In this tutorial you find NumPy exercises that create images.
It is meant as a gentle introduction to NumPy. It assumes that you have made your first steps with Python already. To get the best out of it, put it into practice immediately:
paint things – create art – have fun!
If you are using the Anaconda distribution, you should have all necessary libraries already.
Otherwise, download or clone the git repository github.com/krother/generative_art and install the libraries using pip:
:::bash
pip install -r requirements.txt
Next, try the examples and challenges.
| Example | Topic |
|---|---|
| Grayscale | Create a grayscale image |
| Color | Create a RGB image |
| Random Blur | Create random pixels |
| Flags | Slicing |
| Repeat | Repeating tiles |
| Example | Topic |
|---|---|
| Stars | Indexing |
| Lines | Arithmetics |
| Gradient | Linear space |
| Triangles | Matrix operations |
| Circles | Euclidean Distances |
| Mask | Indexing |
| Example | Topic |
|---|---|
| K-Means | Clustering |
| Decision Tree | Color prediction |
| Convolution | CNN kernel |
| Monte Carlo | Sampling |
| Example | Topic |
|---|---|
| Rotation | Rotation figure |
| Shadow | shadow using a mask |
| Warhol | Color channels |
| Puzzle | vstack and hstack |
| Contour Lines | Gaussian Mixture |
| Edge Detection | Sobel Operator |
| Dragon Curve | Recursive graphics |
| Mandelbrot | Recursive graphics |
| Hexpanda | Hexbin plot |
| Vortex | Animation |
(c) 2019 Dr. Kristian Rother (krother@academis.eu)
Distributed under the conditions of the MIT License. See LICENSE for details.
The Brandenburg Gate image is by Thomas Wolf, www.foto-tw.de / Wikimedia Commons / CC BY-SA 3.0