Updated: May 10, 2026
character
This workflow is designed for Qwen Image Edit 2511 seamless head replacement, focused on controlled, authorized portrait editing with strong identity transfer and natural blending. Its main purpose is to use one image as the body / scene reference and another image as the head / face identity reference, then generate a clean final result where the replacement looks integrated rather than pasted.
The workflow is built around Qwen Image Edit 2511, using qwen_image_edit_2511_fp8mixed / qwen_image_edit_2511 model routing, qwen_2.5_vl_7b_fp8_scaled as the vision-language text encoder, and qwen_image_vae as the VAE. It also includes a dedicated head-swap LoRA route, such as bfs_head_v5_2511_merged_version_rank_16_fp16, to strengthen the model’s ability to perform realistic and stable head replacement. This makes the workflow more specialized than a normal image-editing graph.
The core idea is not to regenerate the whole image. Instead, the workflow uses inpainting and reference control to focus the edit on the head area while preserving the body, clothing, pose, background, lighting, camera angle, and overall composition from the base image. This is important because many face-swap or head-swap attempts fail by changing the entire person, destroying the original body structure, or creating mismatched lighting and skin tone. This workflow is designed to reduce that drift.
The workflow includes InpaintCropImproved and InpaintStitchImproved, which help crop the target region, process the edit, and stitch the result back into the original image. This gives the workflow a more professional local-editing structure. It also uses ReferenceLatent, FluxKontextMultiReferenceLatentMethod, CFGNorm, ModelSamplingAuraFlow, SamplerCustomAdvanced, and VAEDecode to improve reference stability and output quality.
A key part of this workflow is mask and foreground preparation. BiRefNetRMBG is included for background removal and subject isolation, helping the system identify the usable human region more clearly. The workflow also uses ImageResizeKJv2, image concatenation, preview nodes, and comparison output, making it easier to check the body image, head reference, generated result, and before-after differences.
The prompt logic is written specifically for seamless replacement. It asks the model to preserve the body image environment, framing, lighting, camera perspective, exposure, and composition while replacing only the head identity. It also emphasizes matching head size, face-to-body ratio, neck thickness, shoulder alignment, gaze direction, expression, skin texture, jawline blending, shadow contact, and sharpness consistency. These details are critical for making the final result look natural.
This workflow is suitable for authorized portrait replacement, character concept testing, fashion model preview, AI influencer image editing, cosplay-style transformation, commercial mockups, and Civitai / RunningHub showcase examples. If you want to understand how the reference images, inpaint crop, LoRA route, and final stitch-back structure work together, watch the full tutorial from the YouTube link above.
⚙️ Try the Workflow Online
👉 Workflow: https://www.runninghub.ai/post/2027327275267530754?inviteCode=rh-v1111
Open the link above to run the workflow directly online and view the generation results in real time.
If the results meet your expectations, you can also deploy it locally for further customization.
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📺 Bilibili Updates (Mainland China & Asia-Pacific)
If you are in Mainland China or the Asia-Pacific region, you can watch the video below for workflow demos and a detailed creative breakdown.
📺 Bilibili Video: https://www.bilibili.com/video/BV1DpADznEo2/
I will continue updating model resources on Quark Drive:
👉 https://pan.quark.cn/s/20c6f6f8d87b
These resources are mainly prepared for local users, making creation and learning more convenient.
⚙️ 在线体验工作流
👉 工作流： https://www.runninghub.ai/post/2027327275267530754?inviteCode=rh-v1111
打开上方链接即可直接运行该工作流，实时查看生成效果。
如果觉得效果理想，你也可以在本地进行自定义部署。
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📺 Bilibili 更新（中国大陆及南亚太地区）
如果你在中国大陆或南亚太地区，可以通过下方视频查看该工作流的实测效果与构思讲解。
📺 B站视频： https://www.bilibili.com/video/BV1DpADznEo2/
我会在 夸克网盘 持续更新模型资源：
👉 https://pan.quark.cn/s/20c6f6f8d87b
这些资源主要面向本地用户，方便进行创作与学习。