DPDD

The DPDD dataset (Dual-Pixel Defocus Deblurring) provides paired defocused and all-in-focus images, along with dual-pixel sub-aperture views, for training and evaluating models on defocus-deblurring tasks. Each scene includes a defocused image captured with a wide aperture, its left/right dual-pixel views, and a corresponding sharp image captured with a small aperture.

This is a Hugging Face compatible version created from the original dataset released with the paper Defocus Deblurring Using Dual-Pixel Data (ECCV 2020) by Abdullah Abuolaim and Michael S. Brown.

The original repository is licensed under the MIT License, and so does this version. When using the dataset, please cite the original paper as requested by the authors.

Usage

from datasets import load_dataset

ds = load_dataset("JacobLinCool/DPDD")
print(ds)
# DatasetDict({
#     train: Dataset({
#         features: ['source', 'target'],
#         num_rows: 350
#     })
#     val: Dataset({
#         features: ['source', 'target'],
#         num_rows: 74
#     })
#     test: Dataset({
#         features: ['source', 'target'],
#         num_rows: 76
#     })
# })

print(ds["train"][0])
# {'source': <PIL.PngImagePlugin.PngImageFile image mode=RGB size=1680x1120>,
#  'target': <PIL.PngImagePlugin.PngImageFile image mode=RGB size=1680x1120>}