Automatic captioning of an image is a popular problem in AI that connects image processing and computer vision with NLP. In this recipe, you will learn how to use a pre-trained generative model (known as Show and Tell) based on a deep recurrent neural network architecture that can be used to generate captions (complete sentences in a natural language describing the contents of an image). The model was trained with the objective to maximize the likelihood of the input caption texts given the input training images. im2txt is a TensorFlow implementation of the Show and Tell model that can take images as input and generate human-like captions that describe the image. The model was tested on more than 300,000 images. The model is an end-to-end deep neural network consisting of a CNN (used to learn the implicit features of an input image...
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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