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# ten_crop

torchvision.transforms.functional.ten_crop(img: Tensor, size: List[int], vertical_flip: bool = False) → Tuple[Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor]

  Generate ten cropped images from the given image. Crop the given image into four corners and the central crop plus the flipped version of these (horizontal flipping is used by default). If the image is torch Tensor, it is expected to have […, H, W] shape, where … means an arbitrary number of leading dimensions

  Note

  This transform returns a tuple of images and there may be a mismatch in the number of inputs and targets your `Dataset` returns.

  Parameters:

    - img (PIL Image or Tensor) – Image to be cropped.

    - size (sequence or int) – Desired output size of the crop. If size is an int instead of sequence like (h, w), a square crop (size, size) is made. If provided a sequence of length 1, it will be interpreted as (size[0], size[0]).

    - vertical_flip (bool) – Use vertical flipping instead of horizontal

  Returns:

    tuple (tl, tr, bl, br, center, tl_flip, tr_flip, bl_flip, br_flip, center_flip) Corresponding top left, top right, bottom left, bottom right and center crop and same for the flipped image.

  Return type:

    tuple

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