Book Image

Intelligent Projects Using Python

By : Santanu Pattanayak
Book Image

Intelligent Projects Using Python

By: Santanu Pattanayak

Overview of this book

This book will be a perfect companion if you want to build insightful projects from leading AI domains using Python. The book covers detailed implementation of projects from all the core disciplines of AI. We start by covering the basics of how to create smart systems using machine learning and deep learning techniques. You will assimilate various neural network architectures such as CNN, RNN, LSTM, to solve critical new world challenges. You will learn to train a model to detect diabetic retinopathy conditions in the human eye and create an intelligent system for performing a video-to-text translation. You will use the transfer learning technique in the healthcare domain and implement style transfer using GANs. Later you will learn to build AI-based recommendation systems, a mobile app for sentiment analysis and a powerful chatbot for carrying customer services. You will implement AI techniques in the cybersecurity domain to generate Captchas. Later you will train and build autonomous vehicles to self-drive using reinforcement learning. You will be using libraries from the Python ecosystem such as TensorFlow, Keras and more to bring the core aspects of machine learning, deep learning, and AI. By the end of this book, you will be skilled to build your own smart models for tackling any kind of AI problems without any hassle.
Table of Contents (12 chapters)

Preprocess the Images

Each image in the edges2handbags dataset folder contains the picture of the bag and the picture of the bag edges in the same image. For training the network we need to separate them as images belonging to the two domains A and B that we have discussed in the architecture for DiscoGAN. The images can be split up into Domain A and Domain B images by using the following code (

# -*- coding: utf-8 -*-
Created on Fri Apr 13 00:10:12 2018

@author: santanu

import numpy as np
import os
from scipy.misc import imread
from scipy.misc import imsave
import fire
from elapsedtimer import ElapsedTimer
from pathlib import Path
import shutil
Process the images in Domain A and Domain and resize appropriately
Inputs contain the Domain A and Domain B image in the same image
This program will break them up and store them...