python实现人脸检测比对

以下是使用dlib库实现人脸检测比对的Python代码：

import dlib
import numpy as np

# 加载人脸检测器和68点模型
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor('shape_predictor_68_face_landmarks.dat')

# 加载两张图片
img1 = dlib.load_rgb_image('img1.jpg')
img2 = dlib.load_rgb_image('img2.jpg')

# 检测人脸并获取特征点
def get_features(img):
    dets = detector(img, 1)
    if len(dets) == 0:
        return None
    face = max(dets, key=lambda d: d.area())
    shape = predictor(img, face)
    features = np.array([[p.x, p.y] for p in shape.parts()])
    return features

# 获取两张图片的特征点
features1 = get_features(img1)
features2 = get_features(img2)
# 计算欧氏距离
def euclidean_distance(x, y):
    return np.sqrt(np.sum((x - y) ** 2))

# 计算两张图片的人脸相似度
def face_similarity(img1, img2):
    features1 = get_features(img1)
    features2 = get_features(img2)
    if features1 is None or features2 is None:
        return None
    dist = euclidean_distance(features1.mean(axis=0), features2.mean(axis=0))
    return dist

# 输出两张图片的人脸相似度
similarity = face_similarity(img1, img2)
print('两张图片的人脸相似度为：', similarity)