The program our team has developed is designed to assist OSU’s Big Fish Lab in analyzing video taken from cameras attached to sharks. It can identify ~10 different forms of ocean events, some of which the lab finds interesting (e.g. fish, kelp), and some of which are identified as being something non-interesting (e.g. sunlight, noise). The program has two main components: the graphical user interface (GUI), and the underlying machine learning model (classifier) that it interacts with. The program itself is provided as platform-specific executables (Windows), and comes bundled with all dependencies needed to run the program.
Development of the program requires:
- Python 3 (tested on 3.9) with packages:
- scikit-image (0.19.1+ recommended)
- numpy
- openpyxl
- ffmpeg-python
- pysimplegui
- sklearn
- pandas
- alive-progress
- imageio-ffmpeg
- seaborn
- pyinstaller
Please refer to the handoff document for in-depth instructions on how to get the program running.