transform_random_crop: Crop the given image at a random location

In torchvision: Models, Datasets and Transformations for Images

Crop the given image at a random location

Description

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.

Usage

transform_random_crop(
  img,
  size,
  padding = NULL,
  pad_if_needed = FALSE,
  fill = 0,
  padding_mode = "constant"
)

Arguments

img	A magick-image, array or torch_tensor.
size	(sequence or int): Desired output size. If size is a sequence like (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).
padding	(int or tuple or list): Padding on each border. If a single int is provided this is used to pad all borders. If tuple of length 2 is provided this is the padding on left/right and top/bottom respectively. If a tuple of length 4 is provided this is the padding for the left, right, top and bottom borders respectively.
pad_if_needed	(boolean): 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.
fill	(int or str or tuple): Pixel fill value for constant fill. Default is 0. If a tuple 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 int value is supported for Tensors.
padding_mode	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]⁠

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_linear_transformation(), transform_normalize(), transform_pad(), transform_perspective(), transform_random_affine(), transform_random_apply(), transform_random_choice(), 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()

torchvision documentation built on June 22, 2024, 11:25 a.m.