In this article, I will be creating my own trained model for detecting potholes. For detection, I will be using the instance segmentation technique using the Mask-RCNN with the help of Supervisely.

Before creating our model lets get to know what tools and techniques we are using.

What is Instance Segmentation?

Instance segmentation is a technique used for detecting by masking or covering a detected object pixel to pixel. Instance segmentation is very useful in Automatic car as we get pixel to pixel result which increases the accuracy of less accidents

Mask-RCNN

Mask-RCNN is a deep neural network aimed to solve instance segmentation problem in machine learning or computer vision. There are two stages of Mask RCNN. First, it generates proposals about the regions where there might be an object based on the input image. Second, it predicts the class of the object, refines the bounding box and generates a mask in pixel level of the object based on the first stage proposal.

Mask-RCNN is actually a trained model but in this article I will be showing you how to fine tune or train the Mask-RCNN model for your own custom objects.

#computer-vision #computer-science #machine-learning #artificial-intelligence #deep-learning #deep learning