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OpenCV 3.x with Python By Example - Second Edition

You're reading from  OpenCV 3.x with Python By Example - Second Edition

Product type Book
Published in Jan 2018
Publisher Packt
ISBN-13 9781788396905
Pages 268 pages
Edition 2nd Edition
Languages
Authors (2):
Gabriel Garrido Calvo Gabriel Garrido Calvo
Profile icon Gabriel Garrido Calvo
Prateek Joshi Prateek Joshi
Profile icon Prateek Joshi
View More author details
Toc

Table of Contents (17) Chapters close

Title Page
Copyright and Credits
Contributors
Packt Upsell
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. Seam Carving 7. Detecting Shapes and Segmenting an Image 8. Object Tracking 9. Object Recognition 10. Augmented Reality 11. Machine Learning by an Artificial Neural Network 1. Other Books You May Enjoy

Fun with faces


Now that we know how to detect and track faces, let's have some fun with it. When we capture a video stream from the webcam, we can overlay funny masks on top of our faces. It will look something like the following image:

If you are a fan of Hannibal, you can try this one:

Let's look at the code to see how to overlay the skull mask on top of the face in the input video stream:

import cv2 
import numpy as np 

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

face_mask = cv2.imread('./images/mask_hannibal.png') 
h_mask, w_mask = face_mask.shape[:2] 

if face_cascade.empty(): 
    raise IOError('Unable to load the face cascade classifier xml file') 

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)

    face_rects = face_cascade.detectMultiScale(frame, scaleFactor=1.3, minNeighbors=3) 
    for...
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