Labs for University course

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.

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.

Python Implementation of Robust PCA

fg is a command-line utility in Unix-like operating systems that runs a job in the foreground. It is commonly used to bring background processes to the foreground for interaction and monitoring.

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