Unlock the Power of E-commerce Model Pose Transfer with This Advanced Workflow
Unlock AI-powered e-commerce model pose transfer with this workflow! Discover how to migrate poses from reference images to target characters while preserving clothing textures and skin details.
- Use Case
- Ecommerce
- Best For
- Ecommerce
- Models
- FluxControlnetLora
- Key Nodes
- Controlnet
- Reading Time
- 4 min
Workflow Overview
Unlock AI-powered e-commerce model pose transfer with this workflow! Discover how to migrate poses from reference images to target characters while preserving clothing textures and skin details.
Content type: Workflow
Primary intent: Download
Required Models
- Flux
- Controlnet
- Lora
Required Nodes
- Controlnet
Setup Notes
- Install the required models before opening the workflow template.
1. Workflow Overview
This workflow specializes in e-commerce model pose transfer, accurately migrating poses from reference images to target characters (e.g., "Ari") while preserving clothing textures and skin details. Key features:
Multi-ControlNet: OpenPose + Depth + Canny for pose/depth/contour control
LoRA Fusion: Blends "ZOEY Real Skin" and "Ari E-commerce" LoRAs
Flux Architecture: Uses FP8-precision FLUX.1-ControlNet for stability
2. Core Models
Model Name | Function | Source |
|---|---|---|
基础算法_F.1 | Base model (FP8 optimized) | Load via |
FLUX.1-ControlNet-Union-Pro | Triple-ControlNet (OpenPose+Depth+Canny) | Download |
ZOEY Skin LoRA | Enhances skin realism (weight=0.4) | Place in |
Ari E-commerce LoRA | Injects fashion photography style (weight=0.4) | Stack with skin LoRA |
3. Key Nodes
Node Name | Function | Installation | Dependencies |
|---|---|---|---|
ControlNetApplySD3 | Next-gen ControlNet (multi-modal) | Update | FLUX-specific models required |
AIO_Preprocessor | Unified preprocessor (Canny/OpenPose) | Install | None |
CLIPTextEncodeFlux | Flux-specific text encoder |
| Dual-CLIP models |
easy positive | Structured positive prompt generator | Built-in | None |
4. Workflow Structure
Group 1: Base Models
UNETLoader + DualCLIPLoader: Load FP8 base model
VAELoader: Uses
ae.sftdecoder
Group 2: LoRA Stacking
LoraLoader×2: Blends skin & style LoRAs (0.4 weight each)
Group 3: Multi-ControlNet
OpenPose: Extracts skeleton from reference image
DepthAnything: Generates depth map
CannyEdge: Constrains outlines
Group 4: Generation
KSampler //Inspire: 30 steps, Euler-beta
SaveImage: Auto-saves with timestamp
5. Inputs & Outputs
Inputs:
Required: Pose reference image (768x1024), clothing prompts
Optional: Seed (random), ControlNet weights (0.6-0.7)
Output:
Images saved to
%date%/image_*Real-time ControlNet previews
6. Critical Notes
Hardware:
≥10GB VRAM (batch processing for 2048x1024)
RTX 30/40 series recommended
Model Specs:
Must use
fp8_e4m3fnprecisionFLUX.1-specific ControlNet required
Debug:
Pose inaccuracy? Check OpenPose preprocessing
Skin artifacts? Adjust ZOEY LoRA (0.3-0.5)
Maintenance:
Regularly update
Impact-Packfor latest processors