基于LBPH的python人脸识别操作

import cv2

# 加载训练数据集文件

# 获取人脸识别对象
recognizer = cv2.face.LBPHFaceRecognizer_create()
# 读取训练数据
recognizer.read('trainer/trainer.yml')

# 准备识别图片
img = cv2.imread('6.pgm')

# 将图片灰度
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

# 加载特征数据
face_detector = cv2.CascadeClassifier('D:/Python/opencv/sources/data/haarcascades
/haarcascade_frontalface_default.xml')
# 参数： scaleFactor(比例因子)：图片缩放多少，minNeighbors:至少检测多少次，
minSize maxSize:当前检测区域的最小面积
faces = face_detector.detectMultiScale(gray)  # scaleFactor=1.01, minNeighbors=3, 
maxSize=(33, 33), minSize=(28, 28)

# 获取脸部特征值
for x, y, w, h in faces:
    cv2.rectangle(img, (x, y), (x+w, y+h), (0, 255, 0), thickness=2)
    cv2.circle(img, (x+w//2, y+h//2), radius=w//2, thickness=2, color=(0, 0, 255))

    # 人脸识别
    id, confidence = recognizer.predict(gray[y:y+h, x:x+w])
    print('标签id:', id, '置信评分：', confidence)


# 显示图片
cv2.imshow('result', img)
cv2.waitKey(0)  # 一直显示
cv2.destroyAllWindows()  # 释放资源