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Threat Detection System

With school shootings on the rise, our client Critical Reach, a Silicon Valley non-profit, was looking to create a solution to reduce potential threats on school campuses by leveraging AI image recognition technology. This Threat Detection System has the capacity to save lives and is comprised of three components: a threat detection model, a UI, and a data curation tool. The threat detection model identifies five classes of objects: guns, rifles, lenses, wallets, and knives. The threat detection model also features the ability to distinguish people as a police officer or a non-police officer. The UI is simplistic in design as it displays the live camera feed that it is connected to, alerts when a weapon is detected, and the confidence level the algorithm has about the object detected. The data curation tool takes in a video file, slices the file into images, and outputs the images files into a folder.

Install and Deploy

To get the project up and running on your local machine for development and testing purposes as well as how to deploy the project on a live system, please view the following documents for further instructions:

Authors

The following people listed are the authors of this project:

  • Katrina Wilson, Product Owner
  • Connor Coles, Scrum Master
  • Ashley Albert, Developer
  • Derek Araki-Kurdyla, Developer
  • Phuong Cao, Developer
  • Sam Vickers, Developer

Acknowledgement

This project makes use of the following external resources:

  • TensorFlow (Apache 2.0 License) - tensorflow.org
  • YOLO (AGPL-3.0 License) - ultralytics.com/yolo
  • React (Creative Commons Attribution 4.0 International) - react.dev
  • Fast API (MIT License) - fastapi.tiangolo.com
  • PyTorch (3-Clause BSD License) - pytorch.org
  • Python (PSF License Version 2) - python.org

License

This project is licensed under the Creative Commons Attribution 4.0 (CC BY-NC-ND) License. Please visit https://creativecommons.org/ for more details.

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