Military Object Detection Project

Overview

This project detects various objects in a military video clips, including army personnel, weapons, aircraft, shoes, and tanks using the YOLOv5 object detection model.

The YOLOv5 model is a state-of-the-art object detection model that is fast and accurate. It can detect objects in real-time and is widely used in various applications, including surveillance, autonomous driving, and robotics.

Output Video

Video Link: https://www.youtube.com/watch?v=j2P9RZeKI3k

Files Included

• app.py: The main Python script for object detection.
• input.mp4: The input video file.
• output.mp4: The output video file with detected objects.
• report.pdf: A detailed report of the project.
• screenshots/: A folder containing screenshots of the detection results.

Setup Instructions

1. Create an Conda Environment:

conda create -n defencecv python=3.8

2. Activate Conda Environment

conda activate defencecv

3. Install the required libraries:

pip install -r requirements.txt

Step 2: Write a Detailed Report

Create a report.pdf with the following sections:

1. Introduction: Briefly describe the project and its objectives.
2. Methodology: Explain the YOLOv5 model and how it was used.
3. Implementation: Describe the steps to implement the object detection.
4. Results: Include the results and analysis.
5. Conclusion: Summarize the project and future work.

Step 3: Capture Screenshots

Take screenshots of the detection results and save them in a folder named screenshots. Include these in your report and presentation.

Step 4: Organize the Files

Organize your project directory as follows:

About the Author

• Name: [Deva Vinoth]
• GitHub: devavinothm
• LinkedIn: Deva Vinoth
• Portfolio: Deva Vinoth
• Email: [learnerdev101@gmail.com]

Connect with Me

• LinkedIn
• GitHub

Have a Great Day!