https://github.com/alextopher/autopixel
https://github.com/alextopher/autopixel
Last synced: 10 months ago
JSON representation
- Host: GitHub
- URL: https://github.com/alextopher/autopixel
- Owner: Alextopher
- Created: 2023-12-01T10:45:57.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2024-04-26T18:05:44.000Z (almost 2 years ago)
- Last Synced: 2024-04-26T19:24:12.576Z (almost 2 years ago)
- Language: Python
- Homepage: https://pixel.mahoney.best
- Size: 417 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Auto-Pixel
At my school's Computer Science 1 class students learn some basic programming concepts by drawing pixel art programs on [OpenProcessing](https://www.openprocessing.org/), in p5.js. This project is a bit tedious for some students, and it might run counter to the goal of using computers to automate tedious tasks.
I made this small project to show off what a little bit of math and computer science knowledge can do.
Auto-Pixel is a program that takes any image, and converts it into a p5.js program that draws the image as pixel art.
## How it works
The program follows these steps:
1. Pixelate the image
2. Reduce the number of colors with [k-means clustering](https://en.wikipedia.org/wiki/K-means_clustering)
3. Find rectangles of pixels that are the same color [quad-tree decomposition](https://en.wikipedia.org/wiki/Quadtree)
4. Quad-tree nodes are all squares, we optimize by combining adjacent squares into rectangles
5. Write p5.js code to draw the rectangles
## How to use
Dependency management in python is more complicated than I want to support. If you want to use this, you'll have to install the dependencies yourself.
`pixelate.py` requires [OpenCV](https://opencv.org/) and [NumPy](https://numpy.org/).
```cli
usage: pixelate.py [-h] -o OUTPUT [-c COLORS] [-s SIZE] [-v] [-d] [--no-optimize] FILE [FILE ...]
Pixelate an image.
positional arguments:
FILE Input files to process
options:
-h, --help show this help message and exit
-o OUTPUT, --output OUTPUT
Output directory
-c COLORS, --colors COLORS
Number of colors
-s SIZE, --size SIZE Pixel size
-v, --verbose Enable verbose output
-d, --debug Enable debug output
--no-optimize Disable optimization
```
## Flask App
Auto-Pixel can also be used as a small Flask webapp. To run the app, run `app.py` and navigate to `http://localhost:5000/`. This repository also includes an example Dockerfile and docker-compose file, I use that container to run on my own server at .