R/transforms-generics.R
transform_random_resized_crop.RdCrop the given image to a random size and aspect ratio. The image can be a
Magick Image or a Tensor, in which case it is expected to have
[..., H, W] shape, where ... means an arbitrary number of leading
dimensions
A magick-image, array or torch_tensor.
(sequence or int): Desired output size. If size is a sequence like c(h, w), output size will be matched to this. If size is an int, smaller edge of the image will be matched to this number. i.e, if height > width, then image will be rescaled to (size * height / width, size).
(tuple of float): range of size of the origin size cropped
(tuple of float): range of aspect ratio of the origin aspect ratio cropped.
(int, optional) Desired interpolation. An integer
0 = nearest, 2 = bilinear, and 3 = bicubic or a name from
magick::filter_types().
A crop of random size (default: of 0.08 to 1.0) of the original size and a random aspect ratio (default: of 3/4 to 4/3) of the original aspect ratio is made. This crop is finally resized to given size. This is popularly used to train the Inception networks.
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_linear_transformation(),
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_rotation(),
transform_random_vertical_flip(),
transform_resize(),
transform_resized_crop(),
transform_rgb_to_grayscale(),
transform_rotate(),
transform_ten_crop(),
transform_to_tensor(),
transform_vflip()