Face Detection using Webcam

The script will perform the following tasks: it will open a camera feed, it will read a frame, it will examine that frame for faces, it will scan for eyes within the faces detected, and then it will draw blue rectangles around the faces and green rectangles around the eyes.

You can download haarcascade_frontalface_default.xml from Here

You can download haarcascade_eye.xml from Here

Here is input image

# Import Neccessary libraries
import numpy as np
import cv2

# Load haar cascade for face
face_cascade = cv2.CascadeClassifier(' haarcascade_frontalface_default.xml')
# Load haar cascade for eyes
eye_cascade = cv2.CascadeClassifier(' haarcascade_eye.xml')
# Declare instance for Webcam
cap = cv2.VideoCapture(0)
# Start infinite loop
while 1:
    # Read ret and frame
    ret, img = cap.read()
    # Convert to grayscale
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    # Detect faces from grayscale
    faces = face_cascade.detectMultiScale( gray, 1.3, 5)
    # Extract dimensions for faces
    for (x,y,w,h) in faces:
        # Create rectange around face
        cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
        roi_gray = gray[y:y+h, x:x+w]
        roi_color = img[y:y+h, x:x+w]
        # Detect eyes from region of interest of grayscale
        eyes = eye_cascade.detectMultiScale( roi_gray)
        # Extract dimensions of eyes and draw rectangle around eyes
        for (ex,ey,ew,eh) in eyes:
            cv2.rectangle(roi_color,(ex,ey),(ex+ew,ey+eh),(0,255,0),2)
    # Display window
    cv2.imshow('img',img)
    # Obtain key pressed and break loop when Enter key is pressed
    k = cv2.waitKey(30) & 0xff
    if k == 13:
        break

# Relase and destroy windows
cap.release()
cv2.destroyAllWindows()