Pico-Banana-400K: A Large-Scale Dataset for Text-Guided Image Editing

TL;DR

Pico-Banana-400K is a large, high-quality dataset of 400,000 real images with diverse, instruction-based edits, designed to advance research in text-guided image editing by enabling complex, multi-turn, and preference-based tasks.

Contribution

The paper introduces Pico-Banana-400K, the first large-scale, systematically curated dataset for instruction-based image editing with real images, supporting complex editing scenarios and diverse task types.

Findings

Enables training of advanced text-guided image editing models

Supports research on multi-turn and preference-based editing

Provides high-quality, diverse, real-image edit pairs

Abstract

Recent advances in multimodal models have demonstrated remarkable text-guided image editing capabilities, with systems like GPT-4o and Nano-Banana setting new benchmarks. However, the research community's progress remains constrained by the absence of large-scale, high-quality, and openly accessible datasets built from real images. We introduce Pico-Banana-400K, a comprehensive 400K-image dataset for instruction-based image editing. Our dataset is constructed by leveraging Nano-Banana to generate diverse edit pairs from real photographs in the OpenImages collection. What distinguishes Pico-Banana-400K from previous synthetic datasets is our systematic approach to quality and diversity. We employ a fine-grained image editing taxonomy to ensure comprehensive coverage of edit types while maintaining precise content preservation and instruction faithfulness through MLLM-based quality scoring and careful curation. Beyond single turn editing, Pico-Banana-400K enables research into complex editing scenarios. The dataset includes three specialized subsets: (1) a 72K-example multi-turn collection for studying sequential editing, reasoning, and planning across consecutive modifications; (2) a 56K-example preference subset for alignment research and reward model training; and (3) paired long-short editing instructions for developing instruction rewriting and summarization capabilities. By providing this large-scale, high-quality, and task-rich resource, Pico-Banana-400K establishes a robust foundation for training and benchmarking the next generation of text-guided image editing models.