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Digital Imaging / Visual Computing 2024

This is the repository for the Digital Imaging / Visual Computing course (05_DVC4IL) at the FH Hagenberg.

E-Learning course

Contact: David C. Schedl.

Tutorials:

# Tutorial (link to .ipynb) Open in Colab
1 Python for Computer Vision Open In Colab
2 Introduction to OpenCV Open In Colab
3 Histograms Open In Colab
4 Filters Open In Colab
5 Edges Open In Colab
6 Thresh Open In Colab
7 Lines Open In Colab
8 ML Open In Colab
9 NN Open In Colab
101 CNN Open In Colab

Homework Tasks:

# Homework (link to .ipynb) Open in Colab
1 Point Operations and Histograms Open In Colab
2 Hybrid Images Open In Colab
3 Binary Leaves Open In Colab

Python Setup:

Students have the option to run the code online with Google Colab (requires a Google account) or locally with your own installation of Python.

Online:

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: Open In Colab.

Local:

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).

Useful Links:

Course Grading:

This course will be graded based on your performance in the course homeworks. The homework tasks will be announced while we progress through the course.

Footnotes

  1. Using Colab is highly recommended for these tutorial(s).

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Digital Imaging and Computer Vision

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