Semantic Segmentation with Deep Learning: A guide and code

Most people in the deep learning and computer vision communities understand what image classification is: we want our model to tell us what single object or scene is present in the image. Classification is very coarse and high-level. Many are also familiar with object detection, where we try to locate and classify multiple objects within the image, by drawing bounding boxes around them and then classifying what's in the box. Detection is mid-level, where we have some pretty useful and detailed information, but it's still a bit rough since we're only drawing bounding boxes and don't really get an accurate idea of object shape. Semantic Segmentation is the most informative of these three, where we wish to classify each and every pixel in the image, just like you see in the gif above!