light_side.datasets#

An abstract class representing a Dataset.

All datasets that represent a map from keys to data samples should subclass it. All subclasses should overwrite __getitem__(), supporting fetching a data sample for a given key. Subclasses could also optionally overwrite __len__(), which is expected to return the size of the dataset by many Sampler implementations and the default options of DataLoader.

Note

DataLoader by default constructs a index sampler that yields integral indices. To make it work with a map-style dataset with non-integral indices/keys, a custom sampler must be provided.

class ZeroDCE(root_dir=None, phase='train', transforms=None, **kwargs)[source]#

ZeroDCE is a dataset mentioned in the paper and in the original implementation.

_check_exists()[source]#

Check the Root directory is exists

Return type

bool

_is_protocol = False#
static _load_image(img_file_path)#
Return type

ndarray

_split_dataset(phase)[source]#
Return type

Tuple

download()[source]#

Download the dataset from the internet

Return type

None