This chapter covers:
- Running pre-trained image recognition models on sample data
- An introduction to GANs (generative adversarial networks) and CycleGAN
- Captioning models that can produce text descriptions of images
- Sharing models through TorchHub
We closed our first chapter promising to unveil amazing things in this chapter, and now it’s time to deliver.
Computer vision is certainly one of the fields that have been most impacted by the advent of deep learning, for a variety of reasons. The need for classifying or interpreting the content of natural images existed, very large datasets became available and new constructs such as convolutional layers were invented and could be ran quickly on GPUs with unprecedented accuracies. All this combined with the motivation of the Internet giants to understand pictures shot by millions of users through their mobile devices and managed on said giants' platforms. Quite the perfect storm.