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Intro to Digital Image Processing

This directory contains information for getting started with the assignments in the digital image processing part of the NTNU course TDT4195 - Visual Computing Fundamentals.

Assignments can be completed in the programming language of your choice, however, it may be a good idea to select one that support matrix and image processing operations. The computers in the computer lab support Python and MATLAB.

The following Python packages are installed on the lab computers:

Library Function
NumPy Adds support for multi-dimensional arrays along with algorithms to operate on them
Pillow A PIL (Python Imaging Library) fork
imageio A library for reading and writing a range of image data
SciPy Includes a slew of modules that operate on NumPy arrays
matplotlib A 2D plotting package
scikit-image A collection of algorithms for image processing

Getting started

To get started with the assignments, we have created two introductory guides: one for Python and another for MATLAB. Both guides can be found in the getting-started subdirectory:

We recommend that you go through the relevant guide before starting with the assignments.

Installation

Below are a few different ways to set up your own local computer for either Python or MATLAB. Keep in mind that this is not strictly necessary as you can always use the lab computers to do the assignments.

Python

There are multiple ways to install Python. This section outlines some options for installing Python on Linux, Windows, and Mac OS X operating systems.

  • [option 1 - *] Anaconda The easiest way to get quickly started is to install Anaconda. This is a Python distribution that comes with its own virtual environment tool conda and a slew of the most popular Python packages. Please check out the relevant part of the Anaconda documentation for how to install it on Linux, Windows, and Mac OS X systems.
  • [option 2 - Windows] WinPython Take a look at WinPython if you want a similar, but more portable Python distribution compared to Anaconda on Windows.
  • [option 3 - Linux] Manual installation If you have access to a terminal with Python and pip installed, then you can easily create a virtual environment with the packages specified in requirements.txt. To set it up using virtualenv, clone the repository and move into this directory using cd:
sudo pip install virtualenv        # Make sure virtualenv is installed globally
virtualenv ~/.tdt4195env           # Create virtual environment in the home directory
source ~/.tdt4195env/bin/activate  # Activate virtual environment
pip install -r requirements.txt    # Install packages specified in requirements.txt
# Work on assignment
deactivate                         # Deactivate virtual environment

You can also install Python using the installer on the Python website, however, it is more cumbersome to install math heavy packages like NumPy and SciPy this way.

MATLAB

MATLAB is not a free piece of software and you will need a license to run it. Please have a look at the Matlab for students page on NTNU Innsida to see how you can install MATLAB and get an academic license. The most important MATLAB Toolbox to install is the Image Processing Toolbox. Without it you will have a rough time with the assignments.