用python写一个AI换脸代码

好的，下面是一个简单的用Python实现AI换脸的代码示例，仅供参考：

import cv2
import dlib
import numpy as np
from imutils import face_utils
import argparse


def main():
    # 解析命令行参数
    ap = argparse.ArgumentParser()
    ap.add_argument("-i", "--image", required=True, help="path to input image")
    ap.add_argument("-m", "--model", default="./shape_predictor_68_face_landmarks.dat", help="path to facial landmark predictor")
    args = vars(ap.parse_args())

    # 加载图像并进行灰度化
    image = cv2.imread(args["image"])
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

    # 加载人脸检测器和关键点检测器
    detector = dlib.get_frontal_face_detector()
    predictor = dlib.shape_predictor(args["model"])

    # 检测人脸并提取关键点
    rects = detector(gray, 1)
    for (i, rect) in enumerate(rects):
        shape = predictor(gray, rect)
        shape = face_utils.shape_to_np(shape)

        # 提取左眼、右眼、嘴巴和鼻子的关键点
        left_eye = shape[42:48]
        right_eye = shape[36:42]
        mouth = shape[48:68]
        nose = shape[27:36]

        # 计算每个关键点的平均值
        left_eye_center = np.mean(left_eye, axis=0).astype("int")
        right_eye_center = np.mean(right_eye, axis=0).astype("int")
        mouth_center = np.mean(mouth, axis=0).astype("int")
        nose_center = np.mean(nose, axis=0).astype("int")

        # 加载换脸图像
        swap_img = cv2.imread("swap_image.jpg")
        swap_img = cv2.resize(swap_img, (rect.width(), rect.height()))

        # 提取换脸图像的关键点
        swap_gray = cv2.cvtColor(swap_img, cv2.COLOR_BGR2GRAY)
        swap_rects = detector(swap_gray, 1)
        swap_shape = predictor(swap_gray, swap_rects[0])
        swap_shape = face_utils.shape_to_np(swap_shape)

        # 对换脸图像进行仿射变换，使其与当前图像的眼睛、嘴巴和鼻子位置对齐
        M_left_eye = cv2.getAffineTransform(swap_shape[36:42], left_eye)
        M_right_eye = cv2.getAffineTransform(swap_shape[42:48], right_eye)
        M_mouth = cv2.getAffineTransform(swap_shape[48:68], mouth)
        M_nose = cv2.getAffineTransform(swap_shape[27:36], nose)
        swap_img = cv2.warpAffine(swap_img, M_left_eye, (image.shape[1], image.shape[0]))
        swap_img = cv2.warpAffine(swap_img, M_right_eye, (image.shape[1], image.shape[0]))
        swap_img = cv2.warpAffine(swap_img, M_mouth, (image.shape[1], image.shape[0]))
        swap_img = cv2.warpAffine(swap_img, M_nose, (image.shape[1], image.shape[0]))

        # 将换脸图像与当前图像进行融合
        swap_mask = np.zeros(swap_gray.shape, dtype=np.uint8)
        swap_mask = cv2.fillConvexPoly(swap_mask, cv2.convexHull(swap_shape), (255, 255, 255))
        swap_mask = cv2.bitwise_not(swap_mask)
        img_mask = np.zeros(image.shape, dtype=np.uint8)
        img_mask[rect.top():rect.bottom(), rect.left():rect.right()] = swap_mask
        swap_mask = cv2.bitwise_not(swap_mask)
        swap_mask = np.stack((swap_mask,) * 3, axis=-1)
        img = cv2.bitwise_and(image, swap_mask)
        swap = cv2.bitwise_and(swap_img, img_mask)
        result = cv2.add(img, swap)

        # 显示结果
        cv2.imshow("result", result)
        cv2.waitKey(0)

if __name__ == '__main__':
    main()

需要注意的是，这只是一个简单的示例，具体的实现方式和效果可能与你期望的有所不同。如果你需要更高质量的换脸效果，建议使用已有的成熟工具或者更深入的研究。