detector.py

import numpy as np
import cv2
import sqlite3

face_cascade = cv2.CascadeClassifier('cascades/data/haarcascade_frontalface_default.xml')
cap = cv2.VideoCapture(0)
rec = cv2.face.LBPHFaceRecognizer_create()
rec.read('recognizer/trainningData.yml')
id=0
font=cv2.FONT_HERSHEY_SIMPLEX

def getProfile(id):
    conn=sqlite3.connect("facebase.db")
    cmd="SELECT * FROM People WHERE Id="+str(id)
    cursor=conn.execute(cmd)
    profile=None
    for row in cursor:
        profile=row
    conn.close()
    return profile
    

while(True):
    ret, img= cap.read()
    gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
    faces = face_cascade.detectMultiScale(gray, scaleFactor=1.3, minNeighbors=5)
    for (x,y,w,h) in faces:
        color = (0,255,0)
        stroke = 2
        end_cord_x = x+w
        end_cord_y = y+h
        cv2.rectangle(img, (x,y), (end_cord_x,end_cord_y), color, stroke)
        id,conf=rec.predict(gray[y:y+h,x:x+w])
        profile=getProfile(id)
        if(profile!=None):
            cv2.putText(img,str(profile[1]),(x,y+h+30),font, .75, (0, 0, 255))
    cv2.imshow('Face',img)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

cap.release()
cv2.destroyAllWindows()