HumanEdit：一份高质量的人类奖励数据集，用于基于指令的图像编辑

HumanEdit: A High-Quality Human-Rewarded Dataset for Instruction-based Image Editing

December 5, 2024

作者: Jinbin Bai, Wei Chow, Ling Yang, Xiangtai Li, Juncheng Li, Hanwang Zhang, Shuicheng Yan

cs.AI

摘要

我们介绍了HumanEdit，这是一个高质量、由人类奖励的数据集，专门设计用于指导图像编辑，通过开放式语言指令实现精确和多样化的图像操作。先前的大规模编辑数据集通常包含最少的人类反馈，导致数据集与人类偏好之间存在挑战。HumanEdit通过雇佣人类标注者构建数据对和管理员提供反馈来弥合这一差距。通过精心策划，HumanEdit包括5,751张图像，跨越四个阶段需要超过2,500小时的人力工作，确保在各种图像编辑任务中既准确又可靠。该数据集包括六种不同类型的编辑指令：动作、添加、计数、关系、移除和替换，涵盖了广泛的现实场景。数据集中的所有图像都附带蒙版，并且对于数据的一个子集，我们确保指令足够详细，以支持无蒙版编辑。此外，HumanEdit提供了全面的多样性和高分辨率1024乘1024的内容，来源于各个领域，为指导图像编辑数据集设定了一个新的多功能基准。为了推动未来研究并在图像编辑领域建立评估基准，我们在https://huggingface.co/datasets/BryanW/HumanEdit上发布了HumanEdit。

English

We present HumanEdit, a high-quality, human-rewarded dataset specifically designed for instruction-guided image editing, enabling precise and diverse image manipulations through open-form language instructions. Previous large-scale editing datasets often incorporate minimal human feedback, leading to challenges in aligning datasets with human preferences. HumanEdit bridges this gap by employing human annotators to construct data pairs and administrators to provide feedback. With meticulously curation, HumanEdit comprises 5,751 images and requires more than 2,500 hours of human effort across four stages, ensuring both accuracy and reliability for a wide range of image editing tasks. The dataset includes six distinct types of editing instructions: Action, Add, Counting, Relation, Remove, and Replace, encompassing a broad spectrum of real-world scenarios. All images in the dataset are accompanied by masks, and for a subset of the data, we ensure that the instructions are sufficiently detailed to support mask-free editing. Furthermore, HumanEdit offers comprehensive diversity and high-resolution 1024 times 1024 content sourced from various domains, setting a new versatile benchmark for instructional image editing datasets. With the aim of advancing future research and establishing evaluation benchmarks in the field of image editing, we release HumanEdit at https://huggingface.co/datasets/BryanW/HumanEdit.