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import datasets |
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_CITATION = """\ |
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@InProceedings{huggingface:dataset, |
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title = {Small image-text set}, |
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author={James Briggs}, |
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year={2022} |
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} |
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""" |
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_DESCRIPTION = """\ |
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Demo dataset for testing or showing image-text capabilities. |
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""" |
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_HOMEPAGE = "https://huggingface.co./datasets/danbrown/testman-dataset" |
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_LICENSE = "" |
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_REPO = "https://huggingface.co./datasets/danbrown/testman-dataset" |
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class ImageSet(datasets.GeneratorBasedBuilder): |
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"""Small sample of image-text pairs""" |
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def _info(self): |
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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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'text': datasets.Value("string"), |
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'image': datasets.Image(), |
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} |
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), |
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supervised_keys=None, |
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homepage=_HOMEPAGE, |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager): |
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images_archive = dl_manager.download(f"{_REPO}/resolve/main/images.tar.gz") |
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image_iters = dl_manager.iter_archive(images_archive) |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, |
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gen_kwargs={ |
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"images": image_iters, |
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} |
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), |
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] |
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def _generate_examples(self, images): |
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""" This function returns the examples in the raw (text) form.""" |
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for idx, (filepath, image) in enumerate(images): |
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description = filepath.split('/')[-1][:-4] |
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description = description.replace('_', ' ') |
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yield idx, { |
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"image": {"path": filepath, "bytes": image.read()}, |
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"text": description, |
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} |