import os import datasets from datasets import SplitGenerator, Split, ImageClassification from kaggle.api.kaggle_api_extended import KaggleApi _CITATION = """\ @TECHREPORT{gpiosenka/100-bird-species, author = {gpiosenka}, title = {BIRDS 525 SPECIES- IMAGE CLASSIFICATION}, institution = {}, year = {2023} } """ _DESCRIPTION = """\ A dataset of bird species downloaded from kaggle. """ _HOMEPAGE = "https://www.kaggle.com/datasets/gpiosenka/100-bird-species/" _DATA_DIR = 'data/' def _CLASSES() -> list[str]: # reads from bird_labels.txt, line by line with open("birds_labels.txt") as f: return f.read().splitlines() class BirdSpeciesDatasetDataset(datasets.GeneratorBasedBuilder): VERSION = datasets.Version("0.1.0") BUILDER_CONFIGS = [ datasets.BuilderConfig( name="plain_text", version=datasets.Version("0.1.0", ""), description="Import of BIRDS 525 SPECIES Data Set", ) ] def _info(self): _NAMES = _CLASSES() return datasets.DatasetInfo( description=_DESCRIPTION, features=datasets.Features( { "image": datasets.Image(), "label": datasets.features.ClassLabel(names=_NAMES), } ), supervised_keys=("image", "label"), homepage=_HOMEPAGE, citation=_CITATION, task_templates=ImageClassification(image_column="image", label_column="label"), ) def _split_generators(self, dl_manager): data_dir = _DATA_DIR # Downloading the dataset if not os.path.exists(data_dir): kaggle_api = KaggleApi() kaggle_api.authenticate() kaggle_api.dataset_download_files('gpiosenka/100-bird-species', path=data_dir, unzip=True) # There is a bug in the dataset, where one of the folders is named "PARAKETT AUKLET" instead of "PARAKETT AUKLET" # We fix it by adding a space to the valid folder, because train and test are wrong and also the names in the labels file # Fixing the path fault_path = os.path.join(data_dir, 'valid', 'PARAKETT AUKLET') correct_path = os.path.join(data_dir, 'valid', 'PARAKETT AUKLET') os.rename(fault_path, correct_path) return [ SplitGenerator(name=Split.TRAIN, gen_kwargs={"filepath": os.path.join(data_dir, "train")}), SplitGenerator(name=Split.VALIDATION, gen_kwargs={"filepath": os.path.join(data_dir, "valid")}), SplitGenerator(name=Split.TEST, gen_kwargs={"filepath": os.path.join(data_dir, "test")}), ] def _generate_examples(self, filepath): """Yields examples.""" idx = 0 for label in os.listdir(filepath): for f in os.listdir(os.path.join(filepath, label)): record = { "image": os.path.join(filepath, label, f), "label": label, } yield idx, record idx += 1 # To use the dataset: # from datasets import load_dataset # dataset = load_dataset('path/to/birds.py')