Book Image

Practical Convolutional Neural Networks

By : Mohit Sewak, Md. Rezaul Karim, Pradeep Pujari
Book Image

Practical Convolutional Neural Networks

By: Mohit Sewak, Md. Rezaul Karim, Pradeep Pujari

Overview of this book

Convolutional Neural Network (CNN) is revolutionizing several application domains such as visual recognition systems, self-driving cars, medical discoveries, innovative eCommerce and more.You will learn to create innovative solutions around image and video analytics to solve complex machine learning and computer vision related problems and implement real-life CNN models. This book starts with an overview of deep neural networkswith the example of image classification and walks you through building your first CNN for human face detector. We will learn to use concepts like transfer learning with CNN, and Auto-Encoders to build very powerful models, even when not much of supervised training data of labeled images is available. Later we build upon the learning achieved to build advanced vision related algorithms for object detection, instance segmentation, generative adversarial networks, image captioning, attention mechanisms for vision, and recurrent models for vision. By the end of this book, you should be ready to implement advanced, effective and efficient CNN models at your professional project or personal initiatives by working on complex image and video datasets.
Table of Contents (11 chapters)

Instance segmentation in code


It's now time to put the things that we've learned into practice. We'll use the COCO dataset and its API for the data, and use Facebook Research's Detectron project (link in References), which provides the Python implementation of many of the previously discussed techniques under an Apache 2.0 license. The code works with Python2 and Caffe2, so we'll need a virtual environment with the given configuration.

Creating the environment

The virtual environment, with Caffe2 installation, can be created as per the caffe2 installation instructions on the Caffe2 repository link in the References Section. Next, we will install the dependencies.

Installing Python dependencies (Python2 environment)

We can install the Python dependencies as shown in the following code block:

Note

Python 2X and Python 3X are two different flavors of Python (or more precisely CPython), and not a conventional upgrade of version, therefore the libraries for one variant might not be compatible with...