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import json |
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import os |
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import datasets |
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logger = datasets.logging.get_logger(__name__) |
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_CITATION = """""" |
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_DESCRIPTION = """\ |
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Ornithoscope dataset is the dataset used to train the model for the Ornithoscope project. |
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""" |
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_HOMEPAGE = "" |
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_FOLDERS = [ |
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'iNatv1', |
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'iNatv2/10069', |
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'iNatv2/13851', |
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'iNatv2/145303', |
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'iNatv2/14850', |
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'iNatv2/17871', |
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'iNatv2/18911', |
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'iNatv2/204496', |
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'iNatv2/3017', |
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'iNatv2/7278', |
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'iNatv2/792985', |
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'iNatv2/8088', |
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'iNatv2/9398', |
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'iNatv2/9801', |
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'PhotoFeederv1/task_05-01-2021', |
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'PhotoFeederv1/task_06-01-2021', |
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'PhotoFeederv1/task_18-01-2021', |
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'PhotoFeederv1/task_19-01-2021', |
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'PhotoFeederv1/task_20210205', |
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'PhotoFeederv1/task_20210217', |
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'PhotoFeederv1/task_20210227', |
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'PhotoFeederv1/task_20210228', |
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'PhotoFeederv1/task_2021-03-01_07', |
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'PhotoFeederv1/task_2021-03-01_08', |
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'PhotoFeederv1/task_2021-03-01_09', |
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'PhotoFeederv1/task_2021-03-01_10', |
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'PhotoFeederv1/task_2021-03-01_11', |
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'PhotoFeederv1/task_2021-03-01_12', |
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'PhotoFeederv1/task_2021-03-01_13', |
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'PhotoFeederv1/task_2021-03-01_14', |
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'PhotoFeederv1/task_2021-03-01_15', |
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'PhotoFeederv1/task_2021-03-01_16', |
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'PhotoFeederv1/task_2021-03-01_17', |
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'PhotoFeederv1/task_2021-03-01_18', |
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'PhotoFeederv1/task_20210409', |
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'PhotoFeederv1/task_20210411', |
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'PhotoFeederv1/task_20210412', |
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'PhotoFeederv1/task_20210413_UPS', |
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'PhotoFeederv1/task_20210414', |
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'PhotoFeederv1/task_20210415_UPS', |
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'PhotoFeederv1/task_20210416_UPS', |
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'PhotoFeederv1/task_20210417_UPS', |
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'PhotoFeederv1/task_20210418_UPS', |
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'PhotoFeederv1/task_20210419_UPS', |
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'PhotoFeederv1/task_20210420', |
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'PhotoFeederv1/task_20210523_UPS', |
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'PhotoFeederv1/task_20210525_UPS', |
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'PhotoFeederv1/task_20210526_UPS', |
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'PhotoFeederv1/task_20210611_Lab', |
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'PhotoFeederv1/task_20210612_1_Lab', |
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'PhotoFeederv1/task_20210615_Lab', |
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'PhotoFeederv1/task_20210616_Lab', |
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'PhotoFeederv1/task_20210623_balacet', |
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'PhotoFeederv1/task_20210624_balacet', |
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'PhotoFeederv1/task_20210625_balacet', |
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'PhotoFeederv1/task_20210705-07_balacet', |
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'PhotoFeederv1/task_20211008_Moulis', |
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'PhotoFeederv1/task_2021_11_03-04_cescau4', |
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'PhotoFeederv1/task_20211109_cescau1', |
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'PhotoFeederv1/task_20211204_Orlu', |
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'PhotoFeederv1/task_21-01-2021', |
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'PhotoFeederv1/task_berggris_dordogne', |
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'PhotoFeederv1/task_berggris', |
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'PhotoFeederv1/task_MOIDOM_ODJ', |
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'PhotoFeederv2/Balacet_session1', |
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'PhotoFeederv2/Balacet_session4', |
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'PhotoFeederv2/C1_session1', |
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'PhotoFeederv2/C1_session3', |
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'PhotoFeederv2/C1_session4', |
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'PhotoFeederv2/C4_session1', |
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'PhotoFeederv2/C4_session4', |
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'PhotoFeederv2/Francon_session1', |
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'PhotoFeederv2/Francon_session4', |
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'PhotoFeederv2/Montpellier_session1', |
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'PhotoFeederv2/Montpellier_session4', |
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'PhotoFeederv2/Moulis_session4', |
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'PhotoFeederv2/Orlu_session4', |
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] |
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class OrnithoscopeConfig(datasets.BuilderConfig): |
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"""BuilderConfig for Ornithoscope.""" |
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def __init__( |
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self, |
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train_json: str, |
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validation_json: str, |
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test_json: str, |
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**kwargs |
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): |
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"""BuilderConfig for Ornithoscope. |
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Args: |
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train_json: path to the json file containing the train annotations. |
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validation_json: path to the json file containing the validation annotations. |
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test_json: path to the json file containing the test annotations. |
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**kwargs: keyword arguments forwarded to super. |
