Introduction

Welcome to the South Asian Human Facial Images Dataset, curated to advance facial recognition technology and support the development of secure biometric identity systems, KYC verification processes, and AI-driven computer vision applications. This dataset is designed to serve as a robust foundation for real-world face matching and recognition use cases.

Facial Image Data

The dataset contains over 8,000 facial image sets of South Asian individuals. Each set includes:

Diversity & Representation

Image Quality & Capture Conditions

All images were captured with real-world variability to enhance dataset robustness:

Metadata

Each participant’s data is accompanied by rich metadata to support AI model training, including:

This metadata enables targeted filtering and training across diverse scenarios.

Use Cases & Applications

This dataset is ideal for a wide range of AI and biometric applications:

Secure & Ethical Collection

Dataset Updates & Customization

To meet evolving AI demands, this dataset is regularly updated and can be customized. Available options include:

Introduction

Welcome to the South Asian Multi-Year Facial Image Dataset, thoughtfully curated to support the development of advanced facial recognition systems, biometric identification models, KYC verification tools, and other computer vision applications. This dataset is ideal for training AI models to recognize individuals over time, track facial changes, and enhance age progression capabilities.

Facial Image Data

This dataset includes over 10,000+ high-quality facial images, organized into individual participant sets, each containing:

Diversity & Representation

Image Quality & Capture Conditions

To ensure model generalization and practical usability, images in this dataset reflect real-world diversity:

Metadata

Each participant’s dataset is accompanied by rich metadata to support advanced model training and analysis, including:

Use Cases & Applications

This dataset is highly valuable for a wide range of AI and computer vision applications:

Secure & Ethical Collection

Dataset Updates & Customization

To keep pace with evolving AI needs, this dataset is regularly updated and customizable. Custom data collection options include:

A number plate dataset is a collection of images and corresponding annotations that are used to train a machine learning model to recognize and locate number plates (also known as license plates) in images. The dataset typically consists of images of vehicles taken from various angles and under different lighting conditions, along with annotations specifying the location of the number plates in the images.

The goal of a number plate detection model is to accurately identify and locate the number plates in an image, regardless of the angle, lighting conditions, or background. This can be useful for applications such as automating the process of reading number plates for traffic monitoring, parking management, and vehicle identification.

The annotations in a number plate detection dataset may include the bounding box coordinates of the number plate in the image, as well as the text of the number plate. The dataset may also include additional metadata, such as the type of vehicle (car, truck, etc.), the location where the image was taken, and the date and time the image was taken.

Introduction

Welcome to the South Asian Facial Expression Image Dataset, curated to support the development of advanced facial expression recognition systems, biometric identification models, KYC verification processes, and a wide range of facial analysis applications. This dataset is ideal for training robust emotion-aware AI solutions.

Facial Expression Data

The dataset includes over 2000 high-quality facial expression images, grouped into participant-wise sets. Each participant contributes:

Diversity & Representation

Image Quality & Capture Conditions

To ensure generalizability and robustness in model training, images were captured under varied real-world conditions:

Metadata

Each participant's image set is accompanied by detailed metadata, enabling precise filtering and training:

This metadata helps in building expression recognition models that are both accurate and inclusive.

Use Cases & Applications

This dataset is ideal for a variety of AI and computer vision applications, including:

Secure & Ethical Collection

Dataset Updates & Customization

To support evolving AI development needs, this dataset is regularly updated and can be tailored to project-specific requirements. Custom options include:

A devastating earthquake shook the western Himalaya and adjoining regions on the morning of 8th October 2005. The magnitude 7.6 earthquake killed at least 86,000 people, injured more than 69,000 and caused extensive damage in northern Pakistan. The heaviest damage occurred in the Muzaffarabad area, Kashmir where entire villages were destroyed and at Uri where 80 percent of the town was destroyed. At least 32,335 buildings collapsed in Anantnag, Baramula, Jammu and Srinagar, Kashmir. Buildings collapsed in Abbottabad, Gujranwala, Gujrat, Islamabad, Lahore and Rawalpindi, Pakistan. At least 1,360 people killed and 6,266 injured in India. At least one person killed and some buildings collapsed in Afghanistan. Landslides and rockfalls damaged or destroyed several mountain roads and highways cutting off access to the region for several days. Landslides occurred farther north near the towns of Gilgit and Skardu, Kashmir. Liquefaction and sandblows occurred in the western part of Vale of Kashmir and near Jammu.