YOLO Object Detection Demo in Python

Overview

This repository contains a Python project demonstrating the use of YOLO (You Only Look Once), a state-of-the-art, real-time object detection system. The demo showcases how to implement YOLO with Python to detect objects in images and video streams.

Prerequisites

Before running the demo, ensure you have the following installed:

• Python 3.6 or later
• OpenCV (cv2)
• YOLOv3 or YOLOv4 weights file
• Corresponding configuration and coco names files

Installation

1. Clone the repository:

   git clone https://github.com/mica83/yolo-test.git
   

2. Navigate to the cloned directory:

   cd yolo_test
   

3. Install the required packages:

   pip install -r requirements.txt
   

Usage

To run the object detection on an image:

python yolo_image.py --image path/to/image.jpg

For real-time detection on a webcam stream:

python main.py --video 0

Features

• Object detection in static images.
• Real-time object detection in video streams.
• Supports YOLOv3 and YOLOv4.

Customization

• Modify the yolo_config.py file to change detection settings, like threshold values, NMS (Non-maximum suppression) threshold, etc.
• Use different weights and cfg files to experiment with other versions of YOLO.

Contributing

Contributions to this project are welcome. Please fork the repository and submit a pull request.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgements

• YOLO (You Only Look Once) by Joseph Redmon and team.
• The OpenCV library.

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