Resize image and make it fit for network. Args: img (array): image Returns: tensor: data ready for network

same as matlab rgb2ycbcr only_y: only return Y channel Input: uint8, [0, 255] float, [0, 1]

Scale the parameters of a module and return it.

split the large images from original_dataroot into small overlapped images with size (p_size)x(p_size), and save them into taget_dataroot; on

blur + bicubic downsampling Args: x: HxWxC image, [0, 1] k: hxw, double sf: down-scale factor Return: downsam

blur + bicubic downsampling Args: x: HxWxC image, [0, 1] k: hxw, double sf: down-scale factor Return: downsam

Performs a single optimization step. Args: closure (callable, optional): A closure that reevaluates the model and

Converts a torch Tensor into an image Numpy array of BGR channel order Input: 4D(B,(3/1),H,W), 3D(C,H,W), or 2D(H,W), any range, RGB channel

Write depth map to pfm and png file. Args: path (str): filepath without extension depth (array): depth

same as matlab ycbcr2rgb Input: uint8, [0, 255] float, [0, 1]