Face Recognition Using OpenCV | Loading Recognizer

In my previous post we learnt to train a recognizer using a dataset, in this post we are loading recognizer to see how we can use that recognizer to recognize faces.

If you are following my previous posts then you already have the trained recognizer with you inside a folder named “trainner” and “trainner.yml” file inside it. Now we are going to use that training data to recognize some faces we previously trained .

Lets Start By Importing The Libraries

import cv2
import numpy as np

Yes that’s it, thats all we need for this projects.

Now Loading Recognizer

next we create a recognizer object using opencv library and load the training data (before that just sve your script in the same location where your “trainner” folder is located)

recognizer = cv2.createLBPHFaceRecognizer()
recognizer.load('trainner/trainner.yml')

Now we will create a cascade classifier using haar cascade for face detection, assuming u have the cascade file in the same location,

cascadePath = "haarcascade_frontalface_default.xml"
faceCascade = cv2.CascadeClassifier(cascadePath);

Now we will create the video capture object

cam = cv2.VideoCapture(0)

Python

Next we need a “font” that’s because we are going to write the name of that person in the image so we need a font for the text

font = cv2.cv.InitFont(cv2.cv.CV_FONT_HERSHEY_SIMPLEX, 1, 1, 0, 1, 1)

Okay so the first parameter is the font name, 2nd and 3rd is the horizontal and the vertical scale,4rth is shear (like italic), 5th is thickness of line, 6th is line type

So we have all setup

Lets Start the main Loop

Lets start the main loop and do the following basic steps

• Starts capturing frames from the camera object
• Convert it to Gray Scale
• Detect and extract faces from the images
• Use the recognizer to recognize the Id of the user
• Put predicted Id/Name and Rectangle on detected face

while True:
    ret, im =cam.read()
    gray=cv2.cvtColor(im,cv2.COLOR_BGR2GRAY)
    faces=faceCascade.detectMultiScale(gray,1.2,5)
    for(x,y,w,h) in faces:
        cv2.rectangle(im,(x-50,y-50),(x+w+50,y+h+50),(225,0,0),2)
        Id, conf = recognizer.predict(gray[y:y+h,x:x+w])
        cv2.cv.PutText(cv2.cv.fromarray(im),str(Id), (x,y+h),font, 255)
    cv2.imshow('im',im)
    if cv2.waitKey(10) & 0xFF==ord('q'):
        break

So its pretty similar to the face detection code the only difference is the following lines

        Id, conf = recognizer.predict(gray[y:y+h,x:x+w])
        cv2.cv.PutText(cv2.cv.fromarray(im),str(Id), (x,y+h),font, 255)

in the above two line the recognizer is predicting the user Id and confidence of the prediction respectively
in the next line we are writing the User ID in the screen below the face, which is (x, y+h) coordinate

Just Little Finishing Touch (For Unknown Faces)

Now with this we are pretty much done we can add some more finishing touch like its showing user Id instead of the name,
and it cant handle unknown faces,

So to add this additional features we can do the following,

        Id, conf = recognizer.predict(gray[y:y+h,x:x+w])
        if(conf<50):
            if(Id==1):
                Id="Anirban"
            elif(Id==2):
                Id="Obama"
        else:
            Id="Unknown"
        cv2.cv.PutText(cv2.cv.fromarray(im),str(Id), (x,y+h),font, 255)

Now Some Cleanup

cam.release()
cv2.destroyAllWindows()

Now that everything is done, we need to close the camera and the windows. and we are done!!!!

And this is the results

The Complete Face Recognition Code In One Piece

Now as Promised

import cv2
import numpy as np

recognizer = cv2.createLBPHFaceRecognizer()
recognizer.load('trainner/trainner.yml')
cascadePath = "haarcascade_frontalface_default.xml"
faceCascade = cv2.CascadeClassifier(cascadePath);


cam = cv2.VideoCapture(0)
font = cv2.cv.InitFont(cv2.cv.CV_FONT_HERSHEY_SIMPLEX, 1, 1, 0, 1, 1)
while True:
    ret, im =cam.read()
    gray=cv2.cvtColor(im,cv2.COLOR_BGR2GRAY)
    faces=faceCascade.detectMultiScale(gray, 1.2,5)
    for(x,y,w,h) in faces:
        cv2.rectangle(im,(x,y),(x+w,y+h),(225,0,0),2)
        Id, conf = recognizer.predict(gray[y:y+h,x:x+w])
        if(conf<50):
            if(Id==1):
                Id="Anirban"
            elif(Id==2):
                Id="Sam"
        else:
            Id="Unknown"
        cv2.cv.PutText(cv2.cv.fromarray(im),str(Id), (x,y+h),font, 255)
    cv2.imshow('im',im)
    if cv2.waitKey(10) & 0xFF==ord('q'):
        break
cam.release()
cv2.destroyAllWindows()

Complete Video Tutorial

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For this code: you can visit: https://github.com/thcodacus/Face-Recognition

nazmi69 has done a good job converting the code for python 3.x and opencv 3.0
available at https://github.com/nazmi69/Face-Recognition