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"""BirdSet: The General Avian Monitoring Evaluation Benchmark""" |
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|
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import os |
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import datasets |
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import pandas as pd |
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|
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from .classes import BIRD_NAMES_NIPS4BPLUS, BIRD_NAMES_AMAZON_BASIN, BIRD_NAMES_HAWAII, \ |
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BIRD_NAMES_HIGH_SIERRAS, BIRD_NAMES_SIERRA_NEVADA, BIRD_NAMES_POWDERMILL_NATURE, BIRD_NAMES_SAPSUCKER, \ |
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BIRD_NAMES_COLUMBIA_COSTA_RICA, BIRD_NAMES_XENOCANTO, BIRD_NAMES_XENOCANTO_M |
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|
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from .descriptions import _BIRD_DB_CITATION, _NIPS4BPLUS_CITATION, _NIPS4BPLUS_DESCRIPTION, \ |
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_HIGH_SIERRAS_DESCRIPTION, _HIGH_SIERRAS_CITATION, _SIERRA_NEVADA_DESCRIPTION, _SIERRA_NEVADA_CITATION, \ |
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_POWDERMILL_NATURE_DESCRIPTION, _POWDERMILL_NATURE_CITATION, _AMAZON_BASIN_DESCRIPTION, _AMAZON_BASIN_CITATION, \ |
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_SAPSUCKER_WOODS_DESCRIPTION, _SAPSUCKER_WOODS_CITATION, _COLUMBIA_COSTA_RICA_CITATION, \ |
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_COLUMBIA_COSTA_RICA_DESCRIPTION, _HAWAIIAN_ISLANDS_CITATION, _HAWAIIAN_ISLANDS_DESCRIPTION |
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_BIRDSET_CITATION = """\ |
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@article{rauch2024, |
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title = {BirdSet: A Multi-Task Benchmark For Avian Diversity Monitoring}, |
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author={Rauch, Lukas and Schwinger, Raphael and Wirth, Moritz and Lange, Jonas and Heinrich, René}, |
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year={2024} |
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} |
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""" |
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_BIRDSET_DESCRIPTION = """\ |
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This dataset offers a unified, well-structured platform for avian bioacoustics and consists of various tasks. \ |
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By creating a set of tasks, BirdSet enables an overall performance score for models and uncovers their limitations \ |
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in certain areas. |
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Note that each BirdSet dataset has its own citation. Please see the source to get the correct citation for each |
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contained dataset. |
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""" |
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|
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base_url = "https://huggingface.co/datasets/DBD-research-group/gadme/resolve/data" |
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|
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|
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class BirdSetConfig(datasets.BuilderConfig): |
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def __init__( |
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self, |
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name, |
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citation, |
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class_list, |
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**kwargs): |
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super().__init__(version=datasets.Version("0.0.2"), name=name, **kwargs) |
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|
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features = datasets.Features({ |
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"audio": datasets.Audio(sampling_rate=32_000, mono=True, decode=False), |
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"filepath": datasets.Value("string"), |
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"start_time": datasets.Value("float64"), |
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"end_time": datasets.Value("float64"), |
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"low_freq": datasets.Value("int64"), |
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"high_freq": datasets.Value("int64"), |
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"ebird_code": datasets.ClassLabel(names=class_list), |
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"ebird_code_multilabel": datasets.Sequence(datasets.ClassLabel(names=class_list)), |
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"ebird_code_secondary": datasets.Sequence(datasets.Value("string")), |
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"call_type": datasets.Value("string"), |
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"sex": datasets.Value("string"), |
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"lat": datasets.Value("float64"), |
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"long": datasets.Value("float64"), |
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"length": datasets.Value("int64"), |
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"microphone": datasets.Value("string"), |
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"license": datasets.Value("string"), |
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"source": datasets.Value("string"), |
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"local_time": datasets.Value("string"), |
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"detected_events": datasets.Sequence(datasets.Sequence(datasets.Value("float64"))), |
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"event_cluster": datasets.Sequence(datasets.Value("int64")), |
