https://github.com/real0x0a1/objectdetection

Real-time Object Detection using YOLOv
https://github.com/real0x0a1/objectdetection

numpy opencv python python3

Last synced: 1 day ago
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Real-time Object Detection using YOLOv

• Host: GitHub
• URL: https://github.com/real0x0a1/objectdetection
• Owner: real0x0a1
• License: mit
• Created: 2023-12-11T09:48:15.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2023-12-11T10:08:33.000Z (about 1 year ago)
• Last Synced: 2024-11-14T05:38:02.894Z (2 months ago)
• Topics: numpy, opencv, python, python3
• Language: Python
• Homepage:
• Size: 5.86 KB
• Stars: 2
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Real-time Object Detection using YOLOv3

[![License](https://img.shields.io/badge/License-MIT-blue.svg)](https://opensource.org/licenses/MIT) 

## Overview

This Python script uses the YOLOv3 (You Only Look Once) model for real-time object detection using a webcam feed. It detects objects in the frame and draws bounding boxes around them with labels and confidence scores.

## Prerequisites

- Python 3.x

- OpenCV (`cv2`)

- NumPy (`numpy`)

## Installation

1. Clone the repository:

   ```bash

   git clone https://github.com/Real0x0a1/ObjectDetection.git

   ```

2. Install required dependencies:

   ```bash

   pip3 install opencv-python numpy

   ```

3. Download YOLOv3 weights file:

   - YOLOv3 Weights: [Download YOLOv3 Weights](https://pjreddie.com/media/files/yolov3.weights)

   - YOLOv3 Weights: `wget https://pjreddie.com/media/files/yolov3.weights`

   Place these files in the appropriate directories as mentioned in the script.

## Usage

Run the script:

```bash

python3 ObjectDetection.py

```

Press 'q' to exit the real-time object detection.

## Customization

- Adjust confidence threshold: Modify the `confidence > 0.5` condition to change the confidence threshold.

- Customize YOLO file paths: Update the paths in the script based on your folder structure.

## Author

- Ali (Real0x0a1)

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.