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Opencv Python program for Face Detection

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The objective of the program given is to detect object of interest(face) in real time and to keep tracking of the same object.This is a simple example of how to detect face in Python. You can try to use training samples of any other object of your choice to be detected by training the classifier on required objects.

Here is the steps to download the requirements below.

Steps:

  1. Download Python 2.7.x version, numpy and Opencv 2.7.x version.Check if your Windows either 32 bit or 64 bit is compatible and install accordingly.
  2. Make sure that numpy is running in your python then try to install opencv.
  3. Put the haarcascade_eye.xml & haarcascade_frontalface_default.xml files in the same folder(links given in below code).

Implementation




# OpenCV program to detect face in real time
# import libraries of python OpenCV 
# where its functionality resides
import cv2 
  
# load the required trained XML classifiers
# data/haarcascades/haarcascade_frontalface_default.xml
# Trained XML classifiers describes some features of some
# object we want to detect a cascade function is trained
# from a lot of positive(faces) and negative(non-faces)
# images.
face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
  
# /data/haarcascades/haarcascade_eye.xml
# Trained XML file for detecting eyes
eye_cascade = cv2.CascadeClassifier('haarcascade_eye.xml'
  
# capture frames from a camera
cap = cv2.VideoCapture(0)
  
# loop runs if capturing has been initialized.
while 1
  
    # reads frames from a camera
    ret, img = cap.read() 
  
    # convert to gray scale of each frames
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
  
    # Detects faces of different sizes in the input image
    faces = face_cascade.detectMultiScale(gray, 1.3, 5)
  
    for (x,y,w,h) in faces:
        # To draw a rectangle in a face 
        cv2.rectangle(img,(x,y),(x+w,y+h),(255,255,0),2
        roi_gray = gray[y:y+h, x:x+w]
        roi_color = img[y:y+h, x:x+w]
  
        # Detects eyes of different sizes in the input image
        eyes = eye_cascade.detectMultiScale(roi_gray) 
  
        #To draw a rectangle in eyes
        for (ex,ey,ew,eh) in eyes:
            cv2.rectangle(roi_color,(ex,ey),(ex+ew,ey+eh),(0,127,255),2)
  
    # Display an image in a window
    cv2.imshow('img',img)
  
    # Wait for Esc key to stop
    k = cv2.waitKey(30) & 0xff
    if k == 27:
        break
  
# Close the window
cap.release()
  
# De-allocate any associated memory usage
cv2.destroyAllWindows() 


Output:

output


Next Article:
Opencv C++ Program for face detection



Last Updated : 16 May, 2023
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