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.
transform_random_crop(
img,
size,
padding = NULL,
pad_if_needed = FALSE,
fill = 0,
padding_mode = "constant"
)A magick-image, array or torch_tensor.
(integer vector or integer): Desired output size. If size is
an integer vector of length 2 like c(h, w), output size will be matched
to this. If size is a bare integer, 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).
(integer vector or integer): Padding on each border. If a single integer is provided, this value is used to pad all borders. If an integer vector of length 2 is provided, it gives the padding on left/right and top/bottom respectively. If an integer vector of length 4 is provided, it gives the padding for the left, right, top and bottom borders respectively.
(logical): It will pad the image if smaller than the desired size to avoid raising an exception. Since cropping is done after padding, the padding seems to be done at a random offset.
(numeric vector or numeric): Pixel fill value for constant fill.
Default is 0. If a numeric vector of length 3, it is used to fill R, G,
B channels respectively. This value is only used when the padding_mode
is constant. Only integer values are supported for Tensors.
(character): Type of padding. Should be: constant,
edge, reflect or symmetric. Default is constant. Mode symmetric
is not yet supported for Tensor inputs.
constant: pads with a constant value, this value is specified with fill
edge: pads with the last value on the edge of the image
reflect: pads with reflection of image (without repeating the last
value on the edge) padding [1, 2, 3, 4] with 2 elements on both sides
in reflect mode will result in [3, 2, 1, 2, 3, 4, 3, 2]
symmetric: pads with reflection of image (repeating the last value on
the edge) padding [1, 2, 3, 4] with 2 elements on both sides in
symmetric mode will result in [2, 1, 1, 2, 3, 4, 4, 3]