image-editing
imged_rl_grpo_no_reasoning_ckpt_11600_sftnocomplex_rlnocomplex100K__kl3e_4__lr3e_6_SNOWimged_rl_grpo_no_reasoning_ckpt_11600_sftnocomplex_rlcomplex__kl3e_4__lr1e_6__100K_SNOWEmu3-Base-SFT-reasoning_super_concise-Apr17_lr1e-5-checkpoint-32000imged_rl_grpo_g_all_omni100kimged_rl_grpo_nips_c_reasoningimged_rl_grpo_nips_gc_reasoningimged_rl_grpo_gc_all_omni100kimged_rl_grpo_gc_all
ramanv-image-editing-syntheticmulti_reference_image_editing
Multi-Reference Instruction-Based Image Editing Dataset
Overview
This dataset contains 20,000 high-resolution image pairs and multi-modal instructions designed for training advanced image-to-image editing models. It combines two complementary example types: 10,000 reference-grounded edits, where structural or stylistic changes are driven by up to three provided visual reference images, and 10,000 occlusion-based inpainting/outpainting edits, where the model must… See the full description on the dataset page: https://huggingface.co/datasets/molbal/multi_reference_image_editing.ramanv-image-editing-pairsidentity_preservation_image_editing
Identity Preservation Augmentation Dataset for Image Editing
Overview
This dataset contains algorithmically generated image pairs designed to
teach diffusion-based image editing models pixel-level identity
preservation — the ability to keep unchanged regions of an image exactly
intact while applying targeted edits.
Every example consists of a reference image, a target image, and a short
natural-language prompt. The transformation between reference and target is… See the full description on the dataset page: https://huggingface.co/datasets/molbal/identity_preservation_image_editing.ramanv-image-editing
ramanv-image-editing
Image editing dataset for training FLUX.1-Kontext / InstructPix2Pix style models.
Size
592,141 total editing pairs
Sources: ultraedit
Schema
Each shard tar contains {uid}_src.jpg, {uid}_edit.jpg, {uid}_mask.png (where available).
Metadata per record: instruction, prompt, edit_type, caption_before/after, license, sha256.
Licenses
MagicBrush, InstructPix2Pix, Pico-Banana, HumanEdit: CC-BY-4.0
UltraEdit, AnyEdit… See the full description on the dataset page: https://huggingface.co/datasets/lingamvamshikrishnareddy/ramanv-image-editing.escher-ss2
Dataset Card for escher-ss2
SomethingSomethingv2 dataset
Dataset Structure
Data Instances
Each instance contains:
source_image: The original image
edited_image: The edited version of the image
edit_instruction: The instruction used to edit the image
source_image_caption: Caption for the source image
target_image_caption: Caption for the edited image
Additional metadata fields
Data Splits
{}