Learn OpenCV 2020 – Best OpenCV courses, Best OpenCV tutorials & Best OpenCV books

Best OpenCV Courses 2020

Best OpenCV Tutorials 2020

Deep Learning and Computer Vision A-Z: OpenCV, SSD & GANs

Deep Learning and Computer Vision A-Z™: OpenCV, SSD & GANs by Hadelin de Ponteves and Kirill Eremenko will help you learn and master OpenCV. You will build a toolbox of the most powerful Computer Vision models. This OpenCV course will help you understand the theory behind Computer Vision. You will learn object detection and learn facial recognition. This OpenCV tutorial will help you create powerful Computer Vision applications.

Master Computer Vision OpenCV4 in Python with Deep Learning

Master Computer Vision™ OpenCV4 in Python with Deep Learning will help you learn OpenCV4 in Python. This course will help you learn the key concepts of Computer Vision & OpenCV. You will learn how to do Multi Object Detection in OpenCV (up to 90 Objects) using SSDs (Single Shot Detector). This OpenCV training will help you perform Neural Style Transfer using OpenCV. You will learn to carry out image manipulations such as transformations, cropping, blurring, thresholding, edge detection and cropping. This OpenCV tutorial will teach you to segment images by understanding contours, circle, and line detection. You will learn how to approximate contours, do contour filtering, contour ordering and approximations. Feature detection (SIFT, SURF, FAST, BRIEF & ORB) to do object detection is taught. You will learn how to extract facial landmarks for face analysis, applying filters and face swaps. This OpenCV course will teach you Machine Learning in Computer Vision for handwritten digit recognition. You will learn to implement Facial Recognition, Motion Analysis and Object Tracking. Basic computational photography techniques for Photo Restoration (eliminate marks, lines, creases, and smudges from old damaged photos) are taught. You will master Computer Vision with Deep learning, using Keras. This is one of the best OpenCV tutorials in 2020.

Best OpenCV Courses 2020

OpenCV Complete Dummies Guide to Computer Vision with Python

OpenCV Complete Dummies Guide to Computer Vision with Python by Abhilash Nelson will help you learn all OpenCV Image Processing features with examples. You will learn to implement Face Detection, Face Recognition and Optical Character Recognition. This course starts off with installing OpenCV, Virtual Box with Ubuntu and Sublime Text Editor. You will learn to draw shapes including lines, rectangles, simple, concentric circles and random circles. This OpencCV online training covers Image Masking, Image Transformation (Translation, Rotation, Resizing, Flipping, Cropping), Image Gradient Detection, Image Blurring, Image Threshold, Histograms and more! This is one of the best OpenCV courses in 2020.

Best OpenCV Books 2020

Learning OpenCV 3: Computer Vision in C++ with the OpenCV Library

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Learning OpenCV 3: Computer Vision in C++ with the OpenCV Library
  • O\'Reilly Media
  • Kaehler, Adrian (Author)
  • English (Publication Language)
  • 1024 Pages - 01/08/2017 (Publication Date) - O'Reilly Media (Publisher)

Get started with the fast expanding field of computer philosophy with this simple guide. Written by Adrian Kehler and Gary Bradsky, creators of the open source OpenCV Library, the book provides a wide range of roles for developers, educators, robotics and hobbyists. You can learn what it takes to create applications that allow computers to “see” and make decisions based on that data. With more than 500 activities across many fields of philosophy, OpenCV is used for commercial applications such as protection, medical imaging, face and shape recognition, robotics and factory product inspections. This book gives you a solid foundation in computer vision and openness for creating simple or sophisticated vision applications. The practical exercises in each chapter help you apply what you have learned. This modern sculpture with machine learning tools for computer vision covers the entire library in its modern C ++ implementation.

Learn about OpenCV data types, array types and array activities
Capture and store still images and videos with HighGUI
Convert images to enlarge, shrink, distort, rebuild, and repair
Explore pattern recognition with face recognition
Track objects and movements through visual fields
Reconstruct 3D images from stereo vision
Discover OpenCV’s basic and advanced machine learning techniques

Learning OpenCV 4 Computer Vision with Python 3: Get to grips with tools, techniques, and algorithms for computer vision and machine learning, 3rd Edition

Learning OpenCV 4 Computer Vision with Python 3: Get to grips with tools, techniques, and algorithms...
  • Howse, Joseph (Author)
  • English (Publication Language)
  • 372 Pages - 02/20/2020 (Publication Date) - Packt Publishing (Publisher)

Updated to OpenCV4 and Python 3, the book covers the latest in depth cameras, 3D tracking, advanced reality and deep neural networks, a practical code to help you solve real-world computer vision problems. Computer vision is a rapidly evolving science that includes a variety of applications and techniques. This book will help not only those who are new to computer vision, but also experts in the field. You will be able to put the theory into practice by creating applications with OpenCV4 and Python3.

You will start by understanding how to configure it on different platforms with OpenCV4 and Python 3. You will then learn how to perform basic activities such as reading, writing, manipulating and viewing static images, videos and camera streams. Whether guiding you through image processing, video analysis, depth estimation and segmentation or helping you gain practice in creating GUI applications, this book assures you of the potential of practical activities. Next, you will face two popular challenges: face recognition and face recognition. You can also learn about the concepts of object classification and machine learning, which allows you to create and use object detectors and classifiers to track even objects in movie or video camera streams. . Next, you will develop your skills in 3D tracking and augmented reality. Finally, you will cover ANNs and DNNs, learn how to develop applications for identifying handwritten numbers and categorizing a person’s gender and age. At the end of this book, you will have the skills needed to perform real-world computer vision projects. You are about to learn:

Install and familiarize yourself with OpenCV4 Python 3 bindings
Understand the basics of image processing and video analysis
Use a deep camera to separate the foreground and background regions
Identify and locate videos and track their movements
Train and use your own models to match images and classify objects
Identify and identify faces and classify their gender and age
Create an augmented reality application to follow a 3D image
Work with machine learning models including SVM, Artificial Neural Networks (ANN) and Deep Neural Networks (DNN)
Who is this book addressed to?
If you want to learn computer vision, machine learning and openness in the context of real-life practical applications, this book is for you. This OpenCV book will also be useful for experts who are new to computer philosophy and want to stay up to date with OpenCV4 and Python 3.

