基于python的opencv人脸识别(具体人)的模型

2022-12-14 11:55:45 浏览数 (1)

代码语言:javascript复制
import cv2

recognizer = cv2.face.LBPHFaceRecognizer_create()
recognizer.read('face_trainer/trainer.yml')
cascadePath = "haarcascade_frontalface_default.xml"
faceCascade = cv2.CascadeClassifier(cascadePath)
font = cv2.FONT_HERSHEY_SIMPLEX

idnum = 0

names = ['YZE', 'HHJ']

cam = cv2.VideoCapture(0)
minW = 0.1 * cam.get(3)
minH = 0.1 * cam.get(4)

while True:
    ret, img = cam.read()
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

    faces = faceCascade.detectMultiScale(
        gray,
        scaleFactor=1.2,
        minNeighbors=5,
        minSize=(int(minW), int(minH))
    )

    for (x, y, w, h) in faces:
        cv2.rectangle(img, (x, y), (x   w, y   h), (0, 255, 0), 2)
        idnum, confidence = recognizer.predict(gray[y:y   h, x:x   w])

        if confidence < 100:
            idnum = names[idnum]
            confidence = "{0}%".format(round(100 - confidence))
        else:
            idnum = "unknown"
            confidence = "{0}%".format(round(100 - confidence))

        cv2.putText(img, str(idnum), (x   5, y - 5), font, 1, (0, 0, 255), 1)
        cv2.putText(img, str(confidence), (x   5, y   h - 5), font, 1, (0, 0, 0), 1)

    cv2.imshow('camera', img)
    k = cv2.waitKey(10)
    if k == 27:
        break

cam.release()
cv2.destroyAllWindows()

names可以更该为任意名称,根据训练时候所输入的索引来辨别。

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