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"peaks": datasets.Sequence(datasets.Value("float64")), |
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"quality": datasets.Value("string"), |
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"recordist": datasets.Value("string"), |
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}) |
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|
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self.features = features |
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self.citation = citation |
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|
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class BirdSet(datasets.GeneratorBasedBuilder): |
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"""TODO: Short description of my dataset.""" |
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DEFAULT_WRITER_BATCH_SIZE = 500 |
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|
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BUILDER_CONFIGS = [ |
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BirdSetConfig( |
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name="SSW", |
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description=_SAPSUCKER_WOODS_DESCRIPTION, |
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citation=_SAPSUCKER_WOODS_CITATION, |
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data_dir=f"{base_url}/SSW", |
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class_list=BIRD_NAMES_SAPSUCKER, |
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), |
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BirdSetConfig( |
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name="SSW_xc", |
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description=_SAPSUCKER_WOODS_DESCRIPTION, |
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citation=_SAPSUCKER_WOODS_CITATION, |
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data_dir=f"{base_url}/SSW", |
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class_list=BIRD_NAMES_SAPSUCKER, |
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), |
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BirdSetConfig( |
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name="SSW_scape", |
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description=_SAPSUCKER_WOODS_DESCRIPTION, |
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citation=_SAPSUCKER_WOODS_CITATION, |
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data_dir=f"{base_url}/SSW", |
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class_list=BIRD_NAMES_SAPSUCKER, |
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), |
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BirdSetConfig( |
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name="PER", |
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description=_AMAZON_BASIN_DESCRIPTION, |
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citation=_AMAZON_BASIN_CITATION, |
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data_dir=f"{base_url}/PER", |
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class_list=BIRD_NAMES_AMAZON_BASIN, |
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), |
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BirdSetConfig( |
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name="PER_xc", |
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description=_AMAZON_BASIN_DESCRIPTION, |
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citation=_AMAZON_BASIN_CITATION, |
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data_dir=f"{base_url}/PER", |
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class_list=BIRD_NAMES_AMAZON_BASIN, |
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), |
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BirdSetConfig( |
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name="PER_scape", |
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description=_AMAZON_BASIN_DESCRIPTION, |
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citation=_AMAZON_BASIN_CITATION, |
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data_dir=f"{base_url}/PER", |
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class_list=BIRD_NAMES_AMAZON_BASIN, |
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), |
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BirdSetConfig( |
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name="UHH", |
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description=_HAWAIIAN_ISLANDS_DESCRIPTION, |
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citation=_HAWAIIAN_ISLANDS_CITATION, |
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data_dir=f"{base_url}/UHH", |
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class_list=BIRD_NAMES_HAWAII, |
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), |
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BirdSetConfig( |
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name="UHH_xc", |
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description=_HAWAIIAN_ISLANDS_DESCRIPTION, |
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citation=_HAWAIIAN_ISLANDS_CITATION, |
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data_dir=f"{base_url}/UHH", |
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class_list=BIRD_NAMES_HAWAII, |
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), |
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BirdSetConfig( |
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name="UHH_scape", |
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description=_HAWAIIAN_ISLANDS_DESCRIPTION, |
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citation=_HAWAIIAN_ISLANDS_CITATION, |
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data_dir=f"{base_url}/UHH", |
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class_list=BIRD_NAMES_HAWAII, |
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), |
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BirdSetConfig( |
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name="SNE", |
