/ComfyUI_wav2lip

placeholder

Primary LanguagePython

ComfyUI_wav2lip

Wav2Lip Node for ComfyUI

The Wav2Lip node is a custom node for ComfyUI that allows you to perform lip-syncing on videos using the Wav2Lip model. It takes an input video and an audio file and generates a lip-synced output video.

wav2lip

Features

  • Lip-syncing of videos using the Wav2Lip model
  • Face detection and enhancement using GFPGAN or CodeFormer
  • Adjustable fidelity for face enhancement
  • Support for various face detection models

Inputs

  • images: Input video frames (required)
  • audio: Input audio file (required)
  • mode: Processing mode, either "sequential" or "repetitive" (default: "sequential")
  • face_detect_batch: Batch size for face detection (default: 8)
  • facedetection: Face detection model, options: "retinaface_resnet50", "retinaface_mobile0.25", "YOLOv5l", "YOLOv5n" (default: "retinaface_resnet50")
  • face_restore: Enable or disable face enhancement, options: "enable", "disable" (default: "disable")
  • codeformer_fidelity: Fidelity for face enhancement, range: 0.0 to 1.0 (default: 0.5)
  • facerestore_model: Face restoration model, options: "CodeFormer.pth", "GFPGAN.pth" (default: "CodeFormer.pth")

Outputs

  • images: Lip-synced output video frames
  • audio: Output audio file

Installation

  1. Clone the repository to custom_nodes folder:

    git clone https://github.com/yourusername/wav2lip-comfyui.git

  2. Install the required dependencies:

    pip install -r requirements.txt

Model Setup

To use the Wav2Lip node, you need to download the required models separately. Please follow these steps:

facerestore_models:

  1. Download the CodeFormer & GFPGAN models: CodeFormer model | GFPGAN model
  2. Place the .pth model files in the custom_nodes\ComfyUI_wav2lip\models\facerestore_models` folder

facedetection_models:

  1. Download the facedetection models: -1- |-2- |-3- |-4-
  2. Place the .pth model files in the custom_nodes\ComfyUI_wav2lip\models\facedetection` folder

wav2lip model:

  1. Download the wav2lip model: -1-
  2. Place the .pth model file in the custom_nodes\ComfyUI_wav2lip\Wav2Lip\checkpoints` folder
  3. Start or restart ComfyUI.

Usage

  1. Add the Wav2Lip node to your ComfyUI workflow.

  2. Connect the input video frames and audio file to the corresponding inputs of the Wav2Lip node.

  3. Adjust the node settings according to your requirements:

    • Set the mode to "sequential" or "repetitive" based on your video processing needs.
    • Adjust the face_detect_batch size if needed.
    • Select the desired facedetection model.
    • Enable or disable face_restore to apply face enhancement.
    • Adjust the codeformer_fidelity value to control the strength of face enhancement.
    • Select the desired facerestore_model for face restoration.

  4. Execute the ComfyUI workflow to generate the lip-synced output video.

IMPORTANT: Update for basicsr Compatibility

If you encounter an error like "No module named 'torchvision.transforms.functional_tensor" when trying to use the wav2lip node, you'll need to manually update a file in your Python virtual environment (venv) to ensure compatibility with the latest version of torchvision.

To fix this issue, follow these steps:

  1. Download the updated "degradations.py" file provided by the maintainer of the wav2lip node. You can find this file in the 'service' folder.

  2. Locate the existing "degradations.py" file in your venv directory. The path should be similar to:

    path/to/your/venv/lib/site-packages/basicsr/data/degradations.py

  3. Create a backup of the existing "degradations.py" file, just in case you need to revert the changes later. You can rename the file to "degradations.py.backup".

  4. Replace the existing "degradations.py" file with the updated file you downloaded in step 1.

  5. Start or restart ComfyUI.

By replacing the "degradations.py" file with the updated version, you should be able to use the wav2lip node without encountering the "ModuleNotFoundError" related to torchvision.

Note: If you have multiple Python environments or versions installed, make sure to replace the "degradations.py" file in the correct venv directory that is being used by your application.

If you continue to face issues after making this change, please ensure that you have a compatible version of torchvision installed in your environment and that there are no other conflicting dependencies.

Acknowledgement

Thanks to ArtemM, Wav2Lip, PIRenderer, GFP-GAN, GPEN, ganimation_replicate, STIT for sharing their code.

Related Work