ComfyUI Node: Deepface Analyze Face Attributes

Deepface Analyze Face Attributes:

The DeepfaceAnalyzeFaceAttributes node is designed to analyze facial attributes from an image using the DeepFace library. This node can detect and provide detailed information about the gender, race, emotion, and age of the largest face in the image. It is particularly useful for AI artists who want to incorporate facial attribute analysis into their projects, enabling them to create more personalized and context-aware artworks. By leveraging advanced facial recognition and analysis techniques, this node helps you gain insights into the demographic and emotional characteristics of the subjects in your images, enhancing the depth and relevance of your creative outputs.

Deepface Analyze Face Attributes Input Parameters:

image

This parameter represents the input image that will be analyzed. The image should be in a format compatible with the DeepFace library, such as a tensor or numpy array. The node will convert the image to a numpy array if necessary.

detector_backend

This parameter specifies the backend to be used for face detection. Available options include "opencv", "ssd", "dlib", "mtcnn", "retinaface", "mediapipe", "yolov8", "yunet", and "fastmtcnn". The default value is "yolov8". The choice of backend can impact the accuracy and speed of face detection.

analyze_gender

This boolean parameter determines whether the node should analyze the gender of the detected face. The default value is True. If set to False, gender analysis will be skipped.

analyze_race

This boolean parameter determines whether the node should analyze the race of the detected face. The default value is True. If set to False, race analysis will be skipped.

analyze_emotion

This boolean parameter determines whether the node should analyze the emotion of the detected face. The default value is True. If set to False, emotion analysis will be skipped.

analyze_age

This boolean parameter determines whether the node should analyze the age of the detected face. The default value is True. If set to False, age analysis will be skipped.

standard_single_face_image

This boolean parameter indicates whether the input image is a standard single face image. The default value is False. If set to True, the node will assume that the image contains only one face and will not enforce detection.

Deepface Analyze Face Attributes Output Parameters:

gender

This output parameter provides the gender of the detected face. The value will be "M" for male, "F" for female, or an empty string if gender analysis is not performed or the gender cannot be determined.

race

This output parameter provides the race of the detected face. Possible values include "indian", "asian", "latino hispanic", "black", "middle eastern", and "white". If race analysis is not performed or the race cannot be determined, the value will be an empty string.

emotion

This output parameter provides the dominant emotion of the detected face. Possible values include "sad", "angry", "surprise", "fear", "happy", "disgust", and "neutral". If emotion analysis is not performed or the emotion cannot be determined, the value will be an empty string.

age

This output parameter provides the age of the detected face as a string. If age analysis is not performed or the age cannot be determined, the value will be "0".

json_info

This output parameter provides a JSON string containing detailed information about the detected face, including the region, confidence, and other attributes. This can be useful for further analysis or debugging.

Deepface Analyze Face Attributes Usage Tips:

• Ensure that the input image is clear and well-lit to improve the accuracy of face detection and attribute analysis.
• Experiment with different detector backends to find the one that works best for your specific use case. Some backends may offer better performance or accuracy depending on the image quality and content.
• If you are only interested in specific attributes (e.g., only gender and age), set the other analysis parameters (e.g., analyze_race, analyze_emotion) to False to speed up the processing time.
• Use the json_info output to gain deeper insights into the detected face and to troubleshoot any issues with the analysis.

Deepface Analyze Face Attributes Common Errors and Solutions:

Deepface Analyze Face Attributes only support for one image and only analyze the largest face.

• Explanation: This warning occurs when multiple images are provided as input. The node is designed to analyze only one image at a time and will focus on the largest face in the image.
• Solution: Ensure that you provide a single image as input to the node. If you have multiple images, process them one at a time.

Spoof detected in the given image.

• Explanation: This error occurs when the anti-spoofing feature detects a spoofed or fake face in the image.
• Solution: Verify the authenticity of the input image and ensure that it contains a real face. Disable the anti-spoofing feature if it is not required for your use case.

No face detected in the image.

• Explanation: This error occurs when the face detector fails to find any faces in the input image.
• Solution: Check the quality and content of the input image. Ensure that the image is clear, well-lit, and contains a visible face. Try using a different detector backend if the issue persists.