--- license: mit task_categories: - image-to-image tags: - computer-vision - image-editing - exemplar-based size_categories: - 1K ## Dataset Structure Each sample contains 4 images representing an exemplar edit pair: - `x_original`: Source image before editing - `x_edited`: Source image after editing (defines the edit operation) - `y_original`: Target image before editing - `y_edited`: Target image after the same edit is applied ## Dataset Description This dataset was carefully curated from InstructP2P samples, with manual visual inspection to ensure high quality. The edit operation demonstrated on (x_original → x_edited) should be applicable to (y_original → y_edited). **Format**: (x, x_edit, y, y_edit) tuples **Size**: ~1,500 samples **Edit Types**: Diverse set of image editing operations ## Usage ```python from datasets import load_dataset dataset = load_dataset("{dataset_name}") sample = dataset[0] # Access images x_orig = sample['x_original'] x_edit = sample['x_edited'] y_orig = sample['y_original'] y_edit = sample['y_edited'] ``` ## Citation If you use this dataset, please cite the associated paper ``` @InProceedings{Srivastava_2025_WACV, author = {Srivastava, Ashutosh and Menta, Tarun Ram and Java, Abhinav and Jadhav, Avadhoot Gorakh and Singh, Silky and Jandial, Surgan and Krishnamurthy, Balaji}, title = {ReEdit: Multimodal Exemplar-Based Image Editing}, booktitle = {Proceedings of the Winter Conference on Applications of Computer Vision (WACV)}, month = {February}, year = {2025}, pages = {929-939} } ```