
transform_rgb_to_grayscale(),
transform_rotate(),
transform_ten_crop(),
transform_to_tensor(),
transform_vflip()