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OpenCV 4 with Python Blueprints

You're reading from   OpenCV 4 with Python Blueprints Build creative computer vision projects with the latest version of OpenCV 4 and Python 3

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Product type Paperback
Published in Mar 2020
Publisher Packt
ISBN-13 9781789801811
Length 366 pages
Edition 2nd Edition
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Authors (4):
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Michael Beyeler (USD) Michael Beyeler (USD)
Author Profile Icon Michael Beyeler (USD)
Michael Beyeler (USD)
Dr. Menua Gevorgyan Dr. Menua Gevorgyan
Author Profile Icon Dr. Menua Gevorgyan
Dr. Menua Gevorgyan
Michael Beyeler Michael Beyeler
Author Profile Icon Michael Beyeler
Michael Beyeler
Arsen Mamikonyan Arsen Mamikonyan
Author Profile Icon Arsen Mamikonyan
Arsen Mamikonyan
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Toc

Table of Contents (14) Chapters Close

Preface 1. Fun with Filters 2. Hand Gesture Recognition Using a Kinect Depth Sensor FREE CHAPTER 3. Finding Objects via Feature Matching and Perspective Transforms 4. 3D Scene Reconstruction Using Structure from Motion 5. Using Computational Photography with OpenCV 6. Tracking Visually Salient Objects 7. Learning to Recognize Traffic Signs 8. Learning to Recognize Facial Emotions 9. Learning to Classify and Localize Objects 10. Learning to Detect and Track Objects 11. Profiling and Accelerating Your Apps 12. Setting Up a Docker Container 13. Other Books You May Enjoy

Setting up the app

In order to run our app, we will need to execute the main function ,which reads a frame of a video stream, generates a saliency map, extracts the location of the proto-objects, and tracks these locations from one frame to the next.

Let's learn about the main function routine in the next section.

Implementing the main function

The main process flow is handled by the main function in chapter6.py, which instantiates the tracker (MultipleObjectTracker) and opens a video file showing the number of soccer players on the field:

import cv2
from os import path

from saliency import get_saliency_map, get_proto_objects_map
from tracking import MultipleObjectsTracker


def main(video_file='soccer.avi', roi...
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