ComfyUI.org

Elevate Your Art: ControlNet Pose Control and IPAdapter Style Transfer for High-Resolution Images

CN
ComfyUI.org
2025-06-09 08:43:36

1. Workflow Overview

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This workflow combines ControlNet pose control and IPAdapter style transfer to generate high-quality, stylized images, ideal for:

  • Pose Control: Uses ControlNet (scribble mode) to precisely control composition.

  • Style Transfer: Applies reference image styles (e.g., colors, textures) via IPAdapter.

  • High-Resolution Output: Default 1024x1024 images with batch support.

2. Core Models

Model/Component

Function

Source

DreamShaper XL v2.1 Turbo

Base SDXL model (realistic style).

Download to models/checkpoints.

xinsir_controlnet-scribble-sdxl-1.0

ControlNet scribble model for pose.

Download to models/controlnet.

IPAdapter VIT-G

Style transfer model (medium strength).

Install via ComfyUI Manager.

3. Key Nodes

Node Name

Function

Installation

ControlNetApplySD3

Applies ControlNet constraints.

Install ControlNet Preprocessors.

IPAdapterUnifiedLoader

Loads IPAdapter models.

Install IPAdapter Plus plugin.

UltimateSDUpscale

Tile-based upscaling.

Install Ultimate SD Upscale.

4. Workflow Structure

  1. Model & Input Loading

    • Loads base model, ControlNet scribble model, and IPAdapter.

    • Inputs: Reference image (style), white-background scribble image (pose), prompts.

  2. Conditioning

    • CLIPTextEncode: Encodes positive/negative prompts.

    • IPAdapter: Injects reference image style.

  3. Image Generation

    • KSampler: Generates images with ControlNet + IPAdapter.

    • EmptyLatentImage: Sets initial resolution (1024x1024).

  4. Post-Processing

    • VAEDecode: Decodes latent to image.

    • SaveImage: Saves output to ComfyUI/output.

5. Input & Output

  • Input Parameters:

    • Reference Image: For style transfer (e.g., AI00.jpg).

    • Scribble Image: White-background sketch (e.g., AI09.jpg) for pose control.

    • Prompts: Positive (e.g., "A black camper with puppies, realistic") + negative defaults.

  • Output: One or more 1024x1024 PNG images.

6. Notes

  • Hardware: Minimum 12GB VRAM (IPAdapter + ControlNet are resource-intensive).

  • Tuning Tips:

    • IPAdapter weight ≤0.9 to avoid overstyle.

    • ControlNet strength (default 0.85) affects pose rigidity.

  • Troubleshooting:

    • Missing models: Verify paths for xinsir_controlnet-scribble-sdxl-1.0 and IPAdapter.

    • VRAM errors: Reduce batch size or resolution in KSampler.

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