image-preference-demo

# Image dataset for preference aquisition demo
This dataset provides the files used to run the example that we use in this [blog post]() to illustrate how easily
you can set up and run the annotation process to collect a huge preference dataset using Rapidata's API.
The goal is to collect human preferences based on pairwise image matchups.

The dataset contains:
1. [**Generated images**](images.zip): A selection of example images generated using Flux.1 and Stable Diffusion. The images are provided in a .zip to allow downloading them all at once.
2. [**Pair-wise matchups**](matchups.csv): A .csv file describing which images are compared against which, as well as the prompt that was used to generate those images.
3. [**Results**](preference_data_results.json): An example of the resulting prefences after completing the annotation process. Note that since we are collecting real human prefences, one should not expect their results to exactly match these.

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

# 用于偏好采集演示的图像数据集
本数据集为配套[博客文章]()的示例演示提供所需文件，用于阐释借助Rapidata的应用程序编程接口（API）搭建并运行标注流程以采集大规模偏好数据集的便捷性。本项目核心目标为基于成对图像对比收集人类偏好。

数据集包含以下内容：
1. **生成图像（Generated images）**：精选使用Flux.1与Stable Diffusion生成的示例图像。为便于批量下载，所有图像已打包为ZIP压缩包（images.zip）。
2. **成对对比样本（Pair-wise matchups）**：一个CSV格式文件，记录了两两对比的图像组合，以及生成对应图像所使用的提示词（prompt）。
3. **标注结果（Results）**：一个名为preference_data_results.json的JSON格式文件，展示了完成标注流程后得到的偏好数据示例。请注意，由于本数据集采集的是真实人类偏好，实际标注结果与该示例未必完全一致。

若本数据集为您带来了实用价值且希望后续获取更多同类内容，敬请为其点赞。