Sattyam/Realifake
收藏Hugging Face2023-08-07 更新2024-03-04 收录
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https://hf-mirror.com/datasets/Sattyam/Realifake
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资源简介:
---
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.
提供机构:
Sattyam
原始信息汇总
数据集概述
数据集名称
Realifake
数据集描述
Realifake是一个独特的数据集,包含100,000张真实图像(REAL)和同等数量的AI生成图像(FAKE)。该数据集旨在探索人类创造力与AI想象力的融合。
数据集用途
- 图像分类
- 图像分割
数据集内容
- REAL类别:包含从公共领域资源库收集的真实图像。
- FAKE类别:使用先进的AI模型生成的图像。
数据集规模
- 数据集大小:100,000张图像
- 数据集类别:REAL和FAKE各50,000张
数据集创建
- 采集理由:展示真实世界图像与AI生成内容的共存,促进AI研究与创意发展。
- 数据来源:REAL图像来源于公共领域资源,FAKE图像通过AI模型生成。
使用注意事项
- 研究人员应关注AI生成图像中可能存在的偏见及其社会影响。
数据集管理者
- 数据集由Sattyam jain及其团队精心策划。



