InChapter 3, Convolutional Neural Networks, we demonstrated how a CNN can be used to autoencode an image to obtain a compression of the image. In the digital age, it's even more important to be able to scale up the resolution of an image to high quality. For example, a version of an image can easily be shared via the internet. When the image arrives at the receiver, its quality will need to be increased, also known as Super-Resolution imaging (SR). In the following recipe, we will show you how to increase the resolution of image by training deep learning with the PyTorch framework.
- First, we need to import all the necessary libraries:
import os from os import listdir from os.path import join import numpy as np import random import matplotlib.pyplot as plt import torchvision from torchvision import transforms import torchvision.datasets as datasets import torch import torch.nn as nn import torch.nn.functional...