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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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_URLS = "mortars_data.zip" |
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_HOMEPAGE = "http://https://huggingface.co/datasets/apetulante/mortars_test" |
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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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_CITATION = "" |
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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(names=_NAMES), |
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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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data_files = dl_manager.download_and_extract(_URLS) |
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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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"files": dl_manager.iter_files([data_files]), |
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}, |
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) |
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] |
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def _generate_examples(self, files): |
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"""Generate images and labels for splits.""" |
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for i, path in enumerate(files): |
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file_name = os.path.basename(path) |
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if file_name.endswith(".bmp"): |
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yield i, { |
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"image_file_path": path, |
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"image": path, |
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"labels": os.path.basename(os.path.dirname(path)).lower(), |
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} |
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