I have found image segmentation quite a useful function in my deep learning career. The level of granularity I get from these techniques is astounding. It always amazes me how much detail we are able to extract with a few lines of code. To perform deep learning semantic segmentation of an image with Python and OpenCV, we: Load the model ( Line ). We begin with a ground truth data set, which has already been manually segmented.
To quantify the performance of a segmentation algorithm, we compare ground truth with the predicted binary. Image Segmentation works by studying the image at the lowest level. Till now, we went over image segmentation techniques using only the scikit image module.

However, it will be worth mentioning some of the image segmentation techniques which use deep learning. Here is a wonderful blog post that focuses on image segmentation architectures, Losses, Datasets, and Frameworks.



