Face Keypoints Preprocessor

Documentation

• Class name: FaceKeypointsPreprocessor
• Category: InstantID
• Output node: False

The FaceKeypointsPreprocessor node is designed to preprocess images by extracting facial keypoints. This process involves analyzing the input image to detect faces and compute their keypoints, which are essential for various facial analysis tasks.

Input types

Required

• faceanalysis
  • The 'faceanalysis' parameter is a model that has been loaded and prepared for face analysis. It is crucial for detecting faces within the image and extracting their keypoints, which are then used for further processing.
  • Comfy dtype: FACEANALYSIS
  • Python dtype: FaceAnalysis
• image
  • The 'image' parameter represents the input image to be processed. It is analyzed by the face analysis model to detect faces and extract their keypoints, which are essential for the preprocessing task.
  • Comfy dtype: IMAGE
  • Python dtype: torch.Tensor

Output types

• image
  • Comfy dtype: IMAGE
  • The output is an image with facial keypoints extracted. This processed image is essential for tasks that require facial feature analysis, such as facial recognition or emotion detection.
  • Python dtype: torch.Tensor

Usage tips

• Infra type: CPU
• Common nodes: unknown

Source code

class FaceKeypointsPreprocessor:
    @classmethod
    def INPUT_TYPES(s):
        return {
            "required": {
                "faceanalysis": ("FACEANALYSIS", ),
                "image": ("IMAGE", ),
            },
        }
    RETURN_TYPES = ("IMAGE",)
    FUNCTION = "preprocess_image"
    CATEGORY = "InstantID"

    def preprocess_image(self, faceanalysis, image):
        face_kps = extractFeatures(faceanalysis, image, extract_kps=True)

        if face_kps is None:
            face_kps = torch.zeros_like(image)
            print(f"\033[33mWARNING: no face detected, unable to extract the keypoints!\033[0m")
            #raise Exception('Face Keypoints Image: No face detected.')

        return (face_kps,)