video.py

import cv2
import os
import  numpy as np
import face_detect as fr
face_recognizer=cv2.face.LBPHFaceRecognizer_create()
face_recognizer.read("\\Users\\Purvika pandey\\AppData\\Local\\Programs\\Python\\Python37-32\\cs_project\\training_image.yml")
name={0:"deepika",1:"purvika"}

cap=cv2.VideoCapture(0)
while True:
    ret,test_img=cap.read()
    faces_detected,gray_img=fr.facedetection(test_img)

    #for (x,y,w,h) in faces_detected:
     #  cv2.rectangle(test_img,(x,y),(x+w,y+h),(255,0,0),thickness=5)

    #resized_img = cv2.resize(test_img,(800,500))
    #cv2.imshow("face video detected",resized_img)
    #cv2.waitKey(10)

    for face in faces_detected:
        (x,y,w,h)=face
        roi_gray=gray_img[y:y+h,x:x+h]
        label,confidence=face_recognizer.predict(roi_gray)
        print("confidence:",confidence)
        print("label:",label)
        fr.draw_rect(test_img,face)
        predicted_name=name[label]
        if(confidence>37):
            
            fr.put_text(test_img,predicted_name,x,y)
    resized_img = cv2.resize(test_img,(800,500))
    cv2.imshow("face recognition ",resized_img)
    if cv2.waitKey(10) ==ord('q'):break
cap.release()
cv2.destroyAllWindows