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""" |
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super().__init__(version=datasets.Version("1.0.0"), **kwargs) |
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self.train_json = train_json |
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self.validation_json = validation_json |
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self.test_json = test_json |
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class Ornithoscope(datasets.GeneratorBasedBuilder): |
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NAMES = [ |
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'DS1', |
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'DS2', |
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'DS3', |
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'DS4', |
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'DS5', |
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'DS6', |
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'DS7', |
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'DS8', |
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'DS9.0', |
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'DS9.1', |
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'DS9.2', |
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'DS9.3', |
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'DS9.4', |
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'DS9.5', |
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] |
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VERSION = datasets.Version("1.0.0") |
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BUILDER_CONFIGS = [ |
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OrnithoscopeConfig( |
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name=name, |
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description=f'{name} ornithoscope dataset.', |
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train_json=f'sets/{name}_train.json', |
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validation_json=f'sets/{name}_val.json', |
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test_json=f'sets/{name}_test.json', |
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) |
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for name in NAMES |
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] |
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def _info(self) -> datasets.DatasetInfo: |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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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: datasets.DownloadManager) -> list[datasets.SplitGenerator]: |
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"""Returns SplitGenerators.""" |
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archives = self._get_archives(dl_manager) |
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train_json = json.load( |
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open(dl_manager.download_and_extract(self.config.train_json), 'r')) |
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train_vals = [] |
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for id_path, value in train_json.items(): |
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root, file = os.path.split(id_path) |
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path = os.path.join(archives[root], file) |
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val = { |
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"id_path": id_path, |
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"path": path, |
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"boxes": value['boxes'], |
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"size": value['size'], |
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} |
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train_vals.append(val) |
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validation_json = json.load( |
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open(dl_manager.download_and_extract(self.config.validation_json), 'r')) |
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validation_vals = [] |
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for id_path, value in validation_json.items(): |
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root, file = os.path.split(id_path) |
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path = os.path.join(archives[root], file) |
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val = { |
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"id_path": id_path, |
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"path": path, |
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"boxes": value['boxes'], |
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"size": value['size'], |
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} |
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validation_vals.append(val) |
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test_json = json.load( |
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open(dl_manager.download_and_extract(self.config.test_json), 'r')) |
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test_vals = [] |
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for id_path, value in test_json.items(): |
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root, file = os.path.split(id_path) |
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path = os.path.join(archives[root], file) |
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val = { |
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"id_path": id_path, |
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"path": path, |
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"boxes": value['boxes'], |
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"size": value['size'], |
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} |
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test_vals.append(val) |
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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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"values": train_vals, |
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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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"values": validation_vals, |
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}, |
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), |
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datasets.SplitGenerator( |
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name=datasets.Split.TEST, |
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gen_kwargs={ |
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"values": test_vals, |
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}, |
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), |
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] |
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def _generate_examples(self, values: list) -> tuple: |
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"""Yields examples.""" |
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idx = 0 |
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for val in values: |
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example = { |
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"id_path": val["id_path"], |
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"path": val["path"], |
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"boxes": val["boxes"], |
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"size": val["size"], |
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} |
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yield idx, example |
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idx += 1 |
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def _get_archives(self, dl_manager: datasets.DownloadManager) -> dict: |
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"""Get the archives containing the images.""" |
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archives = {} |
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for folder in _FOLDERS: |
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archives[folder] = dl_manager.download_and_extract( |
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f'data/{folder}.tar' |
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) |
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return archives |
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