GlyphGAN — Exploring Typography with Generative Techniques

#pytorch #python #generativedesign #machinelearning2020

Generative font sample

A pytorch based deep convolutional GAN trained on glyphs. I have also created an Open Frameworks script that generates a dataset from all fonts installed on your Mac.

Generative typography merges technical prowess with artistic expression, utilizing algorithms and machine learning to create unique and dynamic typographic designs. It breaks free from traditional constraints, generating original letterforms beyond pre-existing fonts.
By leveraging AI and machine learning, designers can experiment with vast datasets and complex algorithms to craft dynamic typographic compositions that evolve and surprise.

This convergence of art and technology pushes the boundaries of typographic design, sparking fresh insights at the intersection of creativity and algorithmic innovation. Generative typography fosters collaboration and democratizes design through the sharing of models and open-source frameworks, nurturing a vibrant community of typographic explorers. It represents an exciting frontier that empowers designers to reshape visual communication with captivating and unconventional typographic forms.

Original architecture by Ritchie Vink, implemented by Aleksi Halttunen and Moritz Salla. The code is available here: Repository. The font scraping code is available here: Font Scraper.

Generative font sample

(c) 2023