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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. Args: size: expected output size of each edge scale: range of size of the origin size cropped ratio: range of aspect ratio of the origin aspect ratio cropped interpolation: Default: PIL.Image.BILINEAR g{Gz??g?gUUUUUU?r,cCsxt|ttfrt||_n ||f|_|d|dksD|d|dkrNtd|dkr^t|_n t||_||_ ||_ dS)Nrr;z"range should be of kind (min, max)random) r<listtuplerBwarningswarn_RANDOM_INTERPOLATION interpolationr scaleratio)rrBrOrPrNrrr r&s     z*RandomResizedCropAndInterpolation.__init__cCsLt|\}}||}tdD]}tj||}t|dt|df}ttj|} tt t || } tt t || } | |kr| |krt d|| } t d|| } | | | | fSq||}|t |kr|} tt | t |} n0|t |kr |} tt | t |} n|} |} || d} || d} | | | | fS)aGet parameters for ``crop`` for a random sized crop. 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(size={0}z , scale={0}css|]}t|dVqdSNrX)r/srrr sz=RandomResizedCropAndInterpolation.__repr__..z , ratio={0}css|]}t|dVqdSrorq)r/rrrr rssz, interpolation={0})) r<rNrJrIjoinr __class__r"formatrBrOrPrZinterpolate_str format_stringrrr __repr__s z*RandomResizedCropAndInterpolation.__repr__N)rErGr, r"r#r$r)r& staticmethodrer!rzrrrr r us  *constant)r] output_sizefill padding_modereturnc Cst|}|\}}t|\}}}||ks0||kr||krD||dnd||krZ||dnd||krt||ddnd||kr||ddndg} tj|| ||d}t|\}}}||kr||kr|Stt||d} tt||d} t|| | ||S)akCenter crops and/or pads the given image. If the image is torch Tensor, it is expected to have [..., H, W] shape, where ... means an arbitrary number of leading dimensions. If image size is smaller than output size along any edge, image is padded with 0 and then center cropped. Args: img (PIL Image or Tensor): Image to be cropped. output_size (sequence or int): (height, width) of the crop box. If int or sequence with single int, it is used for both directions. fill (int, Tuple[int]): Padding color Returns: PIL Image or Tensor: Cropped image. rrr;rrg@)rDr'get_dimensionspadr?rXcrop) r]r~rrZ crop_heightZ crop_width_ image_height image_width padding_ltrbZcrop_topZ crop_leftrrr rs cs`eZdZdZd eeeefeeeeeeffedfdd Z ddZ ed d d Z Z S) ra/Crops the given image at the center. If the image is torch Tensor, it is expected to have [..., H, W] shape, where ... means an arbitrary number of leading dimensions. If image size is smaller than output size along any edge, image is padded with 0 and then center cropped. Args: size (sequence or int): Desired output size of the crop. If size is an int instead of sequence like (h, w), a square crop (size, size) is made. If provided a sequence of length 1, it will be interpreted as (size[0], size[0]). rr}rBrrcs$tt||_||_||_dSr%superr&rDrBrrrrBrrrvrr r&s  zCenterCropOrPad.__init__cCst||j|j|jdS) Args: img (PIL Image or Tensor): Image to be cropped. 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