- Description:
VGGFace2 is a large-scale face recognition dataset. Images are downloaded from Google Image Search and have large variations in pose, age, illumination, ethnicity and profession. VGGFace2 contains images from identities spanning a wide range of different ethnicities, accents, professions and ages. All face images are captured "in the wild", with pose and emotion variations and different lighting and occlusion conditions. Face distribution for different identities is varied, from 87 to 843, with an average of 362 images for each subject.
Homepage: http://zeus.robots.ox.ac.uk/vgg_face2/
Source code:
tfds.image_classification.VggFace2
Versions:
1.0.0
(default): No release notes.
Download size:
Unknown size
Dataset size:
Unknown size
Manual download instructions: This dataset requires you to download the source data manually into
download_config.manual_dir
(defaults to~/tensorflow_datasets/downloads/manual/
):
manual_dir should contain two files: vggface2_test.tar.gz and vggface2_train.tar.gz. You need to register on http://zeus.robots.ox.ac.uk/vgg_face2/signup/ in order to get the link to download the dataset.Auto-cached (documentation): Unknown
Splits:
Split | Examples |
---|---|
'test' |
169,396 |
'train' |
3,141,890 |
- Features:
FeaturesDict({
'file_name': Text(shape=(), dtype=tf.string),
'image': Image(shape=(None, None, 3), dtype=tf.uint8),
'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=9131),
})
Supervised keys (See
as_supervised
doc):('image', 'label')
Citation:
@InProceedings{Cao18,
author = "Cao, Q. and Shen, L. and Xie, W. and Parkhi, O. M. and Zisserman, A.",
title = "VGGFace2: A dataset for recognising faces across pose and age",
booktitle = "International Conference on Automatic Face and Gesture Recognition",
year = "2018"}
- Figure (tfds.show_examples):
- Examples (tfds.as_dataframe):