Photos of people and their ID documents for facial recognition, Know Your Customer (KYC) and Re-identification models or software

Introduction

Welcome to the Caucasian 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 1,000 facial image sets of Caucasian 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:

Selfie Identity Dataset - 2 ID photo, 13 selfie

The dataset contains 65,000+ photo of more than 5,000 people from 40 countries, making it a valuable resource for exploring and developing identity verification solutions. This collection serves as a valuable resource for researchers and developers working on biometric verification solutions, especially in areas like facial recognition and financial services.

By utilizing this dataset, researchers can develop more robust re-identification algorithms, a key factor in ensuring privacy and security in various applications. - Get the data

Example of photos in the dataset

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F22059654%2F1014bc8e62e232cc2ecb28e7d8ccdc3c%2F.png?generation=1730863166146276&alt=media" alt="">

This dataset offers a opportunity to explore re-identification challenges by providing 13 selfies of individuals against diverse backgrounds with different lighting, paired with 2 ID photos from different document types.

💵 Buy the Dataset: This is a limited preview of the data. To access the full dataset, please contact us at https://unidata.pro to discuss your requirements and pricing options.

Metadata for the dataset

Devices: Samsung M31, Infinix note11, Tecno Pop 7, Samsung A05, Iphone 15 Pro Max and other

Resolution: 1000 x 750 and higher https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F22059654%2F0f1a70b3b5056e2610f22499cac19c7f%2FFrame%20136.png?generation=1730588713101089&alt=media" alt="">

This dataset enables the development of more robust and reliable authentication systems, ultimately contributing to enhancing customer onboarding experiences by streamlining verification processes, minimizing fraud, and improving overall security measures for a wide range of services, including online platforms, financial institutions, and government agencies.

🌐 UniData provides high-quality datasets, content moderation, data collection and annotation for your AI/ML projects

Introduction

Welcome to the Middle Eastern 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 1500 facial image sets of Middle Eastern 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:

Selfies, ID Images Face Dataset

5 591 sets, which includes 2 photos of a person from his documents and 13 selfies. 571 sets of Hispanics and 3512 sets of Caucasians.

Photo documents contains only a photo of a person. All personal information from the document is hidden

💴 For Commercial Usage: Full version of the dataset includes 95 000+ photos of people, leave a request on TrainingData to buy the dataset

Metadata for the full dataset:

• assignment_id - unique identifier of the media file
• 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
• photo_1_extension, photo_2_extension, …, photo_15_extension - photo extensions in the dataset
• photo_1_resolution, photo_2_resolution, …, photo_15_resolution - photo resolution in the dataset

Content

The dataset includes 2 folders: - 18_sets_Caucasians - images of Caucasian people - 11_sets_Hispanics - images Hispanic people

In each folder there are folders for every person in dataset. Files are named "ID_1", "ID_2" for ID images and "Selfie_1",..."Selfie_13" for selfies.

https://sun9-53.userapi.com/impg/dOFVs6YsLexi-rM0LBud5rc6bVsCQPq5bIvrnA/S-3MRJPo-IE.jpg?size=2560x1054&quality=95&sign=16fc124e8f61d43a371cf4f0712f6a14&type=album" alt="">

💴 Buy the Dataset: This is just an example of the data. Leave a request on https://trainingdata.pro/datasets to learn about the price and buy the dataset

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

keywords: biometric system, biometric dataset, face recognition database, face recognition dataset, face detection dataset, facial analysis, object detection dataset, deep learning datasets, computer vision datset, human images dataset, human faces dataset, machine learning, image-to-image, re-identification, id photos, selfies and paired id, photos, id verification models, passport, id card image, digital photo-identification

USA ID CARD FRONT

## Overview

USA ID CARD FRONT is a dataset for object detection tasks - it contains TEXT annotations for 29 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

