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FatimaNoorAI/
weapon-detection

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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.

Features

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

Requirements

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

pip install ultralytics opencv-python

🛠 Installation & Setup

Clone the Repository

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

bash

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.

📜 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.

📂 File Structure