face_recognition.py

import cv2 as cv
import numpy as np
import os

haar_cascade=cv.CascadeClassifier('haar_face.xml')
people=[]
for i in os.listdir(r'E:\Things I Did\opencv\Faces\train'):
    people.append(i)

features=np.load('features.npy', allow_pickle=True)
labels=np.load('labels.npy', allow_pickle=True)

face_recognizer=cv.face.LBPHFaceRecognizer_create()
face_recognizer.read('face_trained.yml')

img=cv.imread(r'E:\Things I Did\opencv\Faces\train\Jerry Seinfield\9.jpg')

gray=cv.cvtColor(img, cv.COLOR_BGR2GRAY)
cv.imshow('person',gray)


#Detect face in image
faces_rect=haar_cascade.detectMultiScale(gray,scaleFactor= 1.1,minNeighbors=  4)
for x,y,w,h in faces_rect:
    faces_roi=gray[y:y+h,x:x+h]

    label,confidence= face_recognizer.predict(faces_roi)
    print("Label ",label," with confidence", confidence)

    cv.putText(img, str(people[label]),(20,20),cv.FONT_HERSHEY_COMPLEX,1.0,(0,255,0),2)
    cv.rectangle(img, (x,y), (x+w,y+h), (0,255,0), 2)
cv.imshow('Detected face', img)
cv.waitKey(0)