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"""Dataset class for image dataset.""" |
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import datasets |
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import os |
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from datasets.tasks import ImageClassification |
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_URL = "http://https://huggingface.co/datasets/Racso777/AncientMortar/tree/main/metadata" |
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_HOMEPAGE = "http://https://huggingface.co/datasets/Racso777/AncientMortar" |
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_DESCRIPTION = ( |
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"This dataset consists of test dataset of ancient mortar and with only obsidian images as zip file in it" |
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) |
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_NAMES = [ |
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"Obsidian-1to2mm", |
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] |
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class AncientMortarConfig(datasets.BuilderConfig): |
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"""BuilderConfig for COCO cats image.""" |
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def __init__( |
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self, |
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data_url, |
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url, |
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task_templates=None, |
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**kwargs, |
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): |
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super(AncientMortarConfig, self).__init__( |
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version=datasets.Version("1.9.0", ""), **kwargs |
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) |
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self.data_url = data_url |
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self.url = url |
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self.task_templates = task_templates |
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class AncientMortar(datasets.GeneratorBasedBuilder): |
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BUILDER_CONFIGS = [ |
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AncientMortarConfig( |
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name="image", |
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url="", |
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data_url="", |
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) |
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] |
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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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"image": datasets.Image(), |
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"label": datasets.ClassLabel(), |
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} |
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), |
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supervised_keys=("image", "label"), |
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homepage=_HOMEPAGE, |
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citation=_CITATION, |
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task_templates=[ImageClassification(image_column="image", label_column="label")], |
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) |
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def _split_generators(self, dl_manager): |
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archive_path = dl_manager.download_and_extract(_URLS) |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TEST, |
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gen_kwargs={"archive_path": archive_path}, |
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), |
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] |
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def _generate_examples(self, images, metadata_path): |
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"""Generate images and labels for splits.""" |
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with open(metadata_path, encoding="utf-8") as f: |
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files_to_keep = set(f.read().split("\n")) |
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for file_path, file_obj in images: |
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if file_path.startswith(_IMAGES_DIR): |
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if file_path[len(_IMAGES_DIR) : -len(".bmp")] in files_to_keep: |
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label = file_path.split("/")[2] |
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yield file_path, { |
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"image": {"path": file_path, "bytes": file_obj.read()}, |
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"label": label, |
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} |
