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import os |
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from datasets import DatasetInfo, GeneratorBasedBuilder, Split, Features, Image |
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class FFHQProxy(GeneratorBasedBuilder): |
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"""FFHQ Proxy Dataset Loader""" |
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VERSION = "1.0.0" |
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def _info(self): |
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return DatasetInfo( |
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description="Proxy repository for FFHQ: facial upscaling and restoration reference dataset.", |
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homepage="https://github.com/NVlabs/ffhq-dataset", |
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license="creativeml-openrail-m", |
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features=Features({ |
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"low_quality": Image(), |
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"high_quality": Image() |
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}), |
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task_categories=["image-to-image"], |
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language=["en"], |
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) |
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def _split_generators(self, dl_manager): |
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"""Define splits (train/test)""" |
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data_dir = os.path.expanduser(dl_manager.download_and_extract("https://drive.google.com/drive/folders/1u2xu7bSrWxrbUxk-dT-UvEJq8IjdmNTP")) |
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return [ |
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self.SplitGenerator( |
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name=Split.TRAIN, |
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gen_kwargs={"images_dir": os.path.join(data_dir, "train")} |
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), |
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] |
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def _generate_examples(self, images_dir): |
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"""Yield examples.""" |
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for idx, fname in enumerate(os.listdir(images_dir)): |
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if fname.endswith(".png") or fname.endswith(".jpg"): |
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low_quality_path = os.path.join(images_dir, fname) |
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high_quality_path = os.path.join(images_dir, "high_quality", fname) |
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yield idx, { |
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"low_quality": low_quality_path, |
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"high_quality": high_quality_path |
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} |
