utils.py

#filename:utils.py



import cv2
import mediapipe as mp
import numpy as np

def get_face_landmarks(image, face_mesh, draw=False, static_image_mode=True):

    # Read input image
    image_input_rgb = cv2.cvtColor (image, cv2.COLOR_BGR2RGB)

    image_rows, image_cols, _ = image.shape
    results= face_mesh.process(image_input_rgb)

    image_landmarks = []
    
    if results.multi_face_landmarks:
        if draw:
            mp_drawing= mp.solutions.drawing_utils
            mp_drawing_styles= mp.solutions.drawing_styles
            drawing_spec= mp_drawing.DrawingSpec(thickness=1, circle_radius=1)
    
            mp_drawing.draw_landmarks(
                image= image,
                landmark_list= results.multi_face_landmarks[0],
                connections= mp.solutions.face_mesh.FACEMESH_CONTOURS,
                landmark_drawing_spec= drawing_spec,
                connection_drawing_spec= drawing_spec,
            )
    
        ls_single_face= results.multi_face_landmarks[0].landmark
        xs_ =[]
        ys_ =[]
        zs_ =[]
        for idx in ls_single_face:
            xs_.append(idx.x)
            ys_.append(idx.y)
            zs_.append(idx.z)

        # Normalize landmarks using Min-Max scaling for each face
        x_min, x_max = np.min(xs_), np.max(xs_)
        y_min, y_max = np.min(ys_), np.max(ys_)
        z_min, z_max = np.min(zs_), np.max(zs_)

        x_range = x_max - x_min
        y_range = y_max - y_min
        z_range = z_max - z_min

        for j in range(len(xs_)):
            image_landmarks.append((xs_[j] - x_min) / (x_range if x_range > 0 else 1))
            image_landmarks.append((ys_[j] - y_min) / (y_range if y_range > 0 else 1))
            image_landmarks.append((zs_[j] - z_min) / (z_range if z_range > 0 else 1))

    return image_landmarks