Discover @Kallaf Open Source projects

Ahmed Elkalaf (@Kallaf)

Kallaf

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Global Rank 735,430 (Top 26 %)
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Registered about 6 years ago
Most used languages

Python
33.3 %

C#
22.2 %

C
11.1 %

Java
11.1 %

Shell
11.1 %

Jupyter Notebook
11.1 %
Location 🇪🇬 Egypt
Country Total Rank 1,647
Country Ranking

Shell
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C#
235

Jupyter Notebook
329

C
448

Python
533

Java
539

Visual-Odometry

Computer Vision Model that determines the new coordinates of the moving car relative to it's previous location using camera in front of the car.

Jupyter Notebook

Risk-game

Risk game is an AI project where I apply 4 different AI search agents (Greedy search, A* search,real time A* and minimax) and 4 non AI agents (Human agent,aggressive agent,passive agent and nearly pacifist agent) I implemented this project using GUI and OOP in java

8-puzzle-solver

An 8-puzzle game solver implementation in Python, uses multiple search algorithms.

LeetCode

LeetCode solutions

Image-Mosaics

In this project, we have implemented an image stitcher that uses image warping and homo-graphies to automatically create an image mosaic. We have focused on the case where we have two input images that should form the mosaic, where we warp one image into the plane of the second image and display the combined views. This problem gives some practice manipulating homogeneous coordinates, computing homography matrices, and performing image warps. For simplicity, we specifies corresponding pairs of points manually using mouse clicks.

Trilateration

Trilateration implementation in C#

Solar-System

3D Simulation for the solar system, using c++ Opengl library.

Competitive-Programming-Environment

competitive programming environment for Linux users it allows them to compile, run and compare there results and execution time with the problem example output in just one command

Stereo-Vision

In this repository we implement and test some simple stereo algorithms. In each case we take two images Il and Ir (a left and a right image) and compute the horizontal disparity (ie., shift) of pixels along each scanline. This is the so-called baseline stereo case, where the images are taken with a forward-facing camera, and the translation between cameras is along the horizontal axis.