ComfyUI Node: ZenID Combine Face

ZenID Combine Face:

The ZenIDCombineFace node is designed to seamlessly blend facial features from two different images, creating a composite face that balances characteristics from both sources. This node is particularly useful for AI artists looking to experiment with facial morphing and transformation, allowing for creative exploration in digital art and design. By leveraging advanced face analysis and embedding techniques, the node ensures that the resulting image maintains a natural and coherent appearance. The primary goal of this node is to provide a flexible and intuitive tool for combining facial features, offering control over the blending process to achieve the desired artistic effect.

ZenID Combine Face Input Parameters:

control_net

This parameter specifies the control network to be used in the face combination process. It plays a crucial role in guiding the transformation and ensuring that the resulting image adheres to the desired structure and style.

model

The model parameter refers to the specific machine learning model employed for face analysis and combination. It determines the underlying algorithms and techniques used to process and blend the facial features.

positive

This parameter represents the positive conditioning input, which influences the characteristics that are emphasized in the resulting image. It allows you to specify traits or features that should be highlighted during the face combination.

negative

The negative parameter is used to define the conditioning input that suppresses certain features in the resulting image. It helps in minimizing unwanted traits or characteristics, ensuring a more refined and targeted output.

image_1

This is the first input image containing the facial features to be combined. The node extracts and analyzes the facial characteristics from this image to contribute to the final composite.

image_2

Similar to image_1, this parameter provides the second input image for the face combination process. The features from this image are blended with those from image_1 to create the composite face.

instantid_file

This parameter specifies the file path to the InstantID model, which is essential for loading and utilizing the face analysis capabilities required for the combination process.

insightface

The insightface parameter indicates the execution provider for the face analysis model, with options such as CPU, CUDA, ROCM, and CoreML. It determines the computational resources used for processing the images.

balance

This floating-point parameter controls the balance between the two input images during the face combination. It ranges from 0.0 to 1.0, with a default value of 0.5, allowing you to adjust the influence of each image on the final result.

weight

The weight parameter affects the intensity of the face combination process. It is a floating-point value ranging from 0.0 to 5.0, with a default of 0.8, providing control over the strength of the blending effect.

start_at

This parameter defines the starting point of the face combination process, expressed as a floating-point value between 0.0 and 1.0. It allows for precise control over the timing of the transformation.

end_at

Similar to start_at, this parameter specifies the endpoint of the face combination process. It is a floating-point value between 0.0 and 1.0, ensuring that the transformation occurs within a defined range.

ZenID Combine Face Output Parameters:

MODEL

The MODEL output represents the machine learning model used in the face combination process. It encapsulates the algorithms and techniques applied to achieve the desired blending of facial features.

positive

This output provides the positive conditioning result, reflecting the traits and characteristics that were emphasized in the final composite image.

negative

The negative output indicates the conditioning result that suppressed certain features in the resulting image, ensuring a more refined and targeted output.

ZenID Combine Face Usage Tips:

• Experiment with the balance parameter to achieve the desired mix of features from the two input images. A value closer to 0.0 will favor image_1, while a value closer to 1.0 will favor image_2.
• Adjust the weight parameter to control the intensity of the face combination. Higher values can result in more pronounced blending effects, while lower values may produce subtler transformations.

ZenID Combine Face Common Errors and Solutions:

Reference Image: No face detected.

• Explanation: This error occurs when the node fails to detect a face in one of the input images.
• Solution: Ensure that the input images contain clear and unobstructed views of faces. Adjust the images or use different ones if necessary.

WARNING: No face detected in the keypoints image!

• Explanation: The node could not detect facial keypoints in the provided keypoints image.
• Solution: Verify that the keypoints image is correctly formatted and contains a visible face. If no keypoints image is provided, ensure that the default image is suitable for keypoint extraction.