README.md

---
license: cc-by-nc-nd-4.0
task_categories:
- image-to-image
- video-classification
language:
- en
tags:
- code
dataset_info:
  features:
  - name: phone
    dtype: string
  - name: selfie
    dtype: image
  - name: video
    dtype: string
  - name: worker_id
    dtype: string
  - name: age
    dtype: int8
  - name: country
    dtype: string
  - name: gender
    dtype: string
  splits:
  - name: train
    num_bytes: 100634313
    num_examples: 30
  download_size: 568013310
  dataset_size: 100634313
---
# Anti-Spoofing dataset: live

The dataset consists of 40,000 videos and selfies with unique people. 15,000 attack replays from 4,000 unique devices.

# File with the extension .csv

includes the following information for each media file:

- **phone**: the device used to capture the media files,
- **selfie_link**: the URL to access the photo
- **video_link**: the URL to access the video
- **worker_id**: the identifier of the person who provided the media file,
- **age**: the age of the person,
- **country**: the country of origin of the person,
- **gender**: the gender of the person,
- **selfie_file_type**: the type of the photo,
- **video_file_type**: the type of the video

# Folder "img" with media files

- containg all the photos and videos
- which correspond to the data in the .csv file

**How it works**: *go to the first folder and you will make sure that it contains media files taken by a person whose parameters are specified in the first line of the .csv file.*

In order to get access to more than 80,000 media files from 4,000 people or to learn more about our data, please contact our sales team by submitting a request on our website <https://trainingdata.pro/data-market?utm_source=huggingface> or emaling us at <[email protected]>

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

TrainingData's GitHub: **<https://github.com/trainingdata-pro>**