https://github.com/subhan-liaqat/intelligent-image-processing-to-detect-skin-tone-using-kmeans-clustering-and-opencv

https://github.com/subhan-liaqat/intelligent-image-processing-to-detect-skin-tone-using-kmeans-clustering-and-opencv

image-processing matplotlib numpy opencv pandas scikit-learn

Last synced: about 2 months ago
JSON representation

• Host: GitHub
• URL: https://github.com/subhan-liaqat/intelligent-image-processing-to-detect-skin-tone-using-kmeans-clustering-and-opencv
• Owner: subhan-liaqat
• License: mit
• Created: 2024-11-02T10:14:44.000Z (2 months ago)
• Default Branch: main
• Last Pushed: 2024-11-11T11:37:36.000Z (about 2 months ago)
• Last Synced: 2024-11-11T12:31:27.455Z (about 2 months ago)
• Topics: image-processing, matplotlib, numpy, opencv, pandas, scikit-learn
• Language: Jupyter Notebook
• Homepage:
• Size: 38.1 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Intelligent Image Processing To Detect Skin Tone using KMeans Clustering and OpenCV

## Overview

This project focuses on the extraction of skin colors and the detection of dominant colors in images using KMeans clustering and OpenCV. The goal is to analyze skin tone variations effectively, providing insights into color diversity for various applications, including cosmetic and dermatological industries.

## Project Workflow



## Features

- **Skin Color Extraction**: Utilizes KMeans clustering to identify and extract skin tones from images.

- **Dominant Color Detection**: Analyzes images to determine the most prevalent skin color, aiding in understanding skin tone variations.

- **Data Visualization**: Visualizes extracted colors and dominant tones using Matplotlib for better interpretation of results.

## Technologies Used

- Python

- OpenCV

- NumPy

- Scikit-learn

- Matplotlib

- Imutils

## Installation

To run this project, you need to install the required libraries. You can do this by executing the following command:

```bash

pip install -r requirements.txt

```