Datasets:
Languages:
English
Multilinguality:
monolingual
Size Categories:
10K<n<100K
Language Creators:
found
Annotations Creators:
found
| 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("int32"), | |
| 'stats_downloads': datasets.Value("int32"), | |
| '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") 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 |