Object detection is an image processing/computer vision task that detects (semantic) objects' instances corresponding to a given type (for example, faces, humans, vehicles, and buildings) in images. In this chapter, you will learn to implement a few state-of-the-art object detection techniques. The following image processing tasks are related to each other (although they refer to different tasks): image classification, object localization, and object detection. Image classification (discussed in the last chapter) aims to predict a class label for an image, whereas object localization deals with identifying the locations and drawing bounding boxes around an object in an image. Object detection combines these two tasks (classification + localization)—it draws a bounding box around each object (there can be multiple objects) of interest in the...
Python Image Processing Cookbook
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Python Image Processing Cookbook
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Overview of this book
With the advancements in wireless devices and mobile technology, there's increasing demand for people with digital image processing skills in order to extract useful information from the ever-growing volume of images. This book provides comprehensive coverage of the relevant tools and algorithms, and guides you through analysis and visualization for image processing.
With the help of over 60 cutting-edge recipes, you'll address common challenges in image processing and learn how to perform complex tasks such as object detection, image segmentation, and image reconstruction using large hybrid datasets. Dedicated sections will also take you through implementing various image enhancement and image restoration techniques, such as cartooning, gradient blending, and sparse dictionary learning. As you advance, you'll get to grips with face morphing and image segmentation techniques. With an emphasis on practical solutions, this book will help you apply deep learning techniques such as transfer learning and fine-tuning to solve real-world problems.
By the end of this book, you'll be proficient in utilizing the capabilities of the Python ecosystem to implement various image processing techniques effectively.
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Python Image Processing Cookbook
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Table of Contents (11 chapters)
Preface
Image Manipulation and Transformation
Free Chapter
Image Enhancement
Image Restoration
Binary Image Processing
Image Registration
Image Segmentation
Image Classification
Object Detection in Images
Face Recognition, Image Captioning, and More
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