Flux.2 Klein Spectral Graft node keeps pose & lighting intact during clothes/face swaps
New node uses FFT to edit images without altering background or lighting
The Flux.2 Klein 9b model is powerful for image generation, but using it to change clothes often results in unwanted alterations to pose, face, or lighting. A new node called Flux.2 Klein Spectral Graft, built by Reddit user /u/Stock_Mycologist1104, eliminates this issue. It applies FFT (Fast Fourier Transform) to calculate the frequency content of the input image and targets only the desired areas for editing. This allows clothes swapping, face swapping, and object addition/removal while keeping the subject’s pose, lighting, and background exactly as they were. Tested on the Flux.2 Klein 9b FP8 distilled version, the node accepts both reference images and text prompts for guidance.
The node includes adjustable settings for each use case, and users can save their preferred configurations. The creator provides the full ComfyUI workflow in a GitHub repository. Early examples show dramatic improvements over vanilla calls to Flux.2 Klein: swapped outfits look realistic without shifting facial features or changing the scene’s lighting. For AI artists and developers working with fashion, e-commerce, or content creation, this node drastically reduces the manual retouching needed to keep edited images coherent.
- Preserves subject pose, background, and lighting during clothes/face swaps or object edits.
- Uses FFT frequency analysis to precisely target editing areas instead of globally altering the image.
- Tested on Flux.2 Klein 9b FP8 distilled; settings are adjustable and saveable per session.
Why It Matters
Enables precise, context-aware image editing in AI workflows, saving creators hours of manual correction.