Face Recognition using OpenCV – Part 3

FACE RECOGNITION OPENCV - fetching data from SQLite

Hello everyone, this is part three of the tutorial face recognition using OpenCV. We are using OpenCV 3.4.0 for making our face recognition app. In the earlier part of the tutorial, we covered how to write the necessary code implementation for recording and training the face recognition program. To follow along with the series and make your own face recognition application, I strongly advise you to check that out first. The part three of the series is titled, “Face Recognition using OpenCV – fetching data from SQLite”.  In this part of the tutorial, we are going to focus on how to write the necessary code implementation for recognizing faces and fetching the corresponding user information from the SQLite database.

If you are following along with the tutorial series face recognition using OpenCV, by the end of part 2 of the series, you should have created three files:

  1. create_database.py: To create database and table
  2. record_face.py: To capture face images and record the corresponding name in the database.
  3. trainer.py: Use of OpenCV’s LBPH Face Recognizer to train the dataset that outputs trainingData.yml file that we’ll be using for face recognition.

You should already have trainingData.yml file inside the ‘recognizer’ directory in the working directory. If you don’t you might want to recheck the Part-2 of the tutorial series. You might also remember from Part-2 of the series that we used LBPH Face recognizer to train our data. If you are curious about how LBPH works, you can refer to this article here.

Face Recognition and fetch data from SQLite

Now, we will be using the file we prepared during training to recognize whose face is it in front of the camera. We already have our virtual environment activated and the necessary dependencies installed. So, let’s get right to it. Make a file named detector.py in the working directory and copy paste the code below:

import cv2
import numpy as np 
import sqlite3
import os

conn = sqlite3.connect('database.db')
c = conn.cursor()

fname = "recognizer/trainingData.yml"
if not os.path.isfile(fname):
  print("Please train the data first")

face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
cap = cv2.VideoCapture(0)
recognizer = cv2.face.LBPHFaceRecognizer_create()

while True:
  ret, img = cap.read()
  gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
  faces = face_cascade.detectMultiScale(gray, 1.3, 5)
  for (x,y,w,h) in faces:
    ids,conf = recognizer.predict(gray[y:y+h,x:x+w])
    c.execute("select name from users where id = (?);", (ids,))
    result = c.fetchall()
    name = result[0][0]
    if conf < 50:
      cv2.putText(img, name, (x+2,y+h-5), cv2.FONT_HERSHEY_SIMPLEX, 1, (150,255,0),2)
      cv2.putText(img, 'No Match', (x+2,y+h-5), cv2.FONT_HERSHEY_SIMPLEX, 1, (0,0,255),2)
  cv2.imshow('Face Recognizer',img)
  k = cv2.waitKey(30) & 0xff
  if k == 27:


Run it using the command python3 detector.py and voila!

Face Recognition using OpenCV - Aryal Bibek

Your face recognition app is now ready. If you had any problem following along with the tutorial or have any confusions, do let us know in the comments. The full code used in this tutorial can be found in this github repo.

Also, if you want to learn how to detect faces using JQuery, here is a nice tutorial at thedebuggers.com



9 Comments on Face Recognition using OpenCV – Part 3

  1. Please am getting this Error in part 3
    name = result[0][0]
    IndexError: list index out of range

  2. C:\face>record.py
    Enter your name: sanju
    Traceback (most recent call last):
    File “C:\face\record.py”, line 18, in
    faces = face_cascade.detectMultiScale(gray, 1.3, 5)
    cv2.error: OpenCV(4.0.0) C:\projects\opencv-python\opencv\modules\objdetect\src\cascadedetect.cpp:1658: error: (-215:Assertion failed) !empty() in function ‘cv::CascadeClassifier::detectMultiScale’

    [ WARN:1] terminating async callback
    whats dis..????

  3. ids, conf = recognizer.predict(gray[y:y + h, x:x + w])
    cv2.error: OpenCV(3.4.5) C:\projects\opencv-python\opencv_contrib\modules\face\src\lbph_faces.cpp:406: error: (-5:Bad argument) This LBPH model is not computed yet. Did you call the train method? in function ‘cv::face::LBPH::predict’

  4. Hi,

    It is a nice article! A quick question. Have you ever deployed this code in Server using Heroku) and tried detecting faces from a browser?

  5. First of all thank you so much for your this awesome effort for us.
    I enjoyed your tutorial and got one problem on running the detector.py file here i got the actual result but after a sort of time i got an error message as:
    name = result[0][0]
    IndexError: list index out of range.

    pls help me to resolve this problem.

    and thank you so much once again

  6. Hi Aryal
    first of all thanks for this pretty recognition project and still it is working good but at the end when we was doing the testing onit and we was sit approx 2miter distance then it gives the output ” unknown ” .
    My Question is this ,what is it not working when the person face is too distance from the camera ?

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