Being able to process, extract information, and understand an image quickly has become a critical part of real-world applications within security, payment, healthcare, advertising, and other sectors. This book covers a wide range of topics, following a highly practical approach that takes you through a set of image processing concepts and algorithms to help you learn how to use leading Python library functions to implement these algorithms. As you progress, you’ll gain proficiency in writing code snippets in Python 3 and quickly implement complex image processing and computer vision algorithms to solve problems in image enhancement, restoration, denoising, segmentation, classification, object detection and more, using image processing libraries such as PIL, scikit-mage, scipy ndimage, and opencv-python. You’ll also learn how to use ML models using scikit-learn and explore recent advances with deep learning models with CNNs (e. g., ResNet, Yolo) using tensorflow, keras, and pytorch. The final set of chapters will help you solve advanced problems, such as image-to-image translation, anisotropic diffusion, and generative arts. By the end of this book, you will be well versed in image processing and ready to solve a variety of commonly occurring problems.
