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.