Object Detection in Pytorch Using Mask R-CNN

Abstract

This research paper aims to investigate the idea of object detection in PyTorch employing the most widely known object detection and localization algorithm that employs image segmentation techniques and deep learning approach, which is Mask Region-based Convolutional Neural Network. Mask R-CNN is widely used in many fields, such as industrial and medical applications, due to its ability to accurately identify objects and generate segmentation masks for each instance. The Mask R-CNN algorithm combines the region proposal generation and object classification stages of Faster R-CNN with an additional branch for pixel-level segmentation.