Repository for the Computer Vision course (IM520) at the FH Hagenberg held by David C. Schedl.

1. Python for Computer Vision
2. Introduction to OpenCV
3. Filters
4. Edges and Lines
5. Corners and Featuers
6. Alignment
7. Stereo

Students have the option to run the code online with Google Colab (requires a Google account) or locally with your own installation of Python and an editor (I recommend Visual Studio Code).

Everything runs on a Google machine, so you don't need to set up anything on your computer. Furthermore, the machines come with the most popular libraries preinstalled. Just click on the corresponding Open in Colab badge: .

Install Python on your computer via Conda/Miniconda or the Python Installer. Use Python3, as Python2 is not supported anymore. Furthermore, you need an Editor that supports Jupyter (.ipynb) notebooks. I recommend using Visual Studio Code. Optionally, you can also use a local server and open Notebooks in your browser (Visual Studio simplifies this).

• Python Documentation
• OpenCV Tutorial
• If you know Matlab, you can find the differences between Matlab and Python here.

This course will be graded based on your performance in the course project. The topic of your project is free to choose, but it must be Computer Vision related. Focus on a Computer-Vision algorithm, understand its details, and implement it from scratch. You can work with your data or use existing databases (images, videos, …) on a fun topic that interests you. You can find further details here.