Unleash Realistic Product Placements with AI-Powered Star Migration
1. Workflow Overview

This workflow, named "Star Migration", intelligently maps products (e.g., clothing, accessories) onto models while preserving poses and backgrounds. It combines:
Stable Diffusion: Realistic generation (
majicMIX realistic_v7
).Florence-2: Visual understanding of product images.
SAM2: Precise segmentation of products/models.
ControlNet & FluxGuidance: Controls structural details.
Key Features:
Auto-align products to models (wearing/holding).
Background removal via BiRefNetUltra/SAM2.
Optional upscaling (UltimateSDUpscale).
2. Key Components
Nodes:
Input & Preprocessing:
LoadImage
: Load product/model images.ImageResize+
: Standardize resolution (e.g., 1600x1600).
Visual Understanding:
Florence2Run
: Analyzes product images.Sam2Segmentation
: Segments product regions.
Generation & Inpainting:
KSampler
: UsesEuler
(Steps=20, CFG=8).InpaintStitch
: Blends products onto models.
Output:
UltimateSDUpscale
: 2x upscaling (optional).SaveImage
: Saves final results.
Dependencies:
Download
Florence-2-large
andSAM2
models manually.Install plugins via ComfyUI Manager:
ComfyUI-Florence2
,ComfyUI-Inpaint-CropAndStitch
.
3. Workflow Structure
Groups:
Product-to-Model Mapping:
Input: Product image, model photo, prompts (e.g., "best,4K").
Segmentation:
Uses SAM2/BiRefNetUltra for masking.
Upscaling (Optional):
Enabled via
UltimateSDUpscale
.
4. Inputs & Outputs
Inputs:
Required:
Product image (transparent background or masked).
Model photo (with/without background).
Optional: Seed, resolution, sampler settings.
Output:
Final image (PNG) with product naturally fitted.
5. Notes
Issues:
GPU OOM: Reduce resolution or disable upscaling.
Model errors: Verify Florence-2/SAM2 paths.
Optimization:
Use FP16 for Florence-2/SAM2 if GPU supports.
Increase
KSampler
steps (30+) for complex products.