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Python Image Processing Cookbook

Python Image Processing Cookbook

By : Sandipan Dey
2 (2)
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Python Image Processing Cookbook

Python Image Processing Cookbook

2 (2)
By: Sandipan Dey

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.
Table of Contents (11 chapters)
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Image completion with inpainting using deep learning

In this recipe, you will learn how a Fully-Convolutional deep learning Network (FCN, called a Completion Network model, from a recent paper, Globally and Locally Consistent Image Completion from SIGGRAPH 2017) can be used to complete the missing parts of a (previously unseen) image. We shall specifically use a pre-trained version of the neural network model to predict the missing parts in an image. The model will accept an input image and a mask (corresponding to the missing parts in the image) and try to predict the missing parts from the information provided by the remaining (incomplete) image.

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