weapon-detection

Weapon Detection Using YOLO

This project implements a weapon detection system using YOLO (You Only Look Once) for object detection. It processes a video, detects weapons in each frame, and saves the annotated video.

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Features

• Real-time weapon detection in videos
• Bounding box annotations on detected weapons
• Saves the output video with detections
• Easy-to-use Python implementation

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Requirements

Make sure you have the following dependencies installed before running the project:

pip install ultralytics opencv-python

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🛠 Installation & Setup

Clone the Repository

To get started, clone the repository to your local machine using the following command:

git clone https://github.com/your-username/weapon-detection-yolo.git
cd weapon-detection-yolo

Ensure You Have the Model File

Download best.pt (your trained YOLO model) and place it in the project directory.

Install Dependencies

Make sure you have the required dependencies installed:

pip install ultralytics opencv-python

Run the Detection Script

Execute the following command to run the detection script:

python weapon_detection.py

• Ensure video.mp4 exists in the directory or update the script to match the correct file path.
• The output will be saved as weapon_detection_output.mp4.

Exit the Program

• The program will display video frames with detected weapons.
• To stop execution, press 'q' on your keyboard.

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📜 Code Overview

• Load the YOLO model to detect weapons.
• Process the input video, frame by frame.
• Apply object detection using the trained model.
• Save and display results in a new video file with detections.
• Exit when 'q' is pressed.

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📂 File Structure

weapon-detection-yolo/
├── best.pt                   # YOLO model file
├── video.mp4                 # Input video
├── weapon_detection.py       # Main script
├── README.md                 # Project documentation
└── weapon_detection_output.mp4  # Output video (after detection)

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🖥 Example Output

https://github.com/user-attachments/assets/28a04e37-afad-45b2-8291-423bcf17fc6d

📢 Notes

• If you need to train your own model, refer to the official Ultralytics YOLO documentation.
• For real-time detection, you can modify the code to process a webcam feed.

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• Go to your repository link and check if all files are uploaded.

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🎯 Happy Coding! 🚀