Being able to process, extract information from, and understand images quickly has become a critical part of real-world applications in security, payment, healthcare, advertising, and other sectors. This book covers a wide range of topics, following a highly practical approach that guides you through key image processing concepts and algorithms, helping you use leading Python libraries to implement them effectively.As you progress, you’ll gain proficiency in writing Python 3 code and implementing complex image processing and computer vision algorithms to solve problems in image enhancement, restoration, denoising, segmentation, classification, and object detection.
You’ll work with libraries such as PIL, scikit-image, SciPy ndimage, and OpenCV. You’ll also learn to apply machine learning models with scikit-learn and explore deep learning techniques using CNNs (for example, ResNet and YOLO) with TensorFlow, Keras, and PyTorch.
The final chapters guide you through advanced topics such as image-to-image translation, anisotropic diffusion, and generative art.By the end of this book, you will be well versed in image processing and ready to solve a variety of commonly occurring problems.
