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ComfyDeploy: How ComfyUI-FaceChain works in ComfyUI?

What is ComfyUI-FaceChain?

The official ComfyUI version of facechain greatly improves the speed of reasoning and has great custom process controls.

How to install it in ComfyDeploy?

Head over to the machine page

  1. Click on the "Create a new machine" button
  2. Select the Edit build steps
  3. Add a new step -> Custom Node
  4. Search for ComfyUI-FaceChain and select it
  5. Close the build step dialig and then click on the "Save" button to rebuild the machine

ComfyUI-FaceChain

This project is adapted from facechain and involves the breakdown and improvement of the processes of facechain.

workflow_inpaiting_inference.png

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Contact

If you have any questions or suggestions, you can reach us through the following channels:

Steps

  1. Install ComfyUI first.

  2. After a successful installation of ComfyUI, navigate to the custom_nodes directory at ComfyUI/custom_nodes/.

cd custom_nodes
  1. Clone this project into the custom_nodes directory.
git clone https://github.com/THtianhao/ComfyUI-FaceChain
  1. Restart ComfyUI.

ComfyUI Workflow

Facechain Workflow Location: workflow_inpaiting_inference.png Drag the workflow directly into ComfyUI.

Node Introduction

FC StyleLoraLoad

The workflow can load the checkpoints and style Lora used by facechain, download them first, and then merge them, providing relevant prompts. Workflow: ./workflow/workflow_inference.json

FC FaceDetectCrop

Detects faces and crops them.

workflow_face_detect_crop.png Parameter Description:

  1. mode: Cropping mode, normal mode crops according to the face, square 512 width height will scale the face to 512.
  2. face_index: Index of the face, if there are multiple faces, retrieve them based on the index.
  3. crop_ratio: Only effective in normal mode, crops the face proportionally, 1.0 is 1x the face.

FC FaceFusion

Fusion using model scope model.

workflow_face_fusion.png

FC FaceSegment

Segmentation using model scope model to obtain masks for the face and body.

workflow_face_segment.png

Parameter Description:

  1. ksize: Expansion parameter for segmenting the edges of the face.
  2. ksize1: Expansion parameter for segmenting the edges of the face.
  3. include_neck: Whether the segmented image includes the neck.

FC FaceSegAndReplace

Performs face fusion and replaces the original image, similar to facefusion but mainly used for multiple people.

workflow_face_seg_and_replace.png

FC RemoveCannyFace

Removes the Canny-detected parts of the face.

workflow_remove_canny_face.png

FC ReplaceByMask

Replaces the image based on the mask.

workflow_replace_by_mask.png

  • FC MaskOP

    Operations on the mask.

Parameter Description:

  1. mode: Provides three operations, blur, erosion, dilation.
  2. kernel: The kernel used for the operation, the larger the kernel, the stronger the operation.

workflow_mask_op.png

  • FC FCCropToOrigin

    Currently, it can only be used in conjunction with FC FaceDetectCrop in square 512 width height mode. Pastes the cropped image onto the target image based on the mask.

workflow_crop_to_origin.png Parameter Description:

  1. origin_image: Original image.
  2. origin_box: Bounding box of the original image.
  3. origin_mask: Mask cropped from the original image.
  4. paste_image: Pasting image, must be consistent with the origin_mask, hence the need for FC FaceDetectCrop in square 512 width height mode.

Contribution

If you find any issues or have suggestions for improvement, feel free to contribute. Follow these steps:

  1. Branch out a new feature branch: git checkout -b feature/your-feature-name
  2. Make your changes and commit: git commit -m "Add new feature"
  3. Push to your remote branch: git push origin feature/your-feature-name
  4. Create a Pull Request (PR).

License

This project is licensed under the MIT License. See the LICENSE file for details.

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