A lightweight neural network classification software built in collaboration with Gary Baugh (Intel Application Engineer), using Intel's OpenVINO software. Allows for GPU- or CPU- load. AI models used include YOLO V3, MobileNet V2, and ResNet 50. Completed as a course requirement for TCD CSU33013 (Software Engineering Group Project), Spring Semester 2023.
Potential applications and use cases that build off of this software include advanced object detection/tracking, human distinction/facial recognition, hazard detection in automotive and industrial applications, etc. The real-time capabilities of the software, when combined with the options offered by the multiple models used and run on a sufficient system, allow for a high drgree of veresatility in potential future use cases.
- Andrii Yupyk
- Garrison Mullen
- James Fenlon
- Juliana Murphy
- Karolina Raczyńska
- Liam Junkermann
- Mykhailo Bitiutskyy
- Pierce Buckley
- Ryan Idowu
- Tadhg Brennan
git lfs install
git lfs pull
python -m venv .venv
source ./.venv/bin/activate
python -m pip install --upgrade pip
pip install -r requirements.txt
python -m venv .venv
./.venv/Scripts/activate
python -m pip install --upgrade pip
pip install -r requirements.txt
python /src/gui.py