This algorithm uses a rectangle made by the user to identify the foreground item. Then, the user can edit to add or remove objects to the foreground. Then, it removes the background and makes it transparent.

Involves the OpenCV based C++ implementation to detect and track roads for almost realtime performance

My implementation of 《"GrabCut" - Interactive Foreground Extraction using Iterated Graph Cuts》

An iOS image editing app. Computer vision based foreground segmentation with OpenCV and Grabcut algorithm.

Done as part of Computer Vision course assignments(spring 2021) at IIIT Hyderabad.

YOLOv3 object detection then use GrabCut to do semantic segmentation to fish market images.

Course Materials (along with assignments) for Computer Vision, done as a part for requirement of the course "CV" (course-code: CS7.401.S22) @ IIITH. Note: If you are cloning this or taking help of this repo, try to star the repo.

Salient Object Detection to cutout the Object in an image.

Segment and extract the foreground objects accurately with user interaction using OpenCV and Python.

Labs for University course

Extracting the Interactive Foreground from the image

implementing grabcut image segmentation on humerus xray images

Python implementation of the image segmentation algorithm "GrabCut"