Inspiration

One of our team members read about Generative Adversarial Networks (GAN) in his research seminar, so we looked for a new domain to apply GANs to. We decided to pursue creating logos because the training files were easy to obtain, and the website would be useful, as thousands of start-ups are created everyday that want to find a logo design.

What it does

From a bunch of existing company logos, a model is built that can assemble pieces of the existing logos together. The output of the model is loaded onto a website when a user requests to see more logo designs.

How I built it

The GAN network was taken from https://github.com/carpedm20/DCGAN-tensorflow. This originally ran on face data, and we modified the code and data parameters so the algorithm worked for logos.

Challenges I ran into

Fixing some bugs of the pre-existing GAN software.

Accomplishments that I'm proud of

Getting the GAN to run. Polishing GAN outputs with Paint.net for clearer visualization and as a demonstration of moving from logo prototype to possible actual logo.

What I learned

Git branching and GAN implementation in Python.

What's next for Logo GANerator

Generate logos based on user keywords.

Built With

Share this project:

Updates