This repository is all about computer vision

It includes small projects on various computer vision topics, such as object detection, object tracking, classical computer vision techniques, image segmentation, image classification, feature extraction algorithms, and more.

Most of the projects have both C++ and Python implementations.

I will continue to update this repository with new content.

Each project includes an article that explains how the algorithm works, how the code is structured, provides general information about the algorithms, and much more.

You can find all the articles in the README files for each folder, and you can check all of my articles from this link: https://medium.com/@siromermer.

Classical Computer Vision (Pure OpenCV Mostly)

Tracking Objects with SIFT algorithm	Tracking Objects with FAST algorithm	Tracking Objects with ORB algorithm
Tracking Objects with Kalman algorithm	Tracking Objects with Lucas Kanade algorithm	Tracking Objects with Mean shift algorithm
Tracking Objects with Background Subtraction	Text extraction from pages (OCR)	Perspective Transformation
Color-based Object Detection GUI	Object Detection with OpenCV Cascade Classifiers

Deep Learning (PyTorch, TensorFlow)

YOLO Object Detection GUI	Detection (YOLO) + Segmentation (SAM)	Detection (YOLO) + Classification (TensorFlow)
Custom YOLO-NAS Training Pipeline	YOLO Model Inference in C++

Example Videos

To test these projects in your local environment with C++, delete the build folder and rebuild it. This is necessary because the folder paths will change, because of that you need to rebuild the project.
For python you can execute files directly