human-alignment-preferences-images

# Rapidata Image Generation Alignment Dataset

<a href="https://www.rapidata.ai">
<img src="https://cdn-uploads.huggingface.co/production/uploads/66f5624c42b853e73e0738eb/jfxR79bOztqaC6_yNNnGU.jpeg" width="400" alt="Dataset visualization">
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This dataset was collected in ~4 Days using the [Rapidata Python API](https://docs.rapidata.ai), accessible to anyone and ideal for large scale data annotation.

Explore our latest model rankings on our [website](https://www.rapidata.ai/benchmark).

If you get value from this dataset and would like to see more in the future, please consider liking it.

## Overview
One of the largest human annotated alignment datasets for text-to-image models, this release contains over 1,200,000 human preference votes. This alignment dataset builds on the already published [Alignment Dataset](https://huggingface.co/datasets/Rapidata/Flux_SD3_MJ_Dalle_Human_Alignment_Dataset) and shows Rapidata's ability to consistently rank new image generation models at unprecedented speeds.

Participants were shown two images and asked, "Which image matches the description better?"

## Key Features
- **Massive Scale**: 1,200,000+ individual human alignment votes collected in under 100 hours
- **Global Representation**: Collected from participants across the globe
- **Diverse Prompts**: Carefully curated prompts testing various aspects of image generation
- **Leading Models**: Comparisons between state-of-the-art image generation models

<img src="https://cdn-uploads.huggingface.co/production/uploads/66f5624c42b853e73e0738eb/1LVQj_G5bFio7w4WXPxsC.png" alt="Image description" width="650">
**Figure:** Overview of the distribution of annotators by continent (left) compared to the world population distribution (right)

## Applications
This dataset is invaluable for:
- Benchmarking new image generation models
- Developing better evaluation metrics for generative models
- Understanding global preferences in AI-generated imagery
- Training and fine-tuning image generation models
- Researching cross-cultural aesthetic preferences

## Data Collection Powered by Rapidata
What traditionally would take weeks or months of data collection was accomplished in under 100 hours through Rapidata's innovative annotation platform. Our technology enables:
- Lightning-fast data collection at massive scale
- Global reach across 145+ countries
- Built-in quality assurance mechanisms
- Comprehensive demographic representation
- Cost-effective large-scale annotation

## About Rapidata
Rapidata's technology makes collecting human feedback at scale faster and more accessible than ever before. Visit [rapidata.ai](https://www.rapidata.ai/) to learn more about how we're revolutionizing human feedback collection for AI development.

# Rapidata图像生成对齐数据集（Rapidata Image Generation Alignment Dataset）

<a href="https://www.rapidata.ai">
<img src="https://cdn-uploads.huggingface.co/production/uploads/66f5624c42b853e73e0738eb/jfxR79bOztqaC6_yNNnGU.jpeg" width="400" alt="数据集可视化效果">
</a>

本数据集通过 [Rapidata Python 应用程序编程接口（Rapidata Python API）](https://docs.rapidata.ai) 耗时约4天采集完成，面向所有用户开放，是大规模数据标注的理想选择。

欢迎访问我们的 [官网](https://www.rapidata.ai/benchmark) 查看最新模型排名。

若您从本数据集获益并希望未来获得更多同类资源，不妨为其点赞。

## 概览
本数据集是目前规模最大的面向文本到图像模型的人工标注对齐数据集之一，本次发布包含超过120万条人工偏好投票结果。本对齐数据集基于已公开的 [Alignment Dataset](https://huggingface.co/datasets/Rapidata/Flux_SD3_MJ_Dalle_Human_Alignment_Dataset) 构建，展现了Rapidata以空前速度持续对新型图像生成模型进行排序的能力。

参与标注的用户会看到两张图像，并被要求回答：「哪张图像更贴合给定描述？」

## 核心特性
- **海量规模**：在100小时内采集超过120万条独立人工对齐投票
- **全球覆盖**：标注参与者来自全球各地
- **多样化提示词**：精心筛选的提示词覆盖图像生成的各类评测维度
- **顶尖模型对比**：涵盖当前最先进的图像生成模型之间的对比

<img src="https://cdn-uploads.huggingface.co/production/uploads/66f5624c42b853e73e0738eb/1LVQj_G5bFio7w4WXPxsC.png" alt="图像说明" width="650">
**图：** 按大洲划分的标注者分布情况（左图）与全球人口分布情况（右图）对比

## 应用场景
本数据集可广泛用于：
- 新型图像生成模型的基准测试
- 研发更优秀的生成模型评估指标
- 探究人工智能生成图像的全球偏好特征
- 图像生成模型的训练与微调
- 跨文化审美偏好相关研究

## 基于Rapidata的数据采集
传统上需要数周乃至数月的数据采集工作，通过Rapidata创新的标注平台仅用不到100小时即可完成。我们的技术支持：
- 超大规模数据的极速采集
- 覆盖145个以上国家的全球触达能力
- 内置的质量保障机制
- 全面的人口统计学代表性
- 极具成本效益的大规模标注服务

## 关于Rapidata
Rapidata的技术让大规模人工反馈采集变得比以往更快、更易用。访问 [rapidata.ai](https://www.rapidata.ai/) 了解更多关于我们如何革新AI开发领域人工反馈采集的信息。