Repository of Artificial Intelligence and Computer Vision Scripts

This repository contains a collection of scripts developed in the context of Artificial Intelligence (AI) and Computer Vision (CV) subjects. The scripts have been implemented using the Python programming language and cover a wide variety of fundamental concepts and techniques in both areas.

Repository Contents

The repository covers the following topics and concepts:

Graphs and Graph Search Algorithms

• Implementation of graphs using the NetworkX library in Python.
• Graph search algorithms, including Depth-First Search (DFS), Breadth-First Search (BFS), Dijkstra's algorithm, and Prim's algorithm.

Perceptron

• Implementation of the Perceptron algorithm, a basic supervised learning model used in the field of AI.

Computer Vision Filters

• Implementation of various computer vision filters, such as derivative filters, Canny, Prewitt, Sobel, Laplacian, GaussianBlur, and Laplacian with Gaussian filter.

Computer Vision Object Descriptors

• Implementation of object descriptors in computer vision, including chromaticity, chromatic coordinates, and white patch.

Template Matching

• Use of template matching to find specific patterns in an image.

Image Filters

• Implementation of various image filters, such as average blur, Gaussian blur, median blur, maximum filter, and minimum filter.

Final Notes

We hope that these scripts are helpful to you and provide valuable insights into the exciting world of Artificial Intelligence and Computer Vision.