Unlock Realistic Human Images: Transform Cartoon Photos with AI Power
Workflow Overview
The primary purpose of this workflow is to convert cartoon images into realistic human-style images while refining the details of hands and faces. By using ControlNet, LoRA models, and FLUX technology, the workflow can transform cartoon images into realistic human images and ensure that the details of hands and faces are optimized. The workflow also supports high-definition upscaling to further enhance image clarity and detail.
Core Models
The workflow uses the following core models:
ControlNet: Used to control the structure and content of generated images, supporting various preprocessors such as Depth and OpenPose.
LoRA Models:
F.1小红书极致真实清纯网红_1.0and极氪白白酱F.1-人像V8MAX_V8MAX, used to fine-tune the style and details of generated images.FLUX Model:
flux1-redux-dev, used for style transfer and image generation.VAE Model:
ae.sft, used for image encoding and decoding.
Component Explanation
Key components (Nodes) in the workflow include:
LoadImage: Loads the input cartoon image.
ControlNetLoader: Loads ControlNet models, supporting various preprocessors.
StyleModelLoader: Loads the FLUX style model for style transfer.
LoraLoaderModelOnly: Loads LoRA models to fine-tune the style of generated images.
CLIPTextEncode: Encodes prompts into conditioning vectors that the model can understand.
KSampler: A sampler used in the image generation process, controlling the steps and details of image generation.
VAEDecode: Decodes latent space images into visible images.
PreviewImage: Previews the generated images.
UltimateSDUpscale: A high-definition upscaling component that enhances image clarity and detail.
Installation:
Components like ControlNet, LoRA, and FLUX need to be installed via ComfyUI Manager or GitHub. For example:
ControlNet plugin:
ComfyUI_ControlNetLoRA plugin:
ComfyUI_Comfyroll_CustomNodesFLUX plugin:
ComfyUI_IPAdapter_plus
Dependent Models:
ControlNet models (e.g.,
FLUX.1-dev-ControlNet-Union-Pro-InstantX.safetensors) need to be downloaded from Hugging Face or other model repositories.LoRA models (e.g.,
F.1小红书极致真实清纯网红_1.0) also need to be downloaded from the respective repositories.
Workflow Structure
The workflow can be divided into the following main parts:
Image Loading Group:
LoadImage: Loads the input cartoon image.
Input: Image file path (e.g.,
267ffa96a39eeb73153bd3f6af7956af5dce314c1387f854a8210a5cedfc78da.png).Output: Loaded image data for use by subsequent nodes.
ControlNet Control Group:
Multiple ControlNetLoader and ControlNetApplyAdvanced nodes, loading and applying different ControlNet models (e.g., Depth, OpenPose).
Input: Image data passed from the LoadImage node.
Output: Conditioned images processed by ControlNet.
Style Transfer Group:
StyleModelLoader and StyleModelApply nodes, loading and applying the FLUX style model for style transfer.
Input: Reference images and generation models.
Output: Generated images with the style of the reference image.
Image Generation Group:
KSampler and VAEDecode nodes, generating and decoding images.
Input: Conditioned images processed by ControlNet and FLUX.
Output: Final generated images.
High-Definition Upscaling Group:
UltimateSDUpscale node, performing high-definition upscaling on the generated images.
Input: Generated image data.
Output: High-definition upscaled images.
Input and Output
Input:
Cartoon image file path (e.g.,
267ffa96a39eeb73153bd3f6af7956af5dce314c1387f854a8210a5cedfc78da.png).Prompts (e.g.,
Realism, photos, real people，Skin texture, super clear).
Output:
Generated realistic human-style images, saved in PNG or JPG format.
Notes
Model Download: Ensure all used models (e.g., ControlNet, LoRA, FLUX) are correctly downloaded and placed in the ComfyUI model directory.
Performance Requirements: Generating high-resolution images may require significant GPU memory. A GPU with at least 8GB of VRAM is recommended.
Prompt Optimization: The quality of prompts directly affects the generated images. Detailed descriptions are recommended.
Compatibility: Ensure the ComfyUI version is compatible with the components in the workflow.