Update README.md

README.md

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 - legal
 - finance
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+# Biometric Attack Dataset - Different Lighting Conditions Dataset
+The liveness detection dataset consists of videos of individuals and attacks with photos shown in the monitor . Videos are filmed in different lightning conditions (*in a dark room, daylight, light room and nightlight*) and in different places (*indoors, outdoors*). Each video in the dataset has an approximate duration of 20 seconds. 
 
-
-# Biometric Attacks in Different Lighting Conditions Dataset
-The dataset consists of videos of individuals and attacks with photos shown in the monitor . Videos are filmed in different lightning conditions (*in a dark room, daylight, light room and nightlight*) and in different places (*indoors, outdoors*). Each video in the dataset has an approximate duration of 20 seconds. 
+# 💴 For Commercial Usage: Full version of the dataset includes 7296 videos, leave a request on **[TrainingData](https://trainingdata.pro/datasets?utm_source=huggingface&utm_medium=cpc&utm_campaign=biometric-attacks-in-different-lighting-conditions)** to buy the dataset
 
 ### Types of videos in the dataset:
 - **darkroom_photo** - photo of a person in a **dark room** shown on a computer and filmed on the phone
@@ -23,21 +23,17 @@ The dataset consists of videos of individuals and attacks with photos shown in t
 - **daylight_video** - filmed in a **daylight**, on which a person moves his/her head left, right, up and down
 - **lightroom_video** -  filmed in a **light room**, on which a person moves his/her head left, right, up and down
 - **nightlight_video** - filmed in a **night light**, on which a person moves his/her head left, right, up and down
-- **mask** -  video of the person wearing a **printed 2D mask**
-- **outline** - video of the person wearing a **printed 2D mask with cut-out holes for eyes**
+- **outline** -video of the person wearing a **printed 2D mask**
+- **mask** -   video of the person wearing a **printed 2D mask with cut-out holes for eyes**
 - **monitor_video** - video of a person played on a computer and filmed on the phone
 
 ![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2F5f1a0a11908deb6f62b6cb7c7b0d47ad%2FMacBook%20Air%20-%201%20(2).png?generation=1691658152306937&alt=media)
 
-The dataset serves as a valuable resource for computer vision, anti-spoofing tasks, video analysis, and security systems. It allows for the development of algorithms and models that can effectively detect attacks.
-
-Studying the dataset may lead to the development of improved security systems, surveillance technologies, and solutions to mitigate the risks associated with masked individuals carrying out attacks.
-
-# Get the dataset
+The dataset comprises videos of genuine facial presentations using various methods, including printed 2D photos, masks as well as real and spoof faces. It proposes a novel approach that learns and extracts facial features to prevent spoofing attacks, based on deep neural networks and advanced biometric techniques.
 
-### This is just an example of the data
+Our results show that this technology works effectively in securing most applications and prevents unauthorized access by distinguishing between genuine and spoofed inputs. Additionally, it addresses the challenging task of identifying unseen spoofing cues, making it one of the most effective techniques in the field of anti-spoofing research.
 
-Leave a request on [**https://trainingdata.pro/data-market**](https://trainingdata.pro/data-market?utm_source=huggingface&utm_medium=cpc&utm_campaign=biometric-attacks-in-different-lighting-conditions) to discuss your requirements, learn about the price and buy 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?utm_source=huggingface&utm_medium=cpc&utm_campaign=biometric-attacks-in-different-lighting-conditions) to discuss your requirements, learn about the price and buy the dataset**
 
 # Content
 - **files** - contains of original videos and videos of attacks,
@@ -47,10 +43,10 @@ Leave a request on [**https://trainingdata.pro/data-market**](https://trainingda
 - **file**: link to the video,
 - **type**: type of the video
 
-# Attacks might be collected in accordance with your requirements.
-
-## [**TrainingData**](https://trainingdata.pro/data-market?utm_source=huggingface&utm_medium=cpc&utm_campaign=biometric-attacks-in-different-lighting-conditions) provides high-quality data annotation tailored to your needs
+## **[TrainingData](https://trainingdata.pro/datasets?utm_source=huggingface&utm_medium=cpc&utm_campaign=biometric-attacks-in-different-lighting-conditions)** 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, , video replay attack, replay attack dataset, replay attack database, replay mobile dataset, video attack attempts, liveness detection systems, liveness detection dataset, biometric dataset, biometric data dataset, biometric system attacks, anti-spoofing dataset, face liveness detection, deep learning dataset, face spoofing database, face anti-spoofing, face recognition, face detection, face identification, human video dataset, video dataset, presentation attack detection, presentation attack dataset, 2d print attacks, print 2d attacks dataset, phone attack dataset, face anti spoofing, large-scale face anti spoofing, rich annotations anti spoofing dataset, cut prints spoof attack*