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import os |
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import pandas as pd |
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import zipfile |
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import datasets |
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from datasets import load_dataset |
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class StackmixHKRLarge(datasets.GeneratorBasedBuilder): |
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def _info(self): |
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return datasets.DatasetInfo( |
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features=datasets.Features( |
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{ |
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"path": datasets.Value("string"), |
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"name": datasets.Value("string"), |
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"text": datasets.Value("string"), |
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"image": datasets.Image() |
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} |
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) |
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) |
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def _split_generators(self, dl_manager): |
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_URLS = {f"img{i:02d}": f"img/img-{i:02d}.zip" for i in range(10)} |
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_URLS["labels"] = "gt.txt" |
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data_paths = dl_manager.download_and_extract(_URLS) |
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image_paths = [data_paths[key] for key in data_paths if key.startswith("img")] |
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return [datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, |
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gen_kwargs={ |
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"image_paths": dl_manager.iter_files(image_paths), |
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"labels_path": data_paths["labels"] |
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})] |
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def _generate_examples(self, image_paths, labels_path): |
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df = pd.read_csv(labels_path, sep=",", names=["path", "text"]) |
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df["path"] = df.path.str[4:] |
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df.set_index("path", inplace=True) |
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for image_path in image_paths: |
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image_name = os.path.basename(image_path) |
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if image_name in df.index: |
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example = { |
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"path": image_path, |
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"name": image_name, |
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"text": df["text"][image_name], |
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"image": image_path |
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} |
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yield image_name, example |
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