EPITA 2021 MLRF practice_01-00_intro v2021-05-17_160644 by Joseph CHAZALON

Creative Commons License This work is licensed under a [Creative Commons Attribution 4.0 International License](http://creativecommons.org/licenses/by/4.0/).

Practice session 1: Introduction

Goals

The objectives of this sessions are:

  1. to get you started with image manipulations using Python;
  2. to let you experiment with simple pattern matching techniques;
  3. to show you the importance (and the challenges) of evaluating the performance of an image processing system.

Agenda

The session is organised as follows:

  1. Stage 1: Jupyter — First, we will quickly review how to use Jupyter efficiently. You can safely skip this first stage, just make sure you know how to use Jupyter's "magics".
  2. Stage 2: NumPy — Second, we will make sure you have learned the basics of Python and are proficient with SciPy major packages: NumPy (matrix and tensor manipulation) and Matplotlib (2D plotting). Important: apparently you already are used to manipulate NumPy, so you can safely skip this stage. Just have a look at Matplotlib examples at the end.
  3. Stage 3: Image manipulations — Then, we'll show/remind you the basics of image manipulation using OpenCV and Scikit-Image.
  4. Stage 4: Twin it! first steps — Finally, we'll use the tools and techniques we have seen to start solving our Twin it! problem.

Make sure you read and understand everything, and complete all the required actions. Required actions are preceded by the following sign: Back to work!

Let's get started!

Now you're ready to move on to the next stage: A quick tour of Jupyter features.