This repo contains a collection of desktop apps showcasing key concepts in computer vision

BasicToolkit is an intuitive image-processing and computer vision app that has the feel of Photoshop. It offers a range of processing techniques built from scratch, such as filtering, equalizing, active contouring, and more.

Unsupervised, one-shot, instance-based active contour using deep learning features in python.

A PyQt desktop application for basic image processing techniques along with Jupyter notebook implementation for SNAKES and Hough transformation.

A PyQt desktop application for basic image processing techniques along with Jupyter notebook implementation for SNAKES and Hough transformation.

This repository contains the assignments of Medical Image Analysis and Processing course at Sharif University of Technology.

Computer Vision algorithms implementation using C++QT & opencv.

A web application that use python script for image processing such as detect edges using canny detection , Detect lines , Detect circles , Detect ellipse and initialize the contour and evolve the Active Contour Model (snake) using the greedy algorithm.

Deep snake algorithm for 2D images based on ICLR2020

Computer Vision Project - LV Segmentation using Deep Learning, Active Contour, and Principle Component Analysis

Signal processing library for active contour models, also known as snakes. Includes a GUI application to visually test various active contour models.

Distance Regularized Level Set Evolution Segmentation

Image Processing and Computer Vision tasks using OpenCV Python: motion tracking, face detection, tumor segmentation

Tools to process bidimensional signals or images.

The python code of Chan-Vese model and RSF model for image segmentation