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description=_SIERRA_NEVADA_DESCRIPTION, |
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citation=_SIERRA_NEVADA_CITATION, |
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data_dir=f"{base_url}/SNE", |
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class_list=BIRD_NAMES_SIERRA_NEVADA, |
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), |
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BirdSetConfig( |
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name="SNE_xc", |
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description=_SIERRA_NEVADA_DESCRIPTION, |
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citation=_SIERRA_NEVADA_CITATION, |
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data_dir=f"{base_url}/SNE", |
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class_list=BIRD_NAMES_SIERRA_NEVADA, |
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), |
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BirdSetConfig( |
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name="SNE_scape", |
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description=_SIERRA_NEVADA_DESCRIPTION, |
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citation=_SIERRA_NEVADA_CITATION, |
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data_dir=f"{base_url}/SNE", |
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class_list=BIRD_NAMES_SIERRA_NEVADA, |
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), |
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BirdSetConfig( |
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name="POW", |
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description=_POWDERMILL_NATURE_DESCRIPTION, |
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citation=_POWDERMILL_NATURE_CITATION, |
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data_dir=f"{base_url}/POW", |
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class_list=BIRD_NAMES_POWDERMILL_NATURE, |
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), |
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BirdSetConfig( |
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name="POW_xc", |
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description=_POWDERMILL_NATURE_DESCRIPTION, |
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citation=_POWDERMILL_NATURE_CITATION, |
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data_dir=f"{base_url}/POW", |
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class_list=BIRD_NAMES_POWDERMILL_NATURE, |
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), |
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BirdSetConfig( |
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name="POW_scape", |
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description=_POWDERMILL_NATURE_DESCRIPTION, |
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citation=_POWDERMILL_NATURE_CITATION, |
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data_dir=f"{base_url}/POW", |
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class_list=BIRD_NAMES_POWDERMILL_NATURE, |
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), |
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BirdSetConfig( |
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name="HSN", |
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description=_HIGH_SIERRAS_DESCRIPTION, |
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citation=_HIGH_SIERRAS_CITATION, |
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data_dir=f"{base_url}/HSN", |
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class_list=BIRD_NAMES_HIGH_SIERRAS, |
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), |
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BirdSetConfig( |
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name="HSN_xc", |
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description=_HIGH_SIERRAS_DESCRIPTION, |
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citation=_HIGH_SIERRAS_CITATION, |
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data_dir=f"{base_url}/HSN", |
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class_list=BIRD_NAMES_HIGH_SIERRAS, |
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), |
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BirdSetConfig( |
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name="HSN_scape", |
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description=_HIGH_SIERRAS_DESCRIPTION, |
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citation=_HIGH_SIERRAS_CITATION, |
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data_dir=f"{base_url}/HSN", |
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class_list=BIRD_NAMES_HIGH_SIERRAS, |
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), |
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BirdSetConfig( |
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name="NES", |
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description=_COLUMBIA_COSTA_RICA_DESCRIPTION, |
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citation=_COLUMBIA_COSTA_RICA_CITATION, |
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data_dir=f"{base_url}/NES", |
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class_list=BIRD_NAMES_COLUMBIA_COSTA_RICA, |
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), |
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BirdSetConfig( |
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name="NES_xc", |
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description=_COLUMBIA_COSTA_RICA_DESCRIPTION, |
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citation=_COLUMBIA_COSTA_RICA_CITATION, |
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data_dir=f"{base_url}/NES", |
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class_list=BIRD_NAMES_COLUMBIA_COSTA_RICA, |
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), |
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BirdSetConfig( |
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name="NES_scape", |
