This is an experimenting on how to generate photorealistic synthetic human faces using StyleGAN2-ADA. Here's the training result in a video format.

• Dataset: Flickr-Faces-HQ Dataset (FFHQ)

• ML Model: StyleGAN2-ada

• Environment: Google Colab Pro

To train the model, I used I used the first 6,000 images with 1K resolution. With the trained model, I applied the image projection into latent space. The result is a progression of synthetic faces that shares similar visual landmarks and features, and even the glasses, and hair style!

Exploring ML for Shoe Design using StyleGAN2-ADA. Here's the training result in video format.

• Dataset: Shoes dataset from Kaggle with 7,000 images

• ML Model: StyleGAN2-ada

• Environment: Google Colab Pro

My hypothesis that ML could be used to assist/ inspire the product design process using StyleGAN2 ML model. By projecting inspiration images to latent space, the following are results in video showing the meandering progression process.

First, using a regular shoes as the inspiration (left) to see what variation of the target images (right) the ML model could generate.

Let's try something different. How about a red fox?

What about a cat?