Pix2pix is a variant of the conditional GAN. We have already covered conditional GANs in Chapter 3, Face-Aging Using Conditional GAN (cGAN). Before moving forward, make sure you take a look at what cGANs are. Once you are comfortable with cGANs, you can continue with this chapter. Pix2pix is a type of GAN that is capable of performing image-to-image translation using the unsupervised method of machine learning (ML). Once trained, pix2pix can translate an image from domain A to domain B. Vanilla CNNs can also be used for image-to-image translation, but they don't generate realistic and sharp images. On the other hand, pix2pix has shown immense potential to be able to generate realistic and sharp images. We will be training pix2pix to translate labels of facades to images of facade. Let's start by understanding the architecture of pix2pix.
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Kailash Ahirwar is a machine learning and deep learning enthusiast. He has worked in many areas of Artificial Intelligence (AI), ranging from natural language processing and computer vision to generative modeling using GANs. He is a co-founder and CTO of Mate Labs. He uses GANs to build different models, such as turning paintings into photos and controlling deep image synthesis with texture patches. He is super optimistic about AGI and believes that AI is going to be the workhorse of human evolution.
Read more about Kailash Ahirwar
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Kailash Ahirwar is a machine learning and deep learning enthusiast. He has worked in many areas of Artificial Intelligence (AI), ranging from natural language processing and computer vision to generative modeling using GANs. He is a co-founder and CTO of Mate Labs. He uses GANs to build different models, such as turning paintings into photos and controlling deep image synthesis with texture patches. He is super optimistic about AGI and believes that AI is going to be the workhorse of human evolution.
Read more about Kailash Ahirwar