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description=_COLUMBIA_COSTA_RICA_DESCRIPTION, |
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citation=_COLUMBIA_COSTA_RICA_CITATION, |
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data_dir=f"{base_url}/NES", |
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class_list=BIRD_NAMES_COLUMBIA_COSTA_RICA, |
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), |
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BirdSetConfig( |
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name="NBP", |
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description=_NIPS4BPLUS_DESCRIPTION, |
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citation=_NIPS4BPLUS_CITATION, |
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data_dir=f"{base_url}/NBP", |
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class_list=BIRD_NAMES_NIPS4BPLUS, |
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), |
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BirdSetConfig( |
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name="NBP_xc", |
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description=_NIPS4BPLUS_DESCRIPTION, |
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citation=_NIPS4BPLUS_CITATION, |
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data_dir=f"{base_url}/NBP", |
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class_list=BIRD_NAMES_NIPS4BPLUS, |
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), |
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BirdSetConfig( |
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name="NBP_scape", |
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description=_NIPS4BPLUS_DESCRIPTION, |
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citation=_NIPS4BPLUS_CITATION, |
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data_dir=f"{base_url}/NBP", |
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class_list=BIRD_NAMES_NIPS4BPLUS, |
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), |
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BirdSetConfig( |
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name="XCM", |
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description="TODO", |
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citation="TODO", |
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data_dir=f"{base_url}/XCM", |
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class_list=BIRD_NAMES_XENOCANTO_M, |
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), |
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BirdSetConfig( |
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name="XCL", |
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description="TODO", |
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citation="TODO", |
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data_dir=f"{base_url}/XCL", |
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class_list=BIRD_NAMES_XENOCANTO, |
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), |
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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=_BIRDSET_DESCRIPTION + self.config.description, |
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features=self.config.features, |
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citation=self.config.citation + "\n" + _BIRDSET_CITATION, |
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) |
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|
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def _split_generators(self, dl_manager): |
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ds_name = self.config.name |
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train_files = {"PER": 11, |
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"NES": 13, |
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"UHH": 5, |
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"HSN": 7, |
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"NBP": 32, |
|
"POW": 9, |
|
"SSW": 29, |
|
"SNE": 21, |
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"XCM": 182, |
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"XCL": 98} |
|
|
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test_files = {"PER": 3, |
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"NES": 8, |
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"UHH": 7, |
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"HSN": 3, |
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"NBP": 1, |
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"POW": 3, |
|
"SSW": 36, |
|
"SNE": 5} |
|
|
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test5s_files = {"PER": 1, |
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"NES": 1, |
|
"UHH": 1, |
|
"HSN": 1, |
|
"NBP": 1, |
|
"POW": 1, |
|
"SSW": 4, |
|
"SNE": 1} |
|
|
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if self.config.name.endswith("_xc"): |
|
ds_name = ds_name[:-3] |
|
dl_dir = dl_manager.download({ |
|
"train": [os.path.join(self.config.data_dir, f"{ds_name}_train_shard_{n:04d}.tar.gz") for n in range(1, train_files[ds_name] + 1)], |
|
"metadata": os.path.join(self.config.data_dir, f"{ds_name}_metadata_train.parquet"), |
|
}) |
|
|
|
elif self.config.name.endswith("_scape"): |
|
ds_name = ds_name[:-6] |
|
dl_dir = dl_manager.download({ |
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"test": [os.path.join(self.config.data_dir, f"{ds_name}_test_shard_{n:04d}.tar.gz") for n in range(1, test_files[ds_name] + 1)], |
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"test_5s": [os.path.join(self.config.data_dir, f"{ds_name}_test5s_shard_{n:04d}.tar.gz") for n in range(1, test5s_files[ds_name] + 1)], |
|
"metadata": os.path.join(self.config.data_dir, f"{ds_name}_metadata_test.parquet"), |
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"metadata_5s": os.path.join(self.config.data_dir, f"{ds_name}_metadata_test_5s.parquet"), |
|
}) |
|
|
|
|
|
elif self.config.name.startswith("XC"): |
|
dl_dir = dl_manager.download({ |
|
"train": [os.path.join(self.config.data_dir, f"{ds_name}_shard_{n:04d}.tar.gz") for n in range(1, train_files[ds_name] + 1)], |
