import cv2
import dlib
import numpy as np

# 初始化dlib的人脸检测器和关键点预测器
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor("shape_predictor_68_face_landmarks.dat")

def extract_facial_features(image_path):
    # 读取图像
    img = cv2.imread(image_path)
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    
    # 检测人脸
    faces = detector(gray)
    if len(faces) == 0:
        return None
    
    # 获取关键点
    landmarks = predictor(gray, faces[0])
    points = np.array([[p.x, p.y] for p in landmarks.parts()])
    
    # 计算面部比例特征
    features = {}
    
    # 脸宽/脸长比例
    face_width = np.linalg.norm(points[16] - points[0])  # 右颧骨到左颧骨
    face_length = np.linalg.norm(points[8] - points[27]) # 下巴到鼻根
    features['width_length_ratio'] = face_width / face_length
    
    # 计算其他特征...
    
    return features

# 使用示例
features = extract_facial_features("face.jpg")
print(features)