CBSD68
- class deepinv.datasets.CBSD68(root: str, download: bool = False, transform: Callable | None = None)[source]
Bases:
Dataset
Dataset for CBSBD68.
Color BSD68 dataset for image restoration benchmarks is part of The Berkeley Segmentation Dataset and Benchmark. It is used for measuring image restoration algorithms performance. It contains 68 images.
Raw data file structure:
self.root --- data-00000-of-00001.arrow -- dataset_info.json -- state.json
This dataset wraps the huggingface version of the dataset. HF source : https://huggingface.co/datasets/deepinv/CBSD68
- Parameters:
root (str) – Root directory of dataset. Directory path from where we load and save the dataset.
download (bool) – If
True
, downloads the dataset from the internet and puts it in root directory. If dataset is already downloaded, it is not downloaded again. Default at False.transform (callable, optional) – A function/transform that takes in a PIL image and returns a transformed version. E.g,
torchvision.transforms.RandomCrop
- Examples:
Instanciate dataset and download raw data from the Internet
>>> import shutil >>> from deepinv.datasets import CBSD68 >>> dataset = CBSD68(root="CBSB68", download=True) # download raw data at root and load dataset Dataset has been successfully downloaded. >>> print(dataset.check_dataset_exists()) # check that raw data has been downloaded correctly True >>> print(len(dataset)) # check that we have 68 images 68 >>> shutil.rmtree("CBSB68") # remove raw data from disk