Git repository to backup work for my fourth year thesis project at the University of Cape Town. The repo is mostly just to back up my work across multiple work stations, so a lot of the commit descriptions are horrible. Woops.
Many systems require a camera to autonomously identify the objects in its field of view, and then rotate the camera to keep it aimed at a certain class of object.
This report describes the design and implementation of such a system on a low-powered device. The system uses a Convolutional Neural Network to identify the position of objects from photos, making use of a neural accelerator device to achieve near real-time inferences. These measurements are improved through the use of a Kalman Filter, which estimates the angular state of the tracked object. A multiprocess pipeline is used to manage the control on a non-real time OS. Finally, a gimbal is designed and built to rotate the unique payload.
The tracking system is shown to improve over a stationary camera setup.
I find development using a notebook to be quite a bit easier than developing using a regular python file. Unfortunately, you can't import a .ipynb as a module. So, here's the workflow:
- Use each
.ipynbfile to understand the code and make changes. - When you want to commit a change, click
Kernal > Restart and Clear Outputto remove your outputs + make the file a bit smaller (shows up as fewer lines in the git commit). - Run the command
jupyter nbconvert --to=python FILENAME.ipynbto generate a.pyfile which can be imported as a module. Just make sure that any debugging code doesn't run if this is imported as a module into another file!
Alexander Knemeyer