|
"valid": [os.path.join(self.config.data_dir.replace("/XCM", "/POW"), f"POW_test5s_shard_{n:04d}.tar.gz") for n in range(1, test5s_files["POW"] + 1)], |
|
"metadata": os.path.join(self.config.data_dir, f"{ds_name}_metadata.parquet"), |
|
"meta_test_5s": os.path.join(self.config.data_dir.replace("/XCM", "/POW"), f"POW_metadata_test_5s.parquet"), |
|
}) |
|
|
|
elif self.config.name in train_files.keys(): |
|
dl_dir = dl_manager.download({ |
|
"train": [os.path.join(self.config.data_dir, f"{ds_name}_train_shard_{n:04d}.tar.gz") for n in range(1, train_files[ds_name] + 1)], |
|
"test": [os.path.join(self.config.data_dir, f"{ds_name}_test_shard_{n:04d}.tar.gz") for n in range(1, test_files[ds_name] + 1)], |
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"test_5s": [os.path.join(self.config.data_dir, f"{ds_name}_test5s_shard_{n:04d}.tar.gz") for n in range(1, test5s_files[ds_name] + 1)], |
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"meta_train": os.path.join(self.config.data_dir, f"{ds_name}_metadata_train.parquet"), |
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"meta_test": os.path.join(self.config.data_dir, f"{ds_name}_metadata_test.parquet"), |
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"meta_test_5s": os.path.join(self.config.data_dir, f"{ds_name}_metadata_test_5s.parquet"), |
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}) |
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|
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local_audio_archives_paths = dl_manager.extract(dl_dir) if not dl_manager.is_streaming else None |
|
|
|
if self.config.name.startswith("XC") or self.config.name.endswith("_xc"): |
|
return [ |
|
datasets.SplitGenerator( |
|
name=datasets.Split.TRAIN, |
|
gen_kwargs={ |
|
"audio_archive_iterators": [dl_manager.iter_archive(archive_path) for archive_path in dl_dir["train"]], |
|
"local_audio_archives_paths": local_audio_archives_paths["train"] if local_audio_archives_paths else None, |
|
"metapath": dl_dir["metadata"], |
|
"split": datasets.Split.TRAIN, |
|
}, |
|
), |
|
datasets.SplitGenerator( |
|
name="valid", |
|
gen_kwargs={ |
|
"audio_archive_iterators": [dl_manager.iter_archive(archive_path) for archive_path in dl_dir["valid"]], |
|
"local_audio_archives_paths": local_audio_archives_paths["valid"] if local_audio_archives_paths else None, |
|
"metapath": dl_dir["meta_test_5s"], |
|
"split": "valid", |
|
}, |
|
), |
|
] |
|
|
|
elif self.config.name.endswith("_scape"): |
|
return [ |
|
datasets.SplitGenerator( |
|
name=datasets.Split.TEST, |
|
gen_kwargs={ |
|
"audio_archive_iterators": [dl_manager.iter_archive(archive_path) for archive_path in dl_dir["test"]], |
|
"local_audio_archives_paths": local_audio_archives_paths["test"] if local_audio_archives_paths else None, |
|
"metapath": dl_dir["metadata"], |
|
"split": datasets.Split.TEST, |
|
}, |
|
), |
|
datasets.SplitGenerator( |
|
name="test_5s", |
|
gen_kwargs={ |
|
"audio_archive_iterators": [dl_manager.iter_archive(archive_path) for archive_path in dl_dir["test_5s"]], |
|
"local_audio_archives_paths": local_audio_archives_paths["test_5s"] if local_audio_archives_paths else None, |
|
"metapath": dl_dir["metadata_5s"], |
|
"split": "test_multilabel" |
|
}, |
|
), |
|
] |
|
|
|
return [ |
|
datasets.SplitGenerator( |
|
name=datasets.Split.TRAIN, |
|
gen_kwargs={ |
|
"audio_archive_iterators": [dl_manager.iter_archive(archive_path) for archive_path in dl_dir["train"]], |
|
"local_audio_archives_paths": local_audio_archives_paths["train"] if local_audio_archives_paths else None, |
|
"metapath": dl_dir["meta_train"], |
|
"split": datasets.Split.TRAIN, |
|
}, |
|
), |
|
datasets.SplitGenerator( |
|
name=datasets.Split.TEST, |
|
gen_kwargs={ |
|
"audio_archive_iterators": [dl_manager.iter_archive(archive_path) for archive_path in dl_dir["test"]], |
|
"local_audio_archives_paths": local_audio_archives_paths["test"] if local_audio_archives_paths else None, |
|
"metapath": dl_dir["meta_test"], |
|
"split": datasets.Split.TEST, |
|
}, |
|
), |
|
datasets.SplitGenerator( |
|
name="test_5s", |
|
gen_kwargs={ |
|
"audio_archive_iterators": [dl_manager.iter_archive(archive_path) for archive_path in dl_dir["test_5s"]], |
|
"local_audio_archives_paths": local_audio_archives_paths["test_5s"] if local_audio_archives_paths else None, |
|
"metapath": dl_dir["meta_test_5s"], |
|
"split": "test_multilabel" |
|
}, |
|
), |
|
] |
|
|
|
def _generate_examples(self, audio_archive_iterators, local_audio_archives_paths, metapath, split): |
|
metadata = pd.read_parquet(metapath) |
|
idx = 0 |
|
for i, audio_archive_iterator in enumerate(audio_archive_iterators): |
|
for audio_path_in_archive, audio_file in audio_archive_iterator: |
|
id = os.path.split(audio_path_in_archive)[-1] |
|
rows = metadata[metadata.index == (int(id[2:].split(".")[0]) if split == "train" else id)] |
|
audio_path = os.path.join(local_audio_archives_paths[i], audio_path_in_archive) if local_audio_archives_paths else audio_path_in_archive |
|
|
|
audio = audio_path if local_audio_archives_paths else audio_file.read() |
|
for _, row in rows.iterrows(): |
|
idx += 1 |
|
yield id if split == "train" else idx, { |
|
"audio": audio, |
|
"filepath": audio_path, |
|
"start_time": row["start_time"], |
|
"end_time": row["end_time"], |
|
"low_freq": row["low_freq"], |
|
"high_freq": row["high_freq"], |
|
"ebird_code": row["ebird_code"] if split != "test_multilabel" else None, |
|
|
|
"ebird_code_multilabel": row.get("ebird_code_multilabel", None) if "no_call" not in row.get("ebird_code_multilabel", []) else [], |
|
"ebird_code_secondary": row.get("ebird_code_secondary", None), |
|
"call_type": row["call_type"], |
|
"sex": row["sex"], |
|
"lat": row["lat"], |
|
"long": row["long"], |
|
"length": row.get("length", None), |
|
"microphone": row["microphone"], |
|
"license": row.get("license", None), |
|
"source": row["source"], |
|
"local_time": row["local_time"], |
|
"detected_events": row.get("detected_events", None), |
|
"event_cluster": row.get("event_cluster", None), |
|
"peaks": row.get("peaks", None), |
|
"quality": row.get("quality", None), |
|
"recordist": row.get("recordist", None) |
|
} |
|
|