The ID photo software market is experiencing robust growth, driven by the increasing demand for standardized digital identification across various sectors. The market, estimated at $500 million in 2025, is projected to witness a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033. This expansion is fueled by several key factors. The rising adoption of online services and digital identity verification systems across governments and enterprises necessitates efficient and compliant ID photo generation. Furthermore, the increasing use of smartphones and readily available image editing software has broadened the market's reach to individuals requiring personal ID photos for various applications, including passport and driver's license applications. Stringent government regulations regarding ID photo standards are also contributing to this growth, as businesses and individuals seek compliant software solutions. The market segmentation reveals a strong preference for software designed for passport and driver's license photos, with the enterprise segment also exhibiting significant growth. The competition within the ID photo software market is fierce, with established players like Adobe Photoshop alongside specialized software providers vying for market share. However, the market offers significant opportunities for innovative solutions that integrate advanced features like AI-powered facial recognition for automatic compliance checks and streamlined workflows for high-volume processing. Future growth will likely be influenced by advancements in biometric technology, cloud-based solutions, and increasing demand for mobile-friendly applications. Geographic expansion, particularly in developing economies with burgeoning digitalization, presents lucrative opportunities for market players. While challenges such as security concerns and the need for constant updates to meet evolving regulatory standards exist, the overall market outlook remains positive, anticipating sustained growth throughout the forecast period.

It has been shown through a variety of photo-identification studies that populations of bottlenose dolphin inhabit the various embayments along the coast of Florida. Knowledge of population stock structure is critical to developing management plans and understanding how stressors impact individual populations. Researchers have found that photo-identification is one of the best ways to study populations of bottlenose dolphin in near shore environments. Unlike aerial and ship-board surveys, individual dolphins can be identified and tracked temporally and spatially, giving investigators a more comprehensive picture of population stock structure

Introduction

Welcome to the Native American 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 1,000 facial image sets of Native American 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:

Photo-identification data on sperm whales occupying the north central Gulf of Mexico have been collected during vessel surveys. Photographs of sperm whales are taken during encounters and markings on tail flukes can be used to identify individual animals. These images have been reviewed and individuals cataloged to evaluate residency and demographic patterns in sperm whales in the northern Gulf of Mexico.

Matching unfamiliar faces is known to be difficult, and this can give an opportunity to those engaged in identity fraud. Here we examine a relatively new form of fraud, the use of photo-ID containing a graphical morph between two faces. Such a document may look sufficiently like two people to serve as ID for both. We present two experiments with human viewers, and a third with a smartphone face recognition system. In Experiment 1, viewers were asked to match pairs of faces, without being warned that one of the pair could be a morph. They very commonly accepted a morphed face as a match. However, in Experiment 2, following very short training on morph detection, their acceptance rate fell considerably. Nevertheless, there remained large individual differences in people’s ability to detect a morph. In Experiment 3 we show that a smartphone makes errors at a similar rate to ‘trained’ human viewers—i.e. accepting a small number of morphs as genuine ID. We discuss these results in reference to the use of face photos for security.

Introduction

Welcome to the African 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 2,000 facial image sets of African 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:

The global passport photo and ID printer systems market is projected to witness significant growth over the forecast period, driven by rising demand for secure and efficient identification solutions. The increasing need for enhanced security and the growing awareness of identity theft are the key factors driving the market growth. Additionally, the proliferation of digital technology and the adoption of mobile identification systems are creating new opportunities for market expansion. The market is expected to reach a valuation of USD XX million by 2033, exhibiting a CAGR of XX% during the forecast period. Some of the key market trends include: increasing adoption of desktop compact printers due to their portability and affordability, growing demand for high-quality passport and ID photos, and the emergence of advanced technologies such as facial recognition and biometrics. The key players in the market include Matica, Toshiba, Datacard Group, and Pakor, among others. The market is expected to witness increased competition as new entrants emerge and existing players expand their product offerings. North America and Asia Pacific are expected to be the key regions driving the market growth, with emerging markets offering significant potential for expansion.

The ability to correctly and consistently identify sea turtles over time was evaluated using digital imagery of the turtles dorsal and side views of their heads and dorsal views of their carapaces

This dataset is about books. It has 1 row and is filtered where the book is Photo-ID : photographers and scientists explore identity. It features 7 columns including author, publication date, language, and book publisher.

