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metadata
license: cc-by-nc-nd-4.0
task_categories:
  - image-classification
  - video-classification
  - image-to-image
language:
  - en
tags:
  - legal
dataset_info:
  features:
    - name: photo
      dtype: image
    - name: video
      dtype: string
    - name: phone
      dtype: string
    - name: gender
      dtype: string
    - name: age
      dtype: int8
    - name: country
      dtype: string
  splits:
    - name: train
      num_bytes: 21414921
      num_examples: 10
  download_size: 239042378
  dataset_size: 21414921

Selfie and Video on Back Camera Dataset

The dataset consists of selfies and video of real people made on a back camera of the smartphone. The dataset solves tasks in the field of anti-spoofing and it is useful for buisness and safety systems.

The dataset includes 2 different types of files:

  • Photo - a selfie of a person from a mobile phone, the person is depicted alone on it, the face is clearly visible.
  • Video - filmed on the front camera, on which a person moves his/her head left, right, up and down. Duration of the video is from 10 to 20 seconds.

Get the dataset

This is just an example of the data

Leave a request on https://trainingdata.pro/datasets to discuss your requirements, learn about the price and buy the dataset.

Content

Phone models in the datset:

  • iPhone 13 mini
  • iPhone 11
  • iPhone XR
  • iPhone 8 plus
  • Samsung A80
  • Samsung galaxy A51 5G
  • Samsung A32
  • Samsung Galaxy S10 5G

File with the extension .csv

includes the following information for each media file:

  • photo: link to access the selfie,
  • video: link to access the video,
  • phone: the device used to capture selfie and video,
  • gender: gender of a person,
  • age: age of the person,
  • country: country of the person

TrainingData provides high-quality data annotation tailored to your needs

More datasets in TrainingData's Kaggle account: https://www.kaggle.com/trainingdatapro/datasets

TrainingData's GitHub: https://github.com/Trainingdata-datamarket/TrainingData_All_datasets

keywords: biometric system, biometric dataset, face recognition database, face recognition dataset, face detection dataset, facial analysis, object detection dataset, deep learning datasets, computer vision datset, human images dataset, human videos dataset, human faces dataset, machine learning, video-to-image, re-identification, verification models, video dataset, video classification, video recognition, photos and videos