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license: apache-2.0
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license: apache-2.0
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---
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# Img2Img-Controlnet-ComfyUI
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This repository contains the Img2Img project using Controlnet on ComfyUI.
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## Workflow
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1. **Input Image**: The process starts by passing the input image to the LineArt and OpenPose preprocessors.
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2. **ControlNet**: The preprocessed images are fed into ControlNet.
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3. **Efficient Loader**: ControlNet outputs are then passed to the Efficient Loader, which loads the weights.
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4. **KSampler**: Finally, the loaded data is processed through KSampler to generate the output image.
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## Load the model in ComfyUI - [Workflow-Model](https://huggingface.co/Paresh1879/Img2Img-Controlnet-ComfyUI/blob/main/comfyui_workflow.json)
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## Installation
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1. **Clone the Repository**:
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```bash
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git clone https://github.com/comfyanonymous/ComfyUI
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cd ComfyUI
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```
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2. **Install Dependencies**:
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3. **Install Nodes and Models**:
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Copy the custom nodes and models listed to the respective directories in your ComfyUI installation.
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## Custom Nodes
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### Comfyroll Studio
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- CR Aspect Ratio
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- CR Multi-ControlNet Stack
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### ComfyUI
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- PreviewImage
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- SaveImage
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- LoadImage
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### ComfyUI Nodes for Inference.Core
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- CannyEdgePreprocessor
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- OpenposePreprocessor
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- LineArtPreprocessor
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### Efficiency Nodes for ComfyUI Version 2.0+
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- Efficient Loader
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- XY Input: CFG Scale
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- XY Plot
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- KSampler (Efficient)
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## Models - Checkpoint and VAE
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- Checkpoint: [Realistic Vision V6.0](https://huggingface.co/SG161222/Realistic_Vision_V6.0_B1_noVAE/blob/main/Realistic_Vision_V6.0_NV_B1_fp16.safetensors)
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- VAE: [SD VAE](https://huggingface.co/stabilityai/sd-vae-ft-mse-original/blob/main/vae-ft-mse-840000-ema-pruned.ckpt)
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## Docker
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A Docker file is included for easy setup and deployment.
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---
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