人脸融合大促

import cv2
import dlib
from skimage import transform as tf

# 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")

# 读取两张人脸图像
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)

# 进行人脸融合
def warp_image(image, landmarks, reference_landmarks):
    tform = tf.SimilarityTransform()
    tform.estimate(landmarks, reference_landmarks)
    return tf.warp(image, tform.inverse, output_shape=(img1.shape[0], img1.shape[1]))

warped_img2 = warp_image(img2, landmarks2, landmarks1)

# 合并图像
output = img1.copy()
output[warped_img2 != 0] = warped_img2[warped_img2 != 0]

cv2.imshow('Face Fusion', output)
cv2.waitKey(0)
cv2.destroyAllWindows()