The hundred-page Computer Vision OpenCV book in Python

Are you excited about Computer Vision and would love to join the party?!

 

Perhaps you would like to give your homemade robot its own vision and navigation? Make it to recognize faces? Or to learn how to walk around? Or maybe you would like to start making Apps to track people and to secure your smart home? 

Or maybe you want to start a new career in the Self-Driving car industry?

 With my Computer Vision book, you can accomplish the following:

  • Understand the fundamentals of image processing 

  • Remove noise from your images, enhance colors and experiment with brightness and illumination
  • Make your own Instagram-like filters and boost your likes 🙂  
  • Detect points of interest in your images and use them for object detection and classification
  • Prepare your data for Machine Learning algorithms
  • And more. This book is just the beginning! 

Grasp the best practice from the Self-Driving industry frontiers 

As a computer vision engineer within a camera team, I was familiar with a lot of software modules for self-driving trucks (yes, trucks!): low-speed maneuvering, camera blockage, camera calibration.  Hence, I do hope that I’m in a position to instruct you what is the optimal path in order to start this journey. You will notice that “The 100-page computer vision book” consists of four things:

  1. Theory, which provides intuition about the topics
  2. Python code, is easy for beginners and quick to start with
  3. C++ code. I hate it, but it is super fast and you need it to run on hardware
  4. Mastering OpenCV library

When I switched from Data Analyst to Computer Vision, I used this book to quickly refresh my knowledge and learn OpenCV library.

B. Vukov

Data analysis at Upwork

Experience from a University classroom

I do not want to sound overly naive and to preach that Computer Vision, Deep Learning and Image Processing are easy topics to grasp. To fully master them, they do require a lot of persistence, effort and programming, as well as a solid understanding of mathematics. Especially for beginners or amateurs in Computer Vision, it can be very difficult and demotivating.

Master complex algorithms without giving yourself a headache

Therefore, my motto while teaching students was always to teach them to make practical things while understanding the theory. By understanding these implications, the goal was to get any intuition about the algorithms without the need of heavy mathematics where it is not needed.  For years I’ve been improving my teaching methods and I judged my results by the final students projects that they had to deliver.

I have been using this book at my lectures during programming sessions.

Marijana Marjanovic

Associate Professor at Singidunum University

This book is a perfect balance between theory and practical algorithms.

Amir Salarpour

Assistant Professor Of Artificial Intelligence at Sirjan University of Technology

 

The 100-page Computer Vision book is perfect for you!

Learn how to write a code while understanding the theory

After reading this book, you will gain a full understanding of complicated code and mathematical formulas in a very short time while grasping the theory behind Computer Vision.

There are a lot of materials that teach this subject in a very superficial way. I call this show me the code” way of learning. Although it allows a quick start in the Computer Vision journey, it does not provide an understanding of the algorithms being used. So very quickly someone can become demotivated when the person realizes that he/she is only using a bunch of recipes. When it comes to changing certain parameters, optimizing the code, combining more approaches, one usually feels stuck and overwhelmed.

 

 

Learn how to process your images

This book starts out with essential guides to load and process images and videos. Then, it gives you an idea of how you can improve the quality of your images. You will learn how to work with filters and how you can smooth or sharpen your images.

 


 

 

 

 

Prepare your data for Machine Learning algorithms

In addition, you will learn how to adjust the contrast of your images using the histogram equalization algorithm. It is one of the best methods for image enhancement, which provides better quality of images without loss of any information.

 

• You will learn how to detect basic shapes in images, such as lines and circles. For this, you will learn the basics of Hough transform.

• Learn how to manipulate image colors and create a fascinating fade in and fade out effect.

• You will get an intuition and all the needed tools to fully grasp a 2D discrete Fourier transform.

• Get a basic understanding about filtering methods.

 

 

Learn how to detect feature points in an image 

In many Computer Vision and Machine Learning applications, we need some feature points which we will track or which will assist us to compare and detect objects or scenes. A special chapter is dedicated to the detection of these characteristic points in an image. We are doing this by the use of the well-known Harris corner detector.

 

Computer Vision: What it is and why it matters

Computer Vision represents one of the most fascinating subjects. Both engineering and research fields have to deal with it nowadays. In the last few years, there has been significant progress in computer vision achievements. Nowadays computers can recognize people easily. On the latest iPhone, you can implement face recognition end fingerprint recognition options. All this is possible thanks to deep learning and computer vision research results. Moreover, computers nowadays can recognize many different objects with very high accuracy. For instance, you can just point your cell phone when taking a picture and it will mark where a face is. You can wave to your smartphone and in that way, the smartphone will recognize that you want to take a photo and it will be saved on your phone.

Step into the future of intelligent robots and self-driving cars

You have probably heard about recent advancements in the self-driving car industry. With the first experiments nowadays it is almost possible to have a fully autonomous drive. In addition, a famous Boston dynamics start-up company from the US has developed an already well-known series of robots. Those robots are human-like, like the one called Atlas, but they can also be dogs and can be used for many interesting and practical activities. The latest achievements can be seen on YouTube videos of the Atlas robot, and it shows that it performs many acrobatic exercises better than an average human. All this will result in tremendous growth of artificial intelligence end computer vision applications. This will boost new branches of technology and will create jobs of the future. Therefore, whether it is for a hobby or for your professional career starting a new venture in the computer vision area, this book will be an important and beneficial step for you.