Opencv Python program for Face Detection (original) (raw)

Last Updated : 6 Sep, 2024

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

Python `

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

https://github.com/opencv/opencv/tree/master

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')

https://github.com/opencv/opencv/tree/master

/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

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