RunningHub workflow page: https://www.runninghub.ai/zh-cn/post/2079971231356506114?inviteCode=rh-v1111
Krea 2 Identity Edit v1.2 - Two-Image Reference Editor
Purpose: the two-image variant of the Krea 2 Identity Edit v1.2 graph. Image A is the scene, image B is the reference (a person, an outfit, a product), and the instruction tells the model how to bring B into A while preserving the identity and the rest of the scene.
Graph (as saved)
22 nodes / 31 links.
- UNETLoader:
krea2_turbo_fp8_scaled.safetensors; LoRA:krea2_identity_edit_v1_2_fp16.safetensorsat strength 1. - CLIPLoader:
qwen3vl_4b_fp8_scaled.safetensors, typekrea2; VAE:qwen_image_HDR_vae_fp32_comfy.safetensors. - KSampler: 10 steps, CFG 1,
euler,simple, denoise 1. - Krea2EditModelPatch: ref_boost 3, two-image mode, fit.
- Two LoadImage inputs are active (image A = jpg, image B = webp in the saved example); the example instruction transfers a complete sporty outfit from image B onto the woman in image A, and names facial identity, hairstyle and the original scene as things to preserve.
- Two PreviewImage nodes plus SaveImage prefix
ComfyUI/Kera2Edit.
How to use
Put the scene in image A and the reference in image B, then write the transfer in plain English. For people-in-scene edits, name the subject ("the woman in Image A") and list what must stay unchanged. Two-person inputs are better kept at or below about 1.5 MP per the workflow notes; single-subject edits can go higher.
Limits and not-verified items
No inference was run for this listing: no speed, VRAM, identity-transfer quality or compositing claim is made. The saved images, prompts and previews are the author's demo content, not evidence of an output. Two-image behaviour depends on the exact Krea2EditModelPatch implementation; verify it on your own material. Weights, LoRA and input media are not bundled; check their licenses separately. The cover image is a promotional still, not a frame produced by this graph.
Tutorial: YouTube · Bilibili. Workflows are supplied through AI-KSK; verify workflow, node, model, LoRA, source-image and cover rights separately. No blanket commercial or redistribution license is asserted.
Description
RunningHub workflow page: https://www.runninghub.ai/zh-cn/post/2079971231356506114?inviteCode=rh-v1111
Krea 2 Identity Edit v1.2 - Two-Image Reference EditorPurpose: the two-image variant of the Krea 2 Identity Edit v1.2 graph. Image A is the scene, image B is the reference (a person, an outfit, a product), and the instruction tells the model how to bring B into A while preserving the identity and the rest of the scene.
Graph (as saved)22 nodes / 31 links.
- UNETLoader:
krea2_turbo_fp8_scaled.safetensors; LoRA:krea2_identity_edit_v1_2_fp16.safetensorsat strength 1. - CLIPLoader:
qwen3vl_4b_fp8_scaled.safetensors, typekrea2; VAE:qwen_image_HDR_vae_fp32_comfy.safetensors. - KSampler: 10 steps, CFG 1,
euler,simple, denoise 1. - Krea2EditModelPatch: ref_boost 3, two-image mode, fit.
- Two LoadImage inputs are active (image A = jpg, image B = webp in the saved example); the example instruction transfers a complete sporty outfit from image B onto the woman in image A, and names facial identity, hairstyle and the original scene as things to preserve.
- Two PreviewImage nodes plus SaveImage prefix
ComfyUI/Kera2Edit.
Put the scene in image A and the reference in image B, then write the transfer in plain English. For people-in-scene edits, name the subject ("the woman in Image A") and list what must stay unchanged. Two-person inputs are better kept at or below about 1.5 MP per the workflow notes; single-subject edits can go higher.
Limits and not-verified itemsNo inference was run for this listing: no speed, VRAM, identity-transfer quality or compositing claim is made. The saved images, prompts and previews are the author's demo content, not evidence of an output. Two-image behaviour depends on the exact Krea2EditModelPatch implementation; verify it on your own material. Weights, LoRA and input media are not bundled; check their licenses separately. The cover image is a promotional still, not a frame produced by this graph.
Tutorial: YouTube · Bilibili. Workflows are supplied through AI-KSK; verify workflow, node, model, LoRA, source-image and cover rights separately. No blanket commercial or redistribution license is asserted.