10/30/2023 0 Comments Pil image convert gaussianconstant: pads with a constant value, this value is specified with fill.Should be: constant, edge, reflect or symmetric. Only int or str or tuple value is supported for PIL Image. Only number is supported for torch Tensor. This value is only used when the padding_mode is constant. Length 3, it is used to fill R, G, B channels respectively. fill ( number or str or tuple) – Pixel fill value for constant fill.In torchscript mode padding as single int is not supported, use a sequence of length 1. This is the padding for the left, top, right and bottom borders respectively. On left/right and top/bottom respectively. If sequence of length 2 is provided this is the padding padding ( int or sequence) – Padding on each border.To have shape, where … means at most 2 leading dimensions for mode reflect and symmetric,Īt most 3 leading dimensions for mode edge,Īnd an arbitrary number of leading dimensions for mode constant Parameters: Pad the given image on all sides with the given “pad” value. Pad ( padding, fill=0, padding_mode='constant' ) ¶ Img ( PIL Image or Tensor) – Image to be converted to grayscale.Ĭlass ansforms. If num_output_channels = 3 : returned image is 3 channel with r = g = b.If num_output_channels = 1 : returned image is single channel.Num_output_channels ( int) – (1 or 3) number of channels desired for output image To have shape, where … means an arbitrary number of leading dimensions Parameters: Image can be PIL Image or TensorĬlass ansforms. mean ( 1 ) # avg over crops forward ( img ) ¶ Parameters: view ( - 1, c, h, w )) # fuse batch size and ncrops > result_avg = result. > transform = Compose ()) # returns a 4D tensor > ]) > #In your test loop you can do the following: > input, target = batch # input is a 5d tensor, target is 2d > bs, ncrops, c, h, w = input. To have shape, where … means an arbitrary number of leading FiveCrop ( size ) ¶Ĭrop the given image into four corners and the central crop. The parameters used to apply the randomized transformĬlass ansforms. Pass None to turn off the transformation. hue ( tuple of python:float ( min, max ), optional) – The range from which the hue_factor is chosen uniformly. ![]()
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