ComfyUI Node: Face Bounding Box

Face Bounding Box:

The FaceBoundingBox node is designed to detect and extract the bounding boxes of faces within an image. This node leverages face analysis models to identify the coordinates of faces and provides the cropped face images along with their respective bounding box dimensions. The primary benefit of this node is its ability to accurately locate faces in an image, which can be particularly useful for tasks such as face recognition, facial feature analysis, and image editing. By using this node, you can automate the process of face detection and extraction, saving time and ensuring consistency in your workflow.

Face Bounding Box Input Parameters:

analysis_models

This parameter represents the face analysis models used to detect faces in the image. These models are responsible for identifying the coordinates of the faces and extracting the bounding boxes. The accuracy and performance of the face detection depend on the quality and configuration of these models.

image

The image parameter is the input image or a list of images in which faces need to be detected. The images should be in a format that can be processed by the face analysis models, typically in RGB format. The quality and resolution of the input images can impact the accuracy of face detection.

padding

The padding parameter specifies the number of pixels to add around the detected face bounding box. This can be useful to include some context around the face or to ensure that the entire face is captured. The default value is 0, and it can be adjusted based on the desired output.

padding_percent

The padding_percent parameter defines the percentage of the face bounding box dimensions to add as padding. This allows for a proportional increase in the bounding box size, ensuring that the padding scales with the size of the detected face. The default value is 0%, and it can be adjusted to include more or less surrounding area.

index

The index parameter allows you to specify which detected face to return when multiple faces are detected in an image. By default, it is set to -1, which means all detected faces will be returned. If set to a specific index, only the face at that index will be returned. This can be useful when you are interested in a particular face in the image.

Face Bounding Box Output Parameters:

out_img

The out_img parameter is a list of cropped face images extracted from the input image. Each image corresponds to a detected face and includes any specified padding. These images can be used for further analysis or processing.

out_x

The out_x parameter is a list of the x-coordinates of the top-left corner of each detected face bounding box. These coordinates indicate the horizontal position of the faces within the input image.

out_y

The out_y parameter is a list of the y-coordinates of the top-left corner of each detected face bounding box. These coordinates indicate the vertical position of the faces within the input image.

out_w

The out_w parameter is a list of the widths of each detected face bounding box. These values represent the horizontal dimensions of the bounding boxes.

out_h

The out_h parameter is a list of the heights of each detected face bounding box. These values represent the vertical dimensions of the bounding boxes.

Face Bounding Box Usage Tips:

• Ensure that the input images are of good quality and resolution to improve the accuracy of face detection.
• Adjust the padding and padding_percent parameters to include more context around the detected faces if needed.
• Use the index parameter to focus on a specific face when multiple faces are detected in an image.
• Combine this node with other face analysis nodes for comprehensive facial feature extraction and analysis.

Face Bounding Box Common Errors and Solutions:

No face detected in image.

• Explanation: This error occurs when the face analysis models fail to detect any faces in the input image.
• Solution: Ensure that the input image contains clear and visible faces. You may also need to adjust the quality and resolution of the image or use different face analysis models.

Index out of range.

• Explanation: This error occurs when the specified index parameter is greater than the number of detected faces.
• Solution: Verify the number of detected faces and ensure that the index parameter is within the valid range. If you want to select a specific face, make sure the index corresponds to an existing face.