Image classification is the task of predicting labels or categories. Object detection is the task of predicting a list of several deep learning-based algorithms with its corresponding bounding box. The bounding box may have objects other than the detected object inside it. In some applications, labeling every pixel to a label is important rather than bounding box which may have multiple objects. Semantic segmentation is the task of predicting pixel-wise labels.
Here is an example of an image and its corresponding semantic segmentation:
![](https://static.packt-cdn.com/products/9781788295628/graphics/assets/77cfecc2-e2ed-40ae-a40c-7d3b90aa0aca.jpeg)
![](https://static.packt-cdn.com/products/9781788295628/graphics/assets/480974e9-2c9c-4252-b33e-c000ba6a6b77.jpg)
As shown in the image, an input image is predicted with labels for every pixel. The labels could be the sky, tree, person, mountain, and bridge. Rather than assigning a label to the whole image, labels are assigned to each pixel. Semantic segmentation labels pixels independently. You will notice that every...