task_categories:image-to-image task_categories:video-classification language:en license:cc-by-nd-4.0 code finance region:us
The dataset consists of 40,000 videos and selfies with unique people. 15,000
attack replays from 4,000 unique devices. 10,000 attacks with A4 printouts and
10,000 attacks with cut-out printouts.
@InProceedings{huggingface:dataset,
title = {printed_photos_attacks},
author = {TrainingDataPro},
year = {2023}
}
---
license: cc-by-nd-4.0
task_categories:
- image-to-image
- video-classification
language:
- en
tags:
- code
- finance
---

# Printed Photos Attacks
The dataset includes 3 different types of files of the real people: original selfies, original videos and videos of attacks with printed photos. The dataset solves tasks in the field of anti-spoofing and it is useful for buisness and safety systems.

# Get the dataset

### This is just an example of the data

Leave a request on [**https://trainingdata.pro/data-market**](https://trainingdata.pro/data-market?utm_source=huggingface&utm_medium=cpc&utm_campaign=printed_photos_attacks) to discuss your requirements, learn about the price and buy the dataset.

# Content
### The dataset contains of three folders:
- **live_selfie** contains the original selfies of people
- **live_video** includes original videos of people
- **attack** contains video of the attack with the original images from "live_selfie" folder

### File with the extension .csv
includes the following information for each media file:
- **live_selfie**: the link to access the original selfie
- **live_video**: the link to access the original video
- **attack**: the link to access the video of the attack with the printed photo

## [**TrainingData**](https://trainingdata.pro/data-market?utm_source=huggingface&utm_medium=cpc&utm_campaign=printed_photos_attacks) 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**