UNET Implementation in PyTorch - Idiot Developer

This tutorial focus on the implementation of the image segmentation architecture called UNET in the PyTorch framework. It's a simple encoder-decoder architecture developed by Olaf Ronneberger et al. for Biomedical Image Segmentation in 2015 at the University of Freiburg, Germany. An image consists of multiple objects inside it, such as people, cars, animals, or any other object. To classify the image, we use image classification, where the task is to predict the label or class of the input image. Now imagine, we need to find the exact location of the object, i.e, which pixel belongs to the which object.