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"""OpenFire dataset.""" |
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import os |
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import json |
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import datasets |
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_HOMEPAGE = "https://pyronear.org/pyro-vision/datasets.html#openfire" |
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_LICENSE = "Apache License 2.0" |
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_CITATION = """\ |
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@software{Pyronear_PyroVision_2019, |
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title={Pyrovision: wildfire early detection}, |
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author={Pyronear contributors}, |
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year={2019}, |
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month={October}, |
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publisher = {GitHub}, |
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url = {https://github.com/pyronear/pyro-vision} |
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} |
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""" |
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_DESCRIPTION = """\ |
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OpenFire is an image classification dataset for wildfire detection, collected |
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from web searches. |
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""" |
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_REPO = "https://huggingface.co/datasets/pyronear/openfire/resolve/main/data" |
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_URLS = { |
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"train": f"{_REPO}/openfire_train.json", |
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"validation": f"{_REPO}/openfire_val.json", |
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} |
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class OpenFire(datasets.GeneratorBasedBuilder): |
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"""OpenFire dataset.""" |
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VERSION = datasets.Version("1.0.0") |
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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_url": datasets.Value("string", id=None), |
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"is_wildfire": datasets.Value("bool"), |
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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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license=_LICENSE, |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager): |
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data_dir = 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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"annot_file": data_dir["train"], |
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"split": "train", |
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}, |
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), |
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datasets.SplitGenerator( |
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name=datasets.Split.VALIDATION, |
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gen_kwargs={ |
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"annot_file": data_dir["validation"], |
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"split": "validation", |
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}, |
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), |
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] |
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def _generate_examples(self, filepath, split): |
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with open(filepath, "rb", encoding="utf-8") as f: |
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urls = json.load(f) |
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idx = 0 |
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for label in range(2): |
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for url in urls[str(label)]: |
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yield idx, {"image_url": url, "is_wildfire": bool(label)} |
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idx += 1 |
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