In the ever-advancing field of computer vision, image processing plays a prominent role. We can extend the applications of Image processing into solving real-world problems like substantially decreasing Human interaction over the art of driving. In the process of achieving this task, we face several challenges like Segmentation and Detection of objects. Mask RCNN is the superior model over the existing CNN models and yields accurate detection of objects more efficiently. In this paper, a mask R-CNN algorithm has been implemented using Python and the object detection results are shown.