Book Image

Hands-On Deep Learning for Images with TensorFlow

By : Will Ballard
Book Image

Hands-On Deep Learning for Images with TensorFlow

By: Will Ballard

Overview of this book

TensorFlow is Google’s popular offering for machine learning and deep learning, quickly becoming a favorite tool for performing fast, efficient, and accurate deep learning tasks. Hands-On Deep Learning for Images with TensorFlow shows you the practical implementations of real-world projects, teaching you how to leverage TensorFlow’s capabilities to perform efficient image processing using the power of deep learning. With the help of this book, you will get to grips with the different paradigms of performing deep learning such as deep neural nets and convolutional neural networks, followed by understanding how they can be implemented using TensorFlow. By the end of this book, you will have mastered all the concepts of deep learning and their implementation with TensorFlow and Keras.
Table of Contents (7 chapters)

Making predictions

In the previous section, we set up our Docker container, and now, in this section, we'll be using our Docker container to run a REST server and make predictions. We're going to be running our Docker container that we just created and then look at the connected built-in user interface to test our REST service. Finally, we'll post an image with that REST service so that we can see a prediction come back. We'll also see how you can call through to your service with curl, a command-line program that can post files.

Now, we're going to be starting up our Docker container. We'll be mapping the local port 5000 through to the container port 5000, which is the default in our REST service. Then, we'll start the service up. The kerasvideo-server container is the one we just created, and this container will take a second to start up and...