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OpenCV with Python By Example

You're reading from  OpenCV with Python By Example

Product type Book
Published in Sep 2015
Publisher Packt
ISBN-13 9781785283932
Pages 296 pages
Edition 1st Edition
Languages
Author (1):
Prateek Joshi Prateek Joshi
Profile icon Prateek Joshi

Table of Contents (19) Chapters

OpenCV with Python By Example
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. Applying Geometric Transformations to Images 2. Detecting Edges and Applying Image Filters 3. Cartoonizing an Image 4. Detecting and Tracking Different Body Parts 5. Extracting Features from an Image 6. Creating a Panoramic Image 7. Seam Carving 8. Detecting Shapes and Segmenting an Image 9. Object Tracking 10. Object Recognition 11. Stereo Vision and 3D Reconstruction 12. Augmented Reality Index

Detecting and tracking faces


OpenCV provides a nice face detection framework. We just need to load the cascade file and use it to detect the faces in an image. Let's see how to do it:

import cv2
import numpy as np

face_cascade = cv2.CascadeClassifier('./cascade_files/haarcascade_frontalface_alt.xml')

cap = cv2.VideoCapture(0)
scaling_factor = 0.5

while True:
    ret, frame = cap.read()
    frame = cv2.resize(frame, None, fx=scaling_factor, fy=scaling_factor, interpolation=cv2.INTER_AREA)
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

    face_rects = face_cascade.detectMultiScale(gray, 1.3, 5)
    for (x,y,w,h) in face_rects:
        cv2.rectangle(frame, (x,y), (x+w,y+h), (0,255,0), 3)

    cv2.imshow('Face Detector', frame)

    c = cv2.waitKey(1)
    if c == 27:
        break

cap.release()
cv2.destroyAllWindows()

If you run the above code, it will look something like the following image:

Understanding it better

We need a classifier model that can be used to detect the faces in an...

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