单脸融合怎么创建

import cv2
import dlib
import numpy as np

# 加载人脸检测器和特征点预测器
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor("shape_predictor_68_face_landmarks.dat")

# 读取两张图片
img1 = cv2.imread('face1.jpg')
img2 = cv2.imread('face2.jpg')

# 检测人脸并提取特征点
def get_landmarks(image):
    faces = detector(image)
    if len(faces) > 0:
        return np.matrix([[p.x, p.y] for p in predictor(image, faces[0]).parts()])
    return None

landmarks1 = get_landmarks(img1)
landmarks2 = get_landmarks(img2)

# 简单的特征点融合（示例）
def blend_landmarks(landmarks1, landmarks2):
    blended = (landmarks1 + landmarks2) // 2
    return np.array(blended)

blended_landmarks = blend_landmarks(landmarks1, landmarks2)

# 将融合后的特征点应用到图像中（简化处理）
# 这里仅展示概念，实际应用需要更复杂的图像处理技术
for (x, y) in blended_landmarks:
    cv2.circle(img1, (int(x), int(y)), 2, (0, 255, 0), -1)

cv2.imshow('Blended Face', img1)
cv2.waitKey(0)
cv2.destroyAllWindows()