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Computer Vision Projects with OpenCV and Python 3, published by Packt

License: MIT License

Jupyter Notebook 69.33% Python 6.74% Shell 0.09% Makefile 0.01% C++ 23.13% C 0.25% MATLAB 0.46%

computer-vision-projects-with-opencv-and-python-3's Introduction

Computer Vision Projects with OpenCV and Python 3

Computer Vision Projects with OpenCV and Python 3

This is the code repository for Computer Vision Projects with OpenCV and Python 3, published by Packt.

Six end-to-end projects built using machine learning with OpenCV, Python, and TensorFlow

What is this book about?

Python is the ideal programming language for rapidly prototyping and developing production-grade codes for image processing and Computer Vision with its robust syntax and wealth of powerful libraries. This book will help you design and develop production-grade Computer Vision projects tackling real-world problems.

This book covers the following exciting features: Install and run major Computer Vision packages within Python Apply powerful support vector machines for simple digit classification Understand deep learning with TensorFlow Build a deep learning classifier for general images Use LSTMs for automated image captioning Read text from real-world images Extract human pose data from images

If you feel this book is for you, get your copy today!

https://www.packtpub.com/

Instructions and Navigations

All of the code is organized into folders. For example, Chapter02.

The code will look like the following:

testfile = 'test_images/dog.jpeg'

figure()
imshow(imread(testfile))

Following is what you need for this book: Python programmers and machine learning developers who wish to build exciting Computer Vision projects using the power of machine learning and OpenCV will find this book useful. The only prerequisite for this book is that you should have a sound knowledge of Python programming.

With the following software and hardware list you can run all code files present in the book (Chapter 1-7).

Software and Hardware List

Chapter Software required OS required
1-7 Anaconda, Python 3.x, Jupyter Notebook Windows, Mac OS X, and Linux (Any)

We also provide a PDF file that has color images of the screenshots/diagrams used in this book. Click here to download it.

Related products

Get to Know the Author

Matthew Rever Matthew Rever is an image processing and computer vision engineer at a major national laboratory. He has years of experience in automating the analysis of complex scientific data, as well as in controlling sophisticated instruments. He has applied computer vision technology to save a great many hours of valuable human labor. He is also enthusiastic about making the latest developments in computer vision accessible to developers of all backgrounds.

Suggestions and Feedback

Click here if you have any feedback or suggestions.

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