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Create blended face model from input image for face-swapping/enhancement tasks, streamlining creation process for AI artists.
The ReActorBuildFaceModel
node is designed to create a blended face model from an input image. This node is particularly useful for AI artists who want to generate a face model that can be used in various face-swapping or face-enhancement tasks. By analyzing the input image, the node identifies and processes facial features to build a detailed face model. This model can then be saved and reused in other operations, providing a consistent and high-quality base for further manipulations. The primary goal of this node is to streamline the process of face model creation, making it accessible and efficient for users without requiring deep technical knowledge.
This parameter takes an image as input, which is used to build the face model. The image should be in a format that can be processed by the node, such as JPEG or PNG. The quality and resolution of the input image can significantly impact the accuracy and detail of the resulting face model. Ensure that the image is clear and well-lit for the best results.
This parameter specifies the detection size for the face analysis. It is a tuple that defines the dimensions (width, height) used during the face detection process. The default value is (640, 640), which provides a good balance between speed and accuracy. Adjusting this value can help in cases where the face is not detected properly; for example, reducing the size to (320, 320) might help in detecting smaller faces in the image.
The output of this node is a face model, which is a detailed representation of the facial features extracted from the input image. This model can be used in subsequent nodes for tasks such as face swapping, face enhancement, or other manipulations. The face model is typically returned as a data structure that can be saved and loaded as needed.
det_size
parameter to (320, 320) to improve detection.ReActorFaceSwap
or ReActorFaceBoost
for enhanced results.det_size
parameter to a smaller value like (320, 320) to improve face detection.face_model
or image
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