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)

Setting up the TensorFlow Object Detection API

The TensorFlow Object Detection API is documented in detail at its official site https://github.com/tensorflow/models/tree/master/research/object_detection, and you should definitely check out its “Quick Start: Jupyter notebook for off-the-shelf inference” guide for a quick idea of how to use a good pre-trained model for detection in Python. But the documentation there is spread out over many different pages, making it sometimes difficult to follow. In this and the next sections, we’ll streamline the official documentation by reorganizing the important details documented in many different places and adding more examples and code explanations, and offer two step-by-step tutorials on:

  1. How to set up the API and use its pre-trained models for off-the-shelf inference
  2. How to retrain pre-trained models with the API...