Book Image

Intelligent Mobile Projects with TensorFlow

By : Jeff Tang
Book Image

Intelligent Mobile Projects with TensorFlow

By: Jeff Tang

Overview of this book

As a developer, you always need to keep an eye out and be ready for what will be trending soon, while also focusing on what's trending currently. So, what's better than learning about the integration of the best of both worlds, the present and the future? Artificial Intelligence (AI) is widely regarded as the next big thing after mobile, and Google's TensorFlow is the leading open source machine learning framework, the hottest branch of AI. This book covers more than 10 complete iOS, Android, and Raspberry Pi apps powered by TensorFlow and built from scratch, running all kinds of cool TensorFlow models offline on-device: from computer vision, speech and language processing to generative adversarial networks and AlphaZero-like deep reinforcement learning. You’ll learn how to use or retrain existing TensorFlow models, build your own models, and develop intelligent mobile apps running those TensorFlow models. You'll learn how to quickly build such apps with step-by-step tutorials and how to avoid many pitfalls in the process with lots of hard-earned troubleshooting tips.
Table of Contents (14 chapters)

Detecting Objects and Their Locations

Object detection goes one step further than the image classification discussed in the previous chapter. Image classification just returns a label of class for an image, while object detection returns a list of objects identified in an image, along with a bounding box for each identified object. Modern object detection algorithms use deep learning to build models that can be used to detect and localize all kinds of objects in a single image. In the past few years, faster and more accurate object detection algorithms came one after another, and in June 2017, Google released the TensorFlow Object Detection API that incorporates several leading object detection algorithms.

In this chapter, we’ll first give a quick overview of object detection: the process of creating an effective deep learning model for object detection and then using the...