My last pen plotter adventure resulted in a simple method to generate a 2d plot in python, export that as an svg, then translate that svg into something readable by my pen plotter. For my next trick, I aimed to optimize the process of exporting multiple colors.
Several months ago, I built a pen plotter from an open-source design from thingiverse and modified it to hold a different servo and be wall-mounted.
The goal of this project was to take a simple 2d plot generated in python, and export it to a gcode format that is readable by the pen plotter device.
This blog is built using Hugo, a static website generator designed for quick build times and easy deployment. A static website requires no server backend, since everything is delivered in a static state to the reader (that’s you!). All code is executed on the client machine. I love the lightweight simplicity of a static website, which brings up some nostalgia for the internet of the mid to late 90s, when these types of pages were the norm.
Over the past few years, I have acquired quite a video collection. Hundreds of files have been downloaded or DVDs ripped, resulting in nearly a terabyte of television and movies. I usually use Handbrake to rip files off a DVD, since it has several parameters that can be tweaked to give the ideal video output. I can easily name the file, specify an output format, and even create a queue for getting multiple videos from a disk. Handbrake does a great job with movies, since often it is a single file that needs extracting. TV shows are a bit more cumbersome, due to multiple disks being involved. For this reason, I have developed the following workflow to easily rip TV shows from a DVD set.
For a project in my computational physics class, I wanted to create something more than a program. With an old webcam, a pantry turntable, and a cheap laser, I figured I could use MATLAB’s image processing abilities to create proof-of-concept 3d scanner.
By centering the object on the turntable, and projecting the laser line onto the object, I can use the camera to collect images while rotating the object at known intervals. The images are then fed into a MATLAB script that calculates the deviation of the laser from the center of the image. Using these deviations, I can plot the location in Cartesian coordinates, and have a rough estimation of the objects outer dimensions.