Disclaimer: I never received any formal training, like completely zero, in coding or programming. I am self-taught, have had some very helpful mentors, guides, and collaborators, and early on I figured out how to search the internet for solutions. If you want to learn more or get started, there are a lot of excellent free resources. I now try to pass those skills on to my students, and maintain open-source access to everything I do.
Hopefully something is helpful to you.
3D video analysis
Argus is a python application that provides 3d video analysis tools for lab and consumer grade cameras. We designed it to allow use of non-synchronized cameras with high-distortion lenses (e.g. GoPro) in challenging field situations (or the backyard), but it also works with lab-quality cameras. The files are completely interchangeable with the MATLAB-based DLTdv set of digitizing tools. Get the paper, and go visit the program page for usage and installation instructions.
I have written some other minor functions to help with analysis of data and production of videos for presentation. If you use Argus, please feel free to contact me directly for help with either!
DLC2DLT2DLC – Convert to and from deeplabcut format
Argus (above) and DLTdv use direct linear transformation (DLT) to perform 3D reconstruction with multiple cameras, and save data in a specific format. DeepLabCut automates the landmark digitizing process – the most cumbersome part of high-speed video analysis. While DeepLabCut has 3D capabilities, it relies on a checkerboard calibration that may be difficult to perform in the field. This set of python scripts allows the user to use Argus’ wand calibration for 3D calibration and to label training data, then convert to DeepLabCut format for training and individual video analysis, and then convert back to Argus for final 3D reconstruction.
Classroom Related Software
Writing quizzes in Canvas is a tedious task. There is an expensive program to covert a Word document to a Canvas quiz, but it works only on Windows. This program will convert a simply formatted text document a qti (zip) file that can be easily imported to Canvas to add the questions to a question bank. It is well tested on Mac, and the base script should work on Linux. Installation and usage instructions are available on the package’s GitHub page.