Turret Gunner Survivability and Simulation Environment Project

This project is a collaborative effort between the Machine Learning, AI, and Virtual Reality Center at Rowan University and the Picatinny Arsenal. We, the AI team at Rowan, have been tasked with developing a drone detection algorithm that enhances the survivability of turret gunners.

Our solution leverages a forked version of YOLOv7, which we have modified to include a special metric for small object detection known as the Normalized Wasserstein Distance. This metric improves the model's ability to detect small objects, a crucial requirement for our simulation environment.

Setting Up a Virtual Environment

This guide will walk you through the steps to create a new virtual environment, install the required dependencies specified in the requirements.txt file.

Prerequisites

Make sure you have the following installed on your system:

• Python 3.6 or later
• Git
• W&B account (sign up here)

Creating a Virtual Environment

1. Clone the repository to your local machine.

   git clone https://github.com/naddeok96/yolov7_mavrc

2. Navigate to the project directory.

   cd yolov7_mavrc

3. Create a new virtual environment.

   python3 -m venv venv_name

4. Activate the virtual environment.

   source venv_name/bin/activate

Installing Dependencies

1. Install the dependencies specified in the requirements.txt file.

   pip3 install -r requirements.txt