人脸识别排重软件

import cv2
import numpy as np

# 加载人脸检测器和特征提取器
face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
recognizer = cv2.face.LBPHFaceRecognizer_create()

# 训练数据
def train(images, labels):
    recognizer.train(images, np.array(labels))

# 预测
def predict(image):
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    faces = face_cascade.detectMultiScale(gray, 1.3, 5)
    for (x, y, w, h) in faces:
        roi_gray = gray[y:y+h, x:x+w]
        id_, conf = recognizer.predict(roi_gray)
        return id_, conf

# 示例数据
images = [...]  # 训练图像列表
labels = [...]  # 对应标签列表

# 训练模型
train(images, labels)

# 预测新图像
new_image = cv2.imread('new_image.jpg')
id_, conf = predict(new_image)
if conf < 50:  # 设置置信度阈值
    print(f"识别到重复人脸，ID: {id_}")
else:
    print("未识别到重复人脸")