YOLO Object Detection with OpenCV✨

This repository contains a Python program for object detection using the YOLO (You Only Look Once) model with OpenCV.

Table of Contents

• Introduction
• Requirements
• Setup
• Usage
• Acknowledgements
• License

Introduction

This project demonstrates object detection on an input image using the YOLOv3 model. The YOLO algorithm is known for its speed and accuracy in detecting objects in real-time. The program uses OpenCV to handle image processing and visualization tasks.

Requirements

• Python 3.x
• OpenCV
• NumPy

Setup

1. Clone the repository:

   git clone https://github.com/yourusername/yolo-object-detection.git
   cd yolo-object-detection

2. Install the required packages:

   pip install opencv-python numpy

3. Download the YOLOv3 weights and configuration files:

   • YOLOv3 weights
   • YOLOv3 configuration
   • COCO names

4. Place the downloaded files (yolov3.weights, yolov3.cfg, and coco.names) in the project directory.

Usage

1. Replace sampleimage1.jpg with your input image in the project directory.

2. Run the program:

   python yolo_object_detection.py

3. The program will display the input image with detected objects outlined with bounding boxes and labeled with class names.

Acknowledgements

• YOLO: Real-Time Object Detection
• OpenCV
• COCO dataset