↓Skip to main content
  1. Teaching/
  2. Su2024 CS N324E/
  3. teaching/

Project 0: Welcome to Processing

In this project, you will write a simple Processing program which generates an image. The main goal is for you to get used to the Processing coordinate system and generate a creative artifact. The secondary goal is for you to get used to the project format and submission requirements for this class, which can be somewhat complicated compared to previous classes.

Getting Started
#

You will need a copy of Processing to get started. Visit the Processing Website and download the latest version of Processing for your system. The default Processing mode is Java—you will use this mode for all projects in this class.

Create a project folder for this assignment named <eid>_project0, where <eid> is your UT EID. Create a file within this directory called <eid>_project0.pde and open it in Processing. This file will contain all the code for your project.

Basic Requirements
#

Code
#

Your project should create a static image when run. The image should be of something: don’t just make random strokes on the canvas. The image needs to be at least 500x500 pixels in size, and should contain at least:

  • 3 types of geometric primitives
  • 3 types of stroke weights
  • 4 different colors

This Processing project should run when clicking the “Play” button in the Processing IDE.

Project Report
#

Create a project report as specified in the Project Report rules

Your report for this project will be fairly simple unless you decide to implement extra credit, but practice following the format. In future projects, the report may be quite complex.

Language Model Log
#

You should either submit a log of your language model interactions, or a statement that you did not use LMs for this project. In either case, you will need to submit a file in your project on your LLM usage. See the rules on language model logs for details.

Extra Credit
#

Most projects will have some extra credit within the specification. These extra credit points will be challenging, and require you to look up and understand information not presented in class.

Image Distance (7 pts)
#

In many image applications, we want to measure distances between pixels. To do this, we often assume a pixel is connected to its four nearest neighbors (up, down, left, right) and to no other pixels in the image.

The distance between any two connected pixels is determined (only) by the color difference between the pixels. If the colors are the same, the distance is 0.0. If one pixel is black and the other is white, the distance is 1.0.

Create an alternate display mode for the image you drew which, instead of showing the image, visualizes the length of the shortest path from the center of the image to every pixel of the image, using the pairwise distance rules described above. Draw these such that distance zero is drawn black and the largest distance in the image is drawn in white. To do this, you’ll need to recover the image that’s drawn. You may find the PGraphics class helpful for this.

Document how to enable display of the shortest-path image in your project report.

Submission
#

All files should be within a directory named <eid>_project0. This directory should include:

  1. Your project code
  2. Your project report file (see above)
  3. A language model log (see above)

Place all files into a directory named youreid_project0, zip the directory, and submit it to Canvas.