ComfyUI Node: FaceRestoreCFWithModel

FaceRestoreCFWithModel:

The FaceRestoreCFWithModel node is designed to enhance and restore facial features in images using advanced AI models. This node is particularly useful for AI artists who want to improve the quality of faces in their artwork, ensuring that facial details are clear and aesthetically pleasing. The node leverages a face restoration model to process and enhance cropped faces from an input image, making it ideal for tasks such as photo retouching, portrait enhancement, and improving the visual quality of AI-generated faces. By focusing on facial features, this node helps achieve a more polished and professional look in your images.

FaceRestoreCFWithModel Input Parameters:

facerestore_model

The facerestore_model parameter specifies the AI model used for face restoration. This model is responsible for enhancing the facial features in the cropped faces. The choice of model can significantly impact the quality and style of the restored faces. Ensure that the model is compatible with the node and is loaded correctly to avoid any processing errors.

image

The image parameter is the input image that contains the faces you want to restore. This image is processed to detect and crop faces, which are then enhanced using the specified face restoration model. The quality and resolution of the input image can affect the final output, so using high-quality images is recommended for the best results.

facedetection

The facedetection parameter refers to the face detection model used to identify and crop faces from the input image. This model is crucial for accurately locating faces, which are then passed to the restoration model for enhancement. Ensure that the face detection model is properly initialized and compatible with the node.

codeformer_fidelity

The codeformer_fidelity parameter controls the fidelity of the face restoration process. It determines the balance between maintaining the original facial features and enhancing them. Higher fidelity values result in more detailed and accurate restorations, while lower values may produce smoother but less detailed results. Adjust this parameter based on your specific needs and the desired level of detail in the restored faces.

FaceRestoreCFWithModel Output Parameters:

restored_img

The restored_img parameter is the output image with the restored faces. This image is generated by pasting the enhanced faces back into the original input image, ensuring that the overall composition remains intact. The restored image retains the original resolution and format, with improved facial features that enhance the visual quality of the artwork.

FaceRestoreCFWithModel Usage Tips:

• Ensure that the input image is of high quality and resolution to achieve the best restoration results.
• Experiment with different codeformer_fidelity values to find the optimal balance between detail and smoothness in the restored faces.
• Use a compatible and well-trained face restoration model to ensure accurate and aesthetically pleasing enhancements.
• Verify that the face detection model is properly initialized to avoid issues with face cropping and restoration.

FaceRestoreCFWithModel Common Errors and Solutions:

Failed inference for CodeFormer: <error_message>

• Explanation: This error occurs when the face restoration model fails to process the cropped face, possibly due to an incompatible model or incorrect parameter settings.
• Solution: Ensure that the face restoration model is correctly loaded and compatible with the node. Check the parameter settings and adjust them as needed.

CUDA out of memory

• Explanation: This error indicates that the GPU does not have enough memory to process the image, which can happen with high-resolution images or large batch sizes.
• Solution: Reduce the resolution of the input image or decrease the batch size. Alternatively, try using a GPU with more memory.

Face detection model initialization failed

• Explanation: This error occurs when the face detection model is not properly initialized, preventing the node from detecting and cropping faces.
• Solution: Verify that the face detection model is correctly specified and initialized. Ensure that all necessary files and dependencies are in place.

Invalid input image format

• Explanation: This error occurs when the input image is not in a supported format, leading to issues during processing.
• Solution: Convert the input image to a supported format (e.g., PNG, JPEG) and ensure that it is correctly loaded into the node.