![]() By the end of this book, you'll be able to develop advanced computer vision applications to meet your customers' demands. Toward the concluding chapters, you'll explore the application of artificial intelligence and deep learning techniques using the popular Python libraries TensorFlow, and Keras. You'll also discover how to translate the functionality provided by OpenCV into optimized application code projects using Python bindings. Next, you'll learn machine learning techniques and concepts, understand how to apply them in real-world examples, and also explore their benefits, including real-time data production and faster data processing. The book will also introduce you to the creation of advanced applications using Python and OpenCV, enabling you to develop applications that include facial recognition, target tracking, or augmented reality. ![]() You'll then proceed to study more advanced concepts and discover the full potential of OpenCV. In this book, you'll get started by setting up OpenCV and delving into the key concepts of computer vision. OpenCV for Python enables you to run computer vision algorithms smoothly in real time, combining the best of the OpenCV C++ API and the Python language. It helps developers build complete projects in relation to image processing, motion detection, or image segmentation, among many others. Key Features Develop your computer vision skills by mastering algorithms in Open Source Computer Vision 4 (OpenCV 4) and Python Apply machine learning and deep learning techniques with TensorFlow and Keras Discover the modern design patterns you should avoid when developing efficient computer vision applications Book Description OpenCV is considered to be one of the best open source computer vision and machine learning software libraries. ![]() ![]() ![]() Create advanced applications with Python and OpenCV, exploring the potential of facial recognition, machine learning, deep learning, web computing and augmented reality. ![]()
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