This Jupyter notebook demonstrates image segmentation using Lazy Snapping and K-Means Clustering. It showcases how these algorithms can partition an image into segments based on pixel intensity and user-defined masks.

Labs for University course

Python Implementation of Robust PCA

Implementations of various foreground object extraction methods in Computer Vision

An official repository for "Background subtraction based on Gaussian mixture models using color and depth information".

A bot that keeps on following the yellow path until it encounters a blue path.

Collection of image processing modules like foreground extraction, contour extraction, histogram manipulation.

Implementation of "GrabCut": interactive foreground extraction using iterated graph cuts", in MATLAB

Multi-thread Background Subtraction Method.

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

Remove and Replace background in live video in real-time. Using webcam and python

Simplified Deep Image Matting training code with keras on tensorflow

open source background removal and masking tools useful for photogrammetry

FgSegNet: Foreground Segmentation Network, Foreground Segmentation Using Convolutional Neural Networks for Multiscale Feature Encoding