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Practical Convolutional Neural Networks

You're reading from Practical Convolutional Neural Networks Implement advanced deep learning models using Python

Product type Paperback

Published in Feb 2018

Publisher Packt

ISBN-13 9781788392303

Length 218 pages

Edition 1st Edition

Languages

Python

Tools

Keras

Concepts

Deep Learning

Authors (3):

Mohit Sewak

Md. Rezaul Karim

Pradeep Pujari

View More author details

Table of Contents (11) Chapters

Preface

1. Deep Neural Networks – Overview FREE CHAPTER

2. Introduction to Convolutional Neural Networks

3. Build Your First CNN and Performance Optimization

4. Popular CNN Model Architectures

5. Transfer Learning

6. Autoencoders for CNN

7. Object Detection and Instance Segmentation with CNN

8. GAN: Generating New Images with CNN

9. Attention Mechanism for CNN and Visual Models

10. Other Books You May Enjoy

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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...

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Authors (3)

Mohit Sewak

Mohit Sewak

Mohit is a Python programmer with a keen interest in the field of information security. He has completed his Bachelor's degree in technology in computer science from Kurukshetra University, Kurukshetra, and a Master's in engineering (2012) in computer science from Thapar University, Patiala. He is a CEH, ECSA from EC-Council USA. He has worked in IBM, Teramatrix (Startup), and Sapient. He currently doing a Ph.D. from Thapar Institute of Engineering & Technology under Dr. Maninder Singh. He has published several articles in national and international magazines. He is the author of Python Penetration Testing Essentials, Python: Penetration Testing for Developers and Learn Python in 7 days, also by Packt. For more details on the author, you can check the following user name mohitraj.cs

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Pradeep Pujari

Pradeep Pujari

https://www.linkedin.com/in/ppujari/

See other products by Pradeep Pujari

Karim

Karim

Md. Rezaul Karim is a researcher, author, and data science enthusiast with a strong computer science background, coupled with 10 years of research and development experience in machine learning, deep learning, and data mining algorithms to solve emerging bioinformatics research problems by making them explainable. He is passionate about applied machine learning, knowledge graphs, and explainable artificial intelligence (XAI). Currently, he is working as a research scientist at Fraunhofer FIT, Germany. He is also a PhD candidate at RWTH Aachen University, Germany. Before joining FIT, he worked as a researcher at the Insight Centre for Data Analytics, Ireland. Previously, he worked as a lead software engineer at Samsung Electronics, Korea.

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