Artificial Intelligence (AI) final project #02 - Summer 2024
||| In the name of Allah |||
---------------------------
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 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:
- Link #01: W3Schools - Kmeans
- Link #02: Youtube #1 - Kmeans
- Link #03: Youtube #2 - Kmeans
- Link #04: Aparat #1 - Kmeans
- Link #05: Aparat #2 - Kmeans in Python
- Link #06: Aparat #3 - Kmeans in Matlab