Apple Releases Pico-Banana-400K: Large-Scale Dataset for Text-Guided Image Editing Research
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Summary
Apple has released Pico-Banana-400K, a large-scale dataset of approximately 400,000 text-image-edit triplets designed for advancing research in text-guided image editing. The dataset spans 35 edit operations across 8 semantic categories, covering diverse transformations from low-level color adjustments to high-level object, scene, and stylistic edits. It includes ~257K single-turn text-image-edit triplets for supervised fine-tuning and ~56K single-turn text-image(positive)-image(negative)-edit examples for preference learning. The dataset is hosted on GitHub as an open-source contribution to the research community.
Key quotes
· 3 pulledPico-Banana-400K is a large-scale dataset of ~400K text–image–edit triplets designed to advance research in text-guided image editing.
The dataset spans 35 edit operations across 8 semantic categories, covering diverse transformations—from low-level color adjustments to high-level object, scene, and stylistic edits.
~257K single-turn text–image–edit triplets for SFT, ~56K single-turn text-image(positive) - image(negative)-edit for preference
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