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Color Quantization using K-Means clustering algorithm and Python's OpenCV library - Artificial Intelligence (AI) final project - Summer 2024 /// by theMHD; thanks for chatGPT :)

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Color-Quantization-AI-Project

Artificial Intelligence (AI) final project #02 - Summer 2024

Project summary

||| In the name of Allah |||
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Implementation of an Image Processing and a Python Machine Learning project: Color Quantization using K-Means clustering algorithm (with different k values) and OpenCV library.
All functions and variables are written in a Python file Color Quantizer.py. Read the guides and explanations of this project in the Color Quantization - Review.pdf file ...

K-Means algorithm

K-means is an unsupervised machine learning method for clustering data points.
Unsupervised learning in artificial intelligence is a type of machine learning that learns from data without human supervision.
K-means is a centroid-based or a distance-based algorithm, where we calculate the distances to assign a point to a cluster. In K-Means, each cluster is associated with a centroid; the algorithm iteratively divides data points into K clusters by minimizing the variance in each cluster.

More guides, explanations and practical examples:

An example of quantization with different k values

MyForza - figure

Compression ratio for the above k values

MyForza - ratio

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Color Quantization using K-Means clustering algorithm and Python's OpenCV library - Artificial Intelligence (AI) final project - Summer 2024 /// by theMHD; thanks for chatGPT :)

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