import os import json import datasets class Peter(datasets.GeneratorBasedBuilder): def _info(self): return datasets.DatasetInfo( features=datasets.Features( { "image": datasets.Image(), } ) ) def _split_generators(self, dl_manager): _URLS = { "images": "images.zip", "train_data": "annotations_train.json", "test_data": "annotations_test.json", "val_data": "annotations_val.json" } data_files = dl_manager.download_and_extract(_URLS) return [ datasets.SplitGenerator( name=datasets.Split.TRAIN, gen_kwargs={ "image_paths": dl_manager.iter_files(data_files["images"]), "annotation_path": data_files["train_data"], }, ), datasets.SplitGenerator( name=datasets.Split.TEST, gen_kwargs={ "image_paths": dl_manager.iter_files(data_files["images"]), "annotation_path": data_files["test_data"], }, ), datasets.SplitGenerator( name=datasets.Split.VALIDATION, gen_kwargs={ "image_paths": dl_manager.iter_files(data_files["images"]), "annotation_path": data_files["val_data"], }, ) ] def _generate_examples(self, image_paths, annotation_path): """Generate examples.""" with open(annotation_path, 'r') as f: data = json.load(f) image_names = set() for image_data in data['images']: image_names.add(image_data['file_name']) for idx, image_path in enumerate(image_paths): if os.path.basename(image_path) in image_names: example = { "image": image_path, } yield idx, example