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.

r""" Parameters: `processor (`dict` of `AttentionProcessor` or `AttentionProcessor`): The instantiated processor c

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

Save the current parameters for restoring later. Args: parameters: Iterable of `torch.nn.Parameter`; the parameters to be

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

Expects a batch of images and depth as input batch["image"].shape : batch_size, c, h, w batch["depth"].shape : batch_size, 1,

Expects a batch of images and depth as input batch["image"].shape : batch_size, c, h, w batch["depth"].shape : batch_size, 1,

Unfreezes all the parameters of all the ModuleDicts children that are exclusively used for the given bin configuration

Write depth map to png file. Args: path (str): filepath without extension depth (array): depth grayscale (bool): use a gr

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

Write pfm file. Args: path (str): pathto file image (array): data scale (int, optional): Scale. Defaults to 1.

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