Assignment 9

Heather Kim
Nov 4 · 2 min read

After slightly struggling with the Python and RNN, I found Runway much easier to use, as it has pre-trained models and the interface intuitive. Hopefully, I’ll get better at using Runway and use it for my final project!

As for this week’s assignment, I looked at StyleGan, which generates photorealistic images of faces, landscapes, and more. Searching for ways to how to use it, I came across the CodingTrain tutorial for using StyleGan.

Following the tutorial, I chose Cupcakes as my checkpoint and after running it, I was given a gallery of different cupcakes. I picked my favorite one:

I successfully ran it on my p5 web editor to generate different cupcake images whenever I press the “cupcake’ button. One shortcoming I realized is that the p5 won’t run or generate images if Runway is not running (it stops automatically??), just like how it works with p5 serial communication with Arduino. I have to continuously go back and forth to see if Runway is running.

This exercise, although it doesn’t have a lot of creative elements, was very helpful for me to familiarize myself with Runway.

I honestly prefer using Runway to ml5.js and python as I think there is a lot of space for creativity given that there are already pre-trained models. Overall, the terms used in the software are more straightforward (e.g. truncation, HTTP, etc.) than the terms used in neutral network such as epoch and normalizeData.

Intro to Machine Learning

Responses and documentations of work done in Into to Machine Learning Class

    Heather Kim

    Written by

    Intro to Machine Learning

    Responses and documentations of work done in Into to Machine Learning Class

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