OpenCV 4 Computer Vision Application Programming Cookbook: Build complex computer vision applications with OpenCV and C++, 4th Edition

OpenCV 4 Computer Vision Application Programming Cookbook: Build complex computer vision...
  • Millan Escriva, David (Author)
  • English (Publication Language)
  • 494 Pages - 05/03/2019 (Publication Date) - Packt Publishing (Publisher)

Discover great recipes to help you understand the concepts of object detection, image processing and facial recognition. Look for the latest features and APIs of OpenCV4 and create computer vision algorithms. Create an efficient, powerful, and secure vision for your applications. Create computer vision algorithms with machine learning capabilities. OpenCV is an image and video processing library used for all types of image and video analysis. Throughout the book, you will work on recipes that perform a variety of tasks, such as facial recognition and identification. With 70 tutorials alone, this book examines common weakness points and best practices for computer vision (CV) developers. Each recipe addresses a specific problem and offers a proven solution and best practice with information on how it works, so you can copy the code and configuration files and modify them according to your needs.

This book starts by configuring OpenSV and explains how to handle pixels. You will understand how to process images with classes and count pixels with histograms. You will learn to identify, describe and match points of interest. As you progress through the chapters, you will become familiar with predictive relationship predictions in images, 3D visual reconstruction, video footage processing, and visual movement tracking. In the final chapters you will cover in-depth learning ideas such as identifying faces and topics. At the end of the book, you will be able to confidently implement a range of computer vision algorithms to meet the technical requirements of your complex CV projects: You will learn:

Install and create a program using the OpenCV Library
Segment images in homogeneous regions and extract meaningful objects
Apply image filters to enhance image content
Use image geometry to relay different views of the photo shoot scene
Calibrate the camera from various observations of images
Identify people and objects in images using machine learning techniques
Reconstruct 3D scenes from images
Explore face recognition using in-depth learning
Who is this book addressed to?
If you are a resume developer or professional who already uses OpenView to create computer vision software, this book is for you. If you are a C ++ programmer for improving computer vision skills by learning OpenSV, you will also find this book useful.

Bestseller No. 1
Learning OpenCV 4 Computer Vision with Python 3: Get to grips with tools, techniques, and algorithms...
  • Howse, Joseph (Author)
  • English (Publication Language)
  • 372 Pages - 02/20/2020 (Publication Date) - Packt Publishing (Publisher)
SaleBestseller No. 2
Learning OpenCV 3: Computer Vision in C++ with the OpenCV Library
  • O\'Reilly Media
  • Kaehler, Adrian (Author)
  • English (Publication Language)
  • 1024 Pages - 01/08/2017 (Publication Date) - O'Reilly Media (Publisher)
Bestseller No. 3
OpenCV 4 Computer Vision Application Programming Cookbook: Build complex computer vision...
  • Amazon Kindle Edition
  • Millán Escrivá, David (Author)
  • English (Publication Language)
  • 496 Pages - 05/03/2019 (Publication Date) - Packt Publishing (Publisher)
Bestseller No. 4
Mastering OpenCV 4 with Python: A practical guide covering topics from image processing, augmented...
  • Villan, Alberto Fernandez (Author)
  • English (Publication Language)
  • 532 Pages - 03/29/2019 (Publication Date) - Packt Publishing (Publisher)
Bestseller No. 5
Raspberry Pi Computer Vision Programming: Design and implement computer vision applications with...
  • Pajankar, Ashwin (Author)
  • English (Publication Language)
  • 306 Pages - 06/29/2020 (Publication Date) - Packt Publishing (Publisher)
SaleBestseller No. 6
Beginning Robotics with Raspberry Pi and Arduino: Using Python and OpenCV
  • Cicolani, Jeff (Author)
  • English (Publication Language)
  • 380 Pages - 04/24/2018 (Publication Date) - Apress (Publisher)
Bestseller No. 7
OpenCV 4 with Python Blueprints: Build creative computer vision projects with the latest version of...
  • Gevorgyan, Dr. Menua (Author)
  • English (Publication Language)
  • 366 Pages - 03/20/2020 (Publication Date) - Packt Publishing (Publisher)
Bestseller No. 8
Building Computer Vision Projects with OpenCV 4 and C++: Implement complex computer vision...
  • Amazon Kindle Edition
  • Millán Escrivá, David (Author)
  • English (Publication Language)
  • 540 Pages - 03/26/2019 (Publication Date) - Packt Publishing (Publisher)
Bestseller No. 9
OpenCV 3.0 Computer Vision with Java: Create multiplatform computer vision desktop and web...
  • Baggio, Daniel Lelis (Author)
  • English (Publication Language)
  • 174 Pages - 07/01/2015 (Publication Date) - Packt Publishing (Publisher)
Bestseller No. 10
Hands-On GPU-Accelerated Computer Vision with OpenCV and CUDA: Effective techniques for processing...
  • Vaidya, Bhaumik (Author)
  • English (Publication Language)
  • 380 Pages - 09/26/2018 (Publication Date) - Packt Publishing (Publisher)
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