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metadata
license: apache-2.0
task_categories:
  - text-to-image
language:
  - en
pretty_name: ImageReward Dataset
size_categories:
  - 1K<n<10K

ImageRewardDB

Dataset Description

Dataset Summary

ImageRewardDB is a comprehensive text-to-image comparison dataset, focusing on text-to-image human preference. It consists of 137k pairs of expert comparisons, based on text prompts and corresponding model outputs from DiffusionDB. To build the ImageRewadDB, we design a pipeline tailored for it, establishing criteria for quantitative assessment and annotator training, optimizing labeling experience, and ensuring quality validation. And ImageRewardDB is now public available at 🤗 Hugging Face Dataset.

Languages

The text in the dataset is all in English.

Four Subsets

Considering that the ImageRewardDB contains a large number of images, we provide four subsets in different scales to support different needs.

Subset Num of Images Num of Prompts Size Image Directory
ImageRewardDB 1K TBD 1K TBD images/
ImageRewardDB 2K TBD 2K TBD images/
ImageRewardDB 4K TBD 4K TBD images/
ImageRewardDB 8K TBD 8K TBD images/

Dataset Structure

Data Instances

[More Information Needed]

Data Fields

[More Information Needed]

Data Splits

[More Information Needed]

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

[More Information Needed]

Annotations

Annotation process

[More Information Needed]

Who are the annotators?

[More Information Needed]

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

Dataset Curators

[More Information Needed]

Licensing Information

[More Information Needed]

Citation Information

[More Information Needed]

Contributions

[More Information Needed]