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import os |
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import datasets |
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from huggingface_hub import HfApi |
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from datasets import DownloadManager, DatasetInfo |
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from datasets.data_files import DataFilesDict |
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_EXTENSION = [".png", ".jpg", ".jpeg", ".webp", ".bmp"] |
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_NAME = "nyanko7/danbooru2023" |
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_REVISION = "main" |
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class DanbooruDataset(datasets.GeneratorBasedBuilder): |
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BUILDER_CONFIGS = [ |
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datasets.BuilderConfig(name="full"), |
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] |
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def _info(self) -> DatasetInfo: |
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features = { |
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"image": datasets.Image(), |
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"post_id": datasets.Value("int64") |
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} |
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info = datasets.DatasetInfo( |
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features=datasets.Features(features), |
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supervised_keys=None, |
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citation="", |
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) |
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return info |
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def _split_generators(self, dl_manager: DownloadManager): |
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hfh_dataset_info = HfApi().dataset_info(_NAME, revision=_REVISION, timeout=100.0) |
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data_files = DataFilesDict.from_hf_repo( |
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{datasets.Split.TRAIN: ["**"]}, |
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dataset_info=hfh_dataset_info, |
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allowed_extensions=["tar", ".tar"], |
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) |
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gs = [] |
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for split, files in data_files.items(): |
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downloaded_files = dl_manager.download_and_extract(files) |
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gs.append(datasets.SplitGenerator(name=split, gen_kwargs={"filepath": downloaded_files})) |
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return gs |
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def _generate_examples(self, filepath): |
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for path in filepath: |
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all_fnames = {os.path.relpath(os.path.join(root, fname), start=path) for root, _dirs, files in os.walk(path) for fname in files} |
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image_fnames = sorted([fname for fname in all_fnames if os.path.splitext(fname)[1].lower() in _EXTENSION], reverse=True) |
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for image_fname in image_fnames: |
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image_path = os.path.join(path, image_fname) |
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post_id = int(os.path.splitext(os.path.basename(image_fname))[0]) |
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yield image_fname, {"post_id": post_id} |
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