Charbonnier Loss (L1)

Initialize a basic Conv LSTM cell. Args: shape: int tuple thats the height and width of the hidden states h and c() filter_size: int t

[summary] Class representing a motion blur kernel of a given intensity. [description] Keyword Arguments: size {tuple} -- Size

The autoencoder model to enhance images in an image to image translation fashion. This code is built on top of the vit-pytorch code https://g

pytorch torch.nn.Linear wrapper Notes --------------------------------------------------------------------- use partial() to wrap activati

Initialize a basic Conv LSTM cell. Args: filter_size: int that is the height and width of the filters num_features: int thats the num

For test dataset, specify `group_file` parameter to target TXT file data_augmentation = None black_edge_crop = None flip = None

For test dataset, specify `group_file` parameter to target TXT file data_augmentation = None black_edge_crop = None flip = None

Gradient Histogram Loss

A progress bar which can print the progress modified from https://github.com/hellock/cvbase/blob/master/cvbase/progress.py