task_categories:image-classification task_categories:image-segmentation size_categories:100K<n<1M language:en license:gpl AI Artificial intelligence real fake ai generated generative ai region:us
---
license: gpl
task_categories:
- image-classification
- image-segmentation
language:
- en
tags:
- AI
- Artificial intelligence
- real
- fake
- ai generated
- generative ai
pretty_name: realifake
size_categories:
- 100K<n<1M
---
# Dataset Card for Dataset Name

### Dataset Summary

Realifake is a groundbreaking dataset that blurs the boundaries between reality and AI-generated creativity. It comprises 100,000 genuine images (REAL) and an equally impressive collection of AI-generated counterparts (FAKE). This unique dataset aims to explore the convergence of human ingenuity and AI's imaginative potential.

## Dataset Creation

### Curation Rationale

The Realifake dataset was meticulously curated to showcase the coexistence of real-world imagery and AI-generated content. It aims to facilitate research and exploration in AI creativity while fostering collaboration between diverse communities.

### Source Data

#### Initial Data Collection and Normalization

The dataset consists of two main categories: REAL, containing genuine images sourced from various public domain repositories, and FAKE, generated using state-of-the-art AI models.

## Considerations for Using the Data

### Social Impact of Dataset

Realifake presents a valuable opportunity for advancing AI research and promoting creativity. However, researchers should be mindful of potential biases in AI-generated images and the social impact of using such technology.

## Additional Information

### Dataset Curators

The Realifake dataset was curated by Sattyam jain and a team of passionate researchers and enthusiasts.
