face_recognition.py

import cv2
import numpy as np
import os 

def face_recognition(pname):
    
    totol_confidence = 0 
    recognizer = cv2.face.LBPHFaceRecognizer_create()
    recognizer.read('.\\trainer\\trainer.yml')
    cascadePath = ".\\trainer\\haarcascade_frontalface_default.xml"
    faceCascade = cv2.CascadeClassifier(cascadePath)

    font = cv2.FONT_HERSHEY_SIMPLEX

    #iniciate id counter
    id = 0

    # names related to ids: example ==> Sajjad: id=1,  etc
    names = [pname, 'Sajjad_RK', 'Reza','Neginnn', 'Osatad'] 

    # Initialize and start realtime video capture
    cam = cv2.VideoCapture(0)
    cam.set(3, 640) # set video widht
    cam.set(4, 480) # set video height

    # Define min window size to be recognized as a face
    minW = 0.1*cam.get(3)
    minH = 0.1*cam.get(4)
    count = 0
    while True:
        
        ret, img =cam.read()
        count+=1
        # img = cv2.flip(img, -1) # Flip vertically

        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)

            id, confidence = recognizer.predict(gray[y:y+h,x:x+w])
            out_confidence = round((100 - confidence)*2+10)
            # Check if confidence is less them 100 ==> "0" is perfect match 
            if (out_confidence > 40):
                id = names[id]
                confidence = "  {0}%".format(out_confidence)
            else:
                id = "unknown"
                confidence = "  {0}%".format(out_confidence)
            
            if(count%20==0):
                print(id,out_confidence)
            
            totol_confidence += out_confidence
        
            cv2.putText(img, str(id), (x+5,y-5), font, 1, (0,0,255), 3)
            cv2.putText(img, str(confidence), (x+5,y+h-5), font, 1, (255,255,0), 2)  
        
        cv2.imshow('camera',img) 

        k = cv2.waitKey(1) & 0xff # Press 'ESC' for exiting video
        if k == 27:
            break

    # Do a bit of cleanup
    print("\n [INFO] Exiting Program ")
    cam.release()
    cv2.destroyAllWindows()
    
    return totol_confidence/count