The left image works as the condition, and the model generates the image at right. (Check out the pix2pix example with TensorFlow to try it for yourself.)Ī pix2pix generated image. Pix2pix is a kind of conditional generative adversarial network (cGAN) model that’s designed to generate a realistic image from a specified image as a condition. The site uses a pix2pix-based ML model for the style transformation. It generates classical-painting style portraits based on portrait photos that you upload to the site.Ī classical-painting style portrait generated with AI Gahaku. In March 2020, Sato released AI Gahaku (“AI master painter”), which he has been developing alone. “I could get a great learning environment at no cost." Developing AI Gahaku "As I have been earning so little money these days, it was very helpful for me that TensorFlow and Colab are freely available,” Sato explains. He also conquered the basics of deep learning with TensorFlow and Colaboratory. He had taken some basic programming classes in college, but wanted to learn Python and JavaScript to create something fun with emerging technology and share it with the community. It was two years ago when Sato started learning AI. When he realized that Asperger’s could be the reason that he wasn't able to fit well in those environments he tried something else entirely: artificial intelligence (AI). After spending some time unemployed, he tried a couple different career paths, including trying to attend nursing school and learning to become a baker. When Sato quit college in Tokyo 10 years ago, he didn't know he had Asperger syndrome. One million users are enjoying the tool everyday. It's confusing that we have similar names, but we are not the same person.ĪI Gahaku (AI master painter): built by Sato with Firebase, Cloud Run, and Google Colab. Editor's note: This is a post by Kaz Sato from Google based on an interview with Sato an individual developer.
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