# Anti-Spoofing dataset: real

The dataset consists of 140,000 videos and selfies with unique people. 51,000+ attack replays from 4,000+ unique devices.

# 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=anti-spoofing_Real) to discuss your requirements, learn about the price and buy the dataset.

# 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.*

## [**TrainingData**](https://trainingdata.pro/data-market?utm_source=huggingface&utm_medium=cpc&utm_campaign=anti-spoofing_Real) 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**
task_categories:image-to-image task_categories:video-classification language:en license:cc-by-nc-nd-4.0 code region:us
{"language": ["en"], "license": "cc-by-nc-nd-4.0", "task_categories": ["image-to-image", "video-classification"], "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}}
TAGS
#task_categories-image-to-image #task_categories-video-classification #language-English #license-cc-by-nc-nd-4.0 #code #region-us 

# Anti-Spoofing dataset: real

The dataset consists of 140,000 videos and selfies with unique people. 51,000+ attack replays from 4,000+ unique devices.

# Get the dataset

### This is just an example of the data

Leave a request on URL to discuss your requirements, learn about the price and buy the dataset.

# 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.*

## TrainingData provides high-quality data annotation tailored to your needs

More datasets in TrainingData's Kaggle account: <URL

TrainingData's GitHub: URL
# Anti-Spoofing dataset: real

The dataset consists of 140,000 videos and selfies with unique people. 51,000+ attack replays from 4,000+ unique devices. # Get the dataset ### This is just an example of the data

Leave a request on URL to discuss your requirements, learn about the price and buy the dataset. # 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.* ## TrainingData provides high-quality data annotation tailored to your needs

More datasets in TrainingData's Kaggle account: <URL

TrainingData's GitHub: URL
TAGS
#task_categories-image-to-image #task_categories-video-classification #language-English #license-cc-by-nc-nd-4.0 #code #region-us 
 # Anti-Spoofing dataset: real

The dataset consists of 140,000 videos and selfies with unique people. 51,000+ attack replays from 4,000+ unique devices. # Get the dataset ### This is just an example of the data

Leave a request on URL to discuss your requirements, learn about the price and buy the dataset. # 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.* ## TrainingData provides high-quality data annotation tailored to your needs

More datasets in TrainingData's Kaggle account: <URL

TrainingData's GitHub: URL
passage: TAGS
#task_categories-image-to-image #task_categories-video-classification #language-English #license-cc-by-nc-nd-4.0 #code #region-us 
# Anti-Spoofing dataset: real

The dataset consists of 140,000 videos and selfies with unique people. 51,000+ attack replays from 4,000+ unique devices.# Get the dataset### This is just an example of the data

Leave a request on URL to discuss your requirements, learn about the price and buy the dataset.# 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.*## TrainingData provides high-quality data annotation tailored to your needs

More datasets in TrainingData's Kaggle account: <URL

TrainingData's GitHub: URL