Create renovation.py
Browse files- renovation.py +65 -0
renovation.py
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import os
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import csv
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import datasets
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from datasets.tasks import ImageClassification
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_HOMEPAGE = "https://huggingface.co/datasets/rshrott/renovation"
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_CITATION = """\
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@ONLINE {renovationquality,
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author="Your Name",
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title="Renovation Quality Dataset",
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month="Your Month",
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year="Your Year",
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url="https://huggingface.co/datasets/rshrott/renovation"
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}
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"""
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_DESCRIPTION = """\
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This dataset contains images of various properties, along with labels indicating the quality of renovation - 'cheap', 'average', 'expensive'.
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"""
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_URL = "https://huggingface.co/datasets/rshrott/renovation/blob/main/labels.csv"
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_NAMES = ["cheap", "average", "expensive"]
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class RenovationQualityDataset(datasets.GeneratorBasedBuilder):
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"""Renovation Quality Dataset."""
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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.Value("string"),
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"label": datasets.features.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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csv_path = dl_manager.download(_URL)
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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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"filepath": csv_path,
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},
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),
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]
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def _generate_examples(self, filepath):
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with open(filepath, "r") as f:
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reader = csv.reader(f)
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next(reader) # skip header
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for id_, row in enumerate(reader):
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yield id_, {
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'image': row[0],
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'label': row[1],
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}
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