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Python Machine Learning Cookbook

You're reading from   Python Machine Learning Cookbook 100 recipes that teach you how to perform various machine learning tasks in the real world

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Product type Paperback
Published in Jun 2016
Publisher Packt
ISBN-13 9781786464477
Length 304 pages
Edition 1st Edition
Languages
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Authors (2):
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Vahid Mirjalili Vahid Mirjalili
Author Profile Icon Vahid Mirjalili
Vahid Mirjalili
Prateek Joshi Prateek Joshi
Author Profile Icon Prateek Joshi
Prateek Joshi
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Toc

Table of Contents (14) Chapters Close

Preface 1. The Realm of Supervised Learning FREE CHAPTER 2. Constructing a Classifier 3. Predictive Modeling 4. Clustering with Unsupervised Learning 5. Building Recommendation Engines 6. Analyzing Text Data 7. Speech Recognition 8. Dissecting Time Series and Sequential Data 9. Image Content Analysis 10. Biometric Face Recognition 11. Deep Neural Networks 12. Visualizing Data Index

Capturing and processing video from a webcam


We will use a webcam in this chapter to capture video data. Let's see how to capture the video from the webcam using OpenCV-Python.

How to do it…

  1. Create a new Python file, and import the following packages:

    import cv2
  2. OpenCV provides a video capture object that we can use to capture images from the webcam. The 0 input argument specifies the ID of the webcam. If you connect a USB camera, then it will have a different ID:

    # Initialize video capture object
    cap = cv2.VideoCapture(0)
  3. Define the scaling factor for the frames captured using the webcam:

    # Define the image size scaling factor
    scaling_factor = 0.5
  4. Start an infinite loop and keep capturing frames until you press the Esc key. Read the frame from the webcam:

    # Loop until you hit the Esc key
    while True:
        # Capture the current frame
        ret, frame = cap.read()
  5. Resizing the frame is optional but still a useful thing to have in your code:

        # Resize the frame
        frame = cv2.resize(frame, None, fx=scaling_factor...
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