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Licensed dataset
Dataset for training a neural network in face recognition and identification tasks using selfie and 26 photos of a person.
Portrait 26 Photos Dataset
Enables computer systems to automatically learn from data and make predictions
Machine Learning
Process of identifying a specific entity across different data
Re-identification
Gathering data for subsequent annotation
Data Collection
Process of identifying or verify a person identity using facial features
Facial Recognition
7 344
photos
272
people
19.3
GB
10.0
usability
Technical specifications
Each person took 1 selfie and attached 26 photos of themselves in different lighting and environments:
Selfie portrait has strict criteria:
- the photo is cropped above shoulders,
- the person is depicted alone,
- there are no sunglasses or a medical mask on the face,
- calm expression, no smiling
- Everyday life photos have different formats. There are photos captured with the phone, group photos, holiday photos. A person in the photos can be moving or expressing emotions. However, he or she is present in all the photos and his/her face can be easily recognized.
26 photos from life
- Photos from everyday life include pictures taken in different locations, with different people, but a person from the Selfie Portrait is always present on all of them.
Metadata:
Age
Gender
Person’s ID
File type
Country of origin of the person
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