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"""Set5 dataset: An evaluation dataset for the image super resolution task""" |
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import datasets |
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from pathlib import Path |
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_CITATION = """ |
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@article{bevilacqua2012low, |
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title={Low-complexity single-image super-resolution based on nonnegative neighbor embedding}, |
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author={Bevilacqua, Marco and Roumy, Aline and Guillemot, Christine and Alberi-Morel, Marie Line}, |
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year={2012}, |
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publisher={BMVA press} |
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} |
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""" |
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_DESCRIPTION = """ |
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Set5 is a evaluation dataset with 5 RGB images for the image super resolution task. |
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""" |
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_HOMEPAGE = "http://people.rennes.inria.fr/Aline.Roumy/results/SR_BMVC12.html" |
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_LICENSE = "UNK" |
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_DL_URL = "https://huggingface.co./datasets/eugenesiow/Set5/resolve/main/data/" |
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_DEFAULT_CONFIG = "bicubic_x2" |
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_DATA_OPTIONS = { |
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"bicubic_x2": { |
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"hr": _DL_URL + "Set5_HR.tar.gz", |
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"lr": _DL_URL + "Set5_LR_x2.tar.gz", |
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}, |
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"bicubic_x3": { |
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"hr": _DL_URL + "Set5_HR.tar.gz", |
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"lr": _DL_URL + "Set5_LR_x3.tar.gz", |
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}, |
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"bicubic_x4": { |
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"hr": _DL_URL + "Set5_HR.tar.gz", |
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"lr": _DL_URL + "Set5_LR_x4.tar.gz", |
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} |
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} |
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class Set5Config(datasets.BuilderConfig): |
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"""BuilderConfig for Set5.""" |
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def __init__( |
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self, |
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name, |
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hr_url, |
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lr_url, |
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**kwargs, |
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): |
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if name not in _DATA_OPTIONS: |
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raise ValueError("data must be one of %s" % _DATA_OPTIONS) |
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super(Set5Config, self).__init__(name=name, version=datasets.Version("1.0.0"), **kwargs) |
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self.hr_url = hr_url |
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self.lr_url = lr_url |
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class Set5(datasets.GeneratorBasedBuilder): |
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"""Set5 dataset for single image super resolution evaluation.""" |
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BUILDER_CONFIGS = [ |
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Set5Config( |
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name=key, |
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hr_url=values['hr'], |
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lr_url=values['lr'] |
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) for key, values in _DATA_OPTIONS.items() |
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] |
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DEFAULT_CONFIG_NAME = _DEFAULT_CONFIG |
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def _info(self): |
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features = datasets.Features( |
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{ |
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"hr": datasets.Value("string"), |
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"lr": datasets.Value("string"), |
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} |
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) |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=features, |
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supervised_keys=None, |
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homepage=_HOMEPAGE, |
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license=_LICENSE, |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager): |
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"""Returns SplitGenerators.""" |
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hr_data_dir = dl_manager.download_and_extract(self.config.hr_url) |
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lr_data_dir = dl_manager.download_and_extract(self.config.lr_url) |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.VALIDATION, |
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gen_kwargs={ |
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"lr_path": lr_data_dir, |
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"hr_path": str(Path(hr_data_dir) / 'Set5_HR') |
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}, |
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) |
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] |
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def _generate_examples( |
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self, hr_path, lr_path |
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): |
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""" Yields examples as (key, example) tuples. """ |
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extensions = {'.jpg', '.jpeg', '.png'} |
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for file_path in sorted(Path(lr_path).glob("**/*")): |
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if file_path.suffix in extensions: |
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file_path_str = str(file_path.as_posix()) |
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yield file_path_str, { |
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'lr': file_path_str, |
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'hr': str((Path(hr_path) / file_path.name).as_posix()) |
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} |
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