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import io
import datasets
import pandas as pd
_CITATION = """\
@InProceedings{huggingface:dataset,
title = {portrait_and_26_photos},
author = {TrainingDataPro},
year = {2023}
}
"""
_DESCRIPTION = """\
Each set includes 27 photos of people. Each person provided
two types of photos: one photo in profile (portrait_1),
and 26 photos from their life (photo_1, photo_2, …, photo_26).
"""
_NAME = 'portrait_and_26_photos'
_HOMEPAGE = f"https://huggingface.co/datasets/TrainingDataPro/{_NAME}"
_LICENSE = ""
_DATA = f"https://huggingface.co/datasets/TrainingDataPro/{_NAME}/resolve/main/data/"
class PortraitAnd26Photos(datasets.GeneratorBasedBuilder):
"""Small sample of image-text pairs"""
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features({
'portrait_1': datasets.Image(),
'photo_1': datasets.Image(),
'photo_2': datasets.Image(),
'photo_3': datasets.Image(),
'photo_4': datasets.Image(),
'photo_5': datasets.Image(),
'photo_6': datasets.Image(),
'photo_7': datasets.Image(),
'photo_8': datasets.Image(),
'photo_9': datasets.Image(),
'photo_10': datasets.Image(),
'photo_11': datasets.Image(),
'photo_12': datasets.Image(),
'photo_13': datasets.Image(),
'photo_14': datasets.Image(),
'photo_15': datasets.Image(),
'photo_16': datasets.Image(),
'photo_17': datasets.Image(),
'photo_18': datasets.Image(),
'photo_19': datasets.Image(),
'photo_20': datasets.Image(),
'photo_21': datasets.Image(),
'photo_22': datasets.Image(),
'photo_23': datasets.Image(),
'photo_24': datasets.Image(),
'photo_25': datasets.Image(),
'photo_26': datasets.Image(),
'worker_id': datasets.Value('string'),
'age': datasets.Value('int8'),
'country': datasets.Value('string'),
'gender': datasets.Value('string')
}),
supervised_keys=None,
homepage=_HOMEPAGE,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
images = dl_manager.download(f"{_DATA}images.tar.gz")
annotations = dl_manager.download(f"{_DATA}{_NAME}.csv")
images = dl_manager.iter_archive(images)
return [
datasets.SplitGenerator(name=datasets.Split.TRAIN,
gen_kwargs={
"images": images,
'annotations': annotations
}),
]
def _generate_examples(self, images, annotations):
annotations_df = pd.read_csv(annotations, sep=',')
images_data = pd.DataFrame(columns=['Link', 'Bytes'])
for idx, (image_path, image) in enumerate(images):
images_data.loc[idx] = {'Link': image_path, 'Bytes': image.read()}
annotations_df = pd.merge(annotations_df, images_data)
for idx, worker_id in enumerate(pd.unique(annotations_df['WorkerId'])):
annotation = annotations_df.loc[annotations_df['WorkerId'] ==
worker_id]
annotation = annotation.sort_values(['Type'])
data = {
row[5]: {
'path': row[6],
'bytes': row[7]
} for row in annotation.itertuples()
}
age = annotation.loc[annotation['Type'] ==
'portrait_1']['Age'].values[0]
country = annotation.loc[annotation['Type'] ==
'portrait_1']['Country'].values[0]
gender = annotation.loc[annotation['Type'] ==
'portrait_1']['Gender'].values[0]
data['worker_id'] = worker_id
data['age'] = age
data['country'] = country
data['gender'] = gender
yield idx, data
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