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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"] |
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_DESCRIPTION = "" |
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_NAME = "animelover/princess-connect-images" |
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_REVISION = "main" |
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class DanbooruDataset(datasets.GeneratorBasedBuilder): |
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def _info(self) -> DatasetInfo: |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=datasets.Features( |
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{ |
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"image": datasets.Image(), |
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"tags": datasets.Value("string") |
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} |
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), |
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supervised_keys=None, |
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citation="", |
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) |
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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=["zip"], |
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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) |
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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 |
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if os.path.splitext(fname)[1].lower() in _EXTENSION) |
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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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tags_path = os.path.join(path, os.path.splitext(image_fname)[0] + ".txt") |
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with open(tags_path, "r", encoding="utf-8") as f: |
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tags = f.read() |
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yield image_fname, {"image": image_path, "tags": tags} |