Support OrderedDict for yaml. Returns: tuple: yaml Loader and Dumper.

Calculate factor corresponding to quality Args: quality(float): Quality for jpeg compression. Returns: float: Compression f

Return the corresponding reduction function.

Get human readable file size. Args: size (int): File size. suffix (str): Suffix. Default: 'B'. Return: str: Formatte

Load yaml file or string. Args: f (str): File path or a python string. Returns: dict: Loaded dict.

获取所有图像路径

Get the initial lr, which is set by the scheduler.

Initialize slurm distributed training environment. If argument ``port`` is not specified, then the master port will be system environment var

Print keys with different name or different size when loading models. 1. Print keys with different names. 2. If strict=False, print t

Set learning rate for warm-up. Args: lr_groups_l (list): List for lr_groups, each for an optimizer.

Calculate SSIM (structural similarity) for one channel images. It is called by func:`calculate_ssim`. Args: img (ndarray): Images wi

Calculate SSIM (structural similarity) (PyTorch version). It is called by func:`calculate_ssim_pt`. Args: img (Tensor): Images with

Update the best metric results.

Convert a BGR image to YCbCr image. The bgr version of rgb2ycbcr. It implements the ITU-R BT.601 conversion for standard-definition telev

Check resume states and pretrain_network paths. Args: opt (dict): Options. resume_iter (int): Resume iteration.

Compute features. Args: block (ndarray): 2D Image block. Returns: list: Features with length of 18.

Initialize network weights. Args: module_list (list[nn.Module] | nn.Module): Modules to be initialized. scale (float): Scale init

Dequantize an array. Args: arr (ndarray): Input array. min_val (scalar): Minimum value to be clipped. max_val (scalar): M

Recover from quantized flow. Args: dx (ndarray): Quantized dx. dy (ndarray): Quantized dy. max_val (float): Maximum value