Update README.md

README.md

@@ -27,37 +27,56 @@ dataset_info:
   download_size: 735628032
   dataset_size: 5063
 ---
-
-# Anti-Spoofing dataset: replay
+# Antispoofing Replay - Biometric Attack dataset
 The dataset consists of 30,000+ videos of replay attacks from people from 157 countries. 
-It is based on data from **Anti Spoofing Real Dataset**: https://huggingface.co/datasets/TrainingDataPro/anti-spoofing_Real. 
-The dataset solves tasks in the field of anti-spoofing and it is useful for buisness and safety systems. 
+It is based on data from **Anti Spoofing Real Dataset**: https://www.kaggle.com/datasets/trainingdatapro/anti-spoofing-live. 
 
-The dataset includes: **replay attacks** - videos from Antispoofing Real filmed on the phone.
+The anti spoofing dataset includes: **replay attacks** - videos from Antispoofing Real filmed on the phone.
 
-# Get the dataset
+The videos were gathered by capturing faces of genuine individuals presenting spoofs, using facial presentations. Our dataset proposes a novel approach that learns and detects spoofing techniques, extracting features from the genuine facial images to prevent the capturing of such information by fake users. 
 
-### This is just an example of the data
+The dataset contains images and videos of real humans with various **resolutions, views, and colors**, making it a comprehensive resource for researchers working on anti-spoofing technologies.
 
-Leave a request on [**https://trainingdata.pro/data-market**](https://trainingdata.pro/data-market/anti-spoofing-replay?utm_source=huggingface&utm_medium=cpc&utm_campaign=anti-spoofing_replay) to discuss your requirements, learn about the price and buy the dataset.
+![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2F0fe0cca9d56fd2c013589667097b24b9%2Freplay.png?generation=1685095721064910&alt=media)
 
-# File with the extension .csv
-includes the following information for each media file:
+The dataset provides data to combine and apply different techniques, approaches, and models to address the challenging task of distinguishing between genuine and spoofed inputs, providing effective anti-spoofing solutions in active authentication systems. These solutions are crucial as newer devices, such as phones, have become vulnerable to spoofing attacks due to the availability of technologies that can create replays, reflections, and depths, making them susceptible to spoofing and generalization. 
+
+Our dataset also explores the use of neural architectures, such as deep neural networks, to facilitate the identification of distinguishing patterns and textures in different regions of the face, increasing the accuracy and generalizability of the anti-spoofing models. 
+
+# 💴 For Commercial Usage: Full version of the dataset includes 30 000+ videos, leave a request on **[TrainingData](https://trainingdata.pro/datasets/anti-spoofing-replay?utm_source=huggingface&utm_medium=cpc&utm_campaign=anti-spoofing_replay)** to buy the dataset
+
+### Metadata for the full dataset:
+- **replay.assignment_id** - unique identifier of the media file
+- **real_assignment_id**- unique identifier of the media file from the [Antispoofing Real Dataset](https://trainingdata.pro/datasets/antispoofing-real?utm_source=huggingface&utm_medium=cpc&utm_campaign=antispoofing-replay-dataset)
+- **worker_id** - unique identifier of the person
+- **age** - age of the person
+- **true_gender** - gender of the person
+- **country** - country of the person
+- **ethnicity** - ethnicity of the person
+- **video_extension** - video extensions in the dataset
+- **video_resolution** - video resolution in the dataset
+- **video_duration** - video duration in the dataset
+- **video_fps** - frames per second for video in the dataset
+
+# 💴 Buy the Dataset: This is just an example of the data. Leave a request on **[https://trainingdata.pro/datasets](https://trainingdata.pro/datasets/anti-spoofing-replay?utm_source=huggingface&utm_medium=cpc&utm_campaign=anti-spoofing_replay) to discuss your requirements, learn about the price and buy the dataset**
 
+# Content
+### The folder **"samples"** includes 30 folders:
+- corresponding to each person in the sample
+- containing of the video of replay attack 
+
+### File with the extension .csv
+includes the following information for each media file:
 - **live_video_id**: the unique identifier of the "Antispoofing Live" video
 - **phone**: the device used to capture the replay video,
 - **link**: the URL to access the replay video,
 - **phone_video_payback**: the device used to play the "Antispoofing Live" video,
 - **worker_id**: the identifier of the person who provided the media file,
 
-# 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/anti-spoofing-replay?utm_source=huggingface&utm_medium=cpc&utm_campaign=anti-spoofing_replay) provides high-quality data annotation tailored to your needs
+**[TrainingData](https://trainingdata.pro/datasets/anti-spoofing-replay?utm_source=huggingface&utm_medium=cpc&utm_campaign=anti-spoofing_replay)** 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**
+TrainingData's GitHub: **https://github.com/Trainingdata-datamarket/TrainingData_All_datasets**
+
+*keywords: ibeta level 1, ibeta level 2, liveness detection systems, liveness detection dataset, biometric dataset, biometric data dataset, biometric system attacks, anti-spoofing dataset, face liveness detection, deep learning dataset, video replay attack, replay attack dataset, replay attack database, replay mobile dataset, video attack attempts, face spoofing database, face anti-spoofing, face recognition, face detection, face identification, human video dataset, video dataset, phone attack dataset, face anti spoofing, large-scale face anti spoofing, rich annotations anti spoofing dataset, replay spoof attack, display spoof attack*