Unlock Seamless Image Expansion with Flux Diffusion and Janus AI
1. Workflow Overview
This workflow specializes in image outpainting using Flux Diffusion and Janus image understanding, enabling seamless extension of images. It supports multi-directional expansion (top/bottom/left/right) while maintaining consistency with the original style.
2. Core Models
Model Name | Description |
|---|---|
| UNet optimized for inpainting/outpainting at high resolution. |
| Multimodal model for image captioning (auto-prompt generation). |
| Custom VAE for improved image decoding. |
| Dynamically guides diffusion for natural and coherent outpainting. |
3. Key Nodes & Installation
JanusModelLoader
Function: Loads Janus-Pro model for image analysis.
Install: Install
Janus-Nodesvia ComfyUI Manager or clone GitHub repo.
ImagePadForOutpaint
Function: Defines expansion area (in pixels) and generates mask.
Install: Built-in node (no installation needed).
FluxGuidance
Function: Adjusts guidance strength (default=30) to prevent artifacts.
Install: Requires
Flux-Diffusionplugin (search in ComfyUI Manager).
DifferentialDiffusion
Function: Combines base and refiner models for detail enhancement.
Dependency: Download
F.1-Fill-fp16and place inmodels/unet.
4. Workflow Structure
Group Name | Description |
|---|---|
Upload Image | Load input image (PNG/JPG). |
Max Resolution | Constrains output size (default: 1024x1024) to avoid VRAM issues. |
Outpaint Area | Set expansion pixels (e.g., left=104, right=104) to generate mask. |
Prompt Generation | Janus auto-generates captions, or manually input English prompts. |
Batch Control | Repeats latent samples (default=3) for stable results. |
Flux Workspace | Core nodes (KSampler, VAE Decode) with default optimized parameters. |
5. Inputs & Outputs
Inputs:
Image file (e.g.,
output (2).png).Pixel values for expansion (e.g.,
left=104).Optional text prompts (auto-generated if empty).
Output:
Upscaled image (PNG) with expanded regions.
6. Notes
VRAM: β₯12GB GPU recommended (e.g., RTX 3060 Ti).
Tips:
Limit expansion to β€300 pixels per step; split large expansions into multiple steps.
Avoid single-direction expansion (e.g., only downward) to balance composition.
Troubleshooting:
Reduce resolution in
ConstrainImageor batch size ifCUDA OOMoccurs.Manually input prompts if Janus fails to generate captions.