Dataset of 3623 images from 1661 users (~2.18/user), mainly front/back ID documents, ideal for OCR training, document recognition, and automated identity verification tasks.

The images are in the ImageNet structure, with each class having its own folder containing the respective images. The images have a resolution of 256x256 pixels.

Dataset Details:

• Total number of classes: 14
• Total number of images: 3279
• Resolution: 256x256 pixels
• Image format: JPG

If you find this dataset useful or interesting, please don't forget to show your support by Upvoting! 🙌👍

Data Collection Methodology:

To create this dataset, - I searched for each PC part on Google Images and extracted the image links. - I then downloaded the full-size images from the original source and converted them to JPG format with a resolution of 256 pixels. - During the process, most images were downscaled, with only a very few being upscaled. - Finally, I manually went over all the images and deleted any that didn't fit well for image classification.

Potential Task Ideas:

1. Train an image classification model using popular architectures like ViT, ResNet, or EfficientNet.
2. Perform transfer learning on this dataset using pre-trained models.
3. Explore different data augmentation techniques to enhance model performance.
4. Fine-tune existing models to improve classification accuracy.
5. Compare the performance of different models on this dataset.
6. Use the dataset as a benchmark for evaluating new image classification techniques.

Class Naming Convention:

All files are named in ImageNet style. ```shell Kingdom ├── class_1 │ ├── 1.jpg │ └── 2.jpg ├── class_2 │ ├── 1.jpg │ └── 2.jpg └── class_3 ├── 1.jpg └── 2.jpg

**I have not divided the dataset into train,val,test so that you can decide on the split ratios.**

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Photo by <a href="https://unsplash.com/@zelebb?utm_content=creditCopyText&utm_medium=referral&utm_source=unsplash">Andrey Matveev</a> on <a href="https://unsplash.com/photos/a-close-up-of-two-computer-fans-on-a-yellow-background-8hkotoCEI5o?utm_content=creditCopyText&utm_medium=referral&utm_source=unsplash">Unsplash</a>

The eastern population of the North Pacific right whale (Eubalaena japonica) is the most endangered stock of whales in the world, with recent abundance estimates indicating a population size of approximately 30 animals. Photo-identification of the naturally occurring callosity patterns on the chin, rostrum, lips and post blowhole, and the lip and fluke trailing edge crenulations together represent a nonintrusive technique for obtaining information on their life history parameters, distribution and movements, stock structure, health assessment, and population size. As part of a study funded by the Minerals Management Service and North Pacific Research Board, a North Pacific right whale photo-identification catalog has been established using sighting data recorded since the late 1970s by various dedicated surveys and opportunistic sighting platforms. Date, time, position, photographer, picture quality and notes are documented for each of the approximately 1,780 photographs in the catalog. Within the catalog, there are 18 individual animals with both a high-quality left and right side oblique photograph or a high-quality aerial photograph of the head and dorsal surface; this should be considered the conservative minimum number of individuals catalogued. There are nine other animals with a high quality left or right oblique photograph, but not both. There are eight additional animals with the full suite of required photographs, but the images are of poor quality and cannot be reliably matched. Seven individuals were seen between years (over a period of 11 years), and one of those whales was seen in five separate years within that same period. Data from this catalog have been used to calculate the first abundance estimates for the population. Additionally, the first known match between high and low latitudes (the Bering Sea and Hawaii) was discovered in the catalog. Tracking the within- and between-year sighting histories of photo-identified individuals over decades broadens our knowledge of how these animals use their habitat, and can significantly assist the conservation and management of the species.

Summary of all photo identification records from key habitats by demographics.

ID Images is a leading stock photo and image licensing company that specializes in providing high-quality visuals for commercial use. Founded with the goal of making image licensing easier and more accessible, ID Images has built a vast collection of images across a wide range of categories, from people and animals to landscapes and still life.

With a focus on providing a seamless and efficient experience for clients, ID Images prides itself on its easy-to-navigate website and user-friendly licensing process. Whether you're looking for a unique perspective or a specific type of image, ID Images' vast library of images is sure to fit your needs.