import os import datasets _CITATION = """\ @InProceedings{huggingface:dataset, title = {Unsplash Lite Dataset 1.2.0 Photos}, author={Unsplash}, year={2022} } """ _DESCRIPTION = """\ This is a dataset that streams photos data from the Unsplash 25K servers. """ _HOMEPAGE = "https://github.com/unsplash/datasets/" _LICENSE = "" _URL = "https://unsplash.com/data/lite/latest" class Unsplash(datasets.GeneratorBasedBuilder): """The Unsplash 25K dataset for photos""" def _info(self): return datasets.DatasetInfo( description=_DESCRIPTION, features=datasets.Features( { 'photo_id': datasets.Value("string"), 'photo_url': datasets.Value("string"), 'photo_image_url': datasets.Value("string"), 'photo_submitted_at': datasets.Value("string"), 'photo_featured': datasets.Value("string"), 'photo_width': datasets.Value("int32"), 'photo_height': datasets.Value("int32"), 'photo_aspect_ratio': datasets.Value("float32"), 'photo_description': datasets.Value("string"), 'photographer_username': datasets.Value("string"), 'photographer_first_name': datasets.Value("string"), 'photographer_last_name': datasets.Value("string"), 'exif_camera_make': datasets.Value("string"), 'exif_camera_model': datasets.Value("string"), 'exif_iso': datasets.Value("string"), 'exif_aperture_value': datasets.Value("string"), 'exif_focal_length': datasets.Value("string"), 'exif_exposure_time': datasets.Value("string"), 'photo_location_name': datasets.Value("string"), 'photo_location_latitude': datasets.Value("string"), 'photo_location_longitude': datasets.Value("string"), 'photo_location_country': datasets.Value("string"), 'photo_location_city': datasets.Value("string"), 'stats_views': datasets.Value("uint32"), 'stats_downloads': datasets.Value("uint32"), 'ai_description': datasets.Value("string"), 'ai_primary_landmark_name': datasets.Value("string"), 'ai_primary_landmark_latitude': datasets.Value("string"), 'ai_primary_landmark_longitude': datasets.Value("string"), 'ai_primary_landmark_confidence': datasets.Value("string"), 'blur_hash': datasets.Value("string"), } ), supervised_keys=None, homepage="https://github.com/unsplash/datasets/", citation=_CITATION, ) def _split_generators(self, dl_manager): new_url = dl_manager.download_and_extract(_URL) # remove extra files for file in os.listdir(new_url): if os.path.isfile(new_url+"/"+file): if file != 'photos.tsv000': os.remove(new_url+'/'+file) return [ datasets.SplitGenerator( name=datasets.Split.TRAIN, gen_kwargs={"filepath": os.path.join(new_url, "photos.tsv000")} ), ] def _generate_examples(self, filepath): """This function returns the examples in the raw (text) form.""" with open(filepath, "r", encoding="utf-8") as f: id_ = 0 for line in f: if id_ == 0: cols = line.strip().split("\t") id_ += 1 else: values = line.strip().split("\t") if len(values) != len(cols): values.extend(['']*(len(cols)-len(values))) yield id_, {cols[i]: values[i] for i in range(len(cols))} id_ += 1