Coding Train Live 182: Introduction to RunwayML

TL;DR

Learn to use Runway software with the PoseNet model for skeletal tracking in real-time.

Transcript

I always forget I'm gonna do this this dot this dot this star this star song never forget the bits taught somebody composed that song for me hello and welcome to a very special summer edition of the coding train so I'm kind of on a little bit of a hiatus right now you might have heard me talk about where this very light content happening in July an... Read More

Key Insights

• 🏃 Runway software provides an intuitive interface for running machine learning models.
• 😶‍🌫️ PoseNet enables real-time skeletal tracking using Runway without cloud GPU credits.
• ❓ Tweaking model parameters like architecture and resolution can impact model performance.
• 🔬 OSC protocol facilitates communication between Runway and Processing for data exchange.
• 😑 Runway's pre-made examples in processing make it easy to integrate machine learning models into creative projects.
• 📚 Collaboration for creating a Runway processing library can enhance accessibility to a wider audience.
• 🪡 OSC library may need to be added manually in Processing for successful model communication.

Questions & Answers

Q: What is the PoseNet model used for?

PoseNet is a machine learning model designed for real-time skeletal tracking of one or more people.

Q: How can the architecture parameter affect the model's performance?

The architecture parameter in Runway can determine the size and accuracy of the model, with larger values resulting in larger layers for increased accuracy.

Q: How does Runway support communication with other software platforms?

Runway supports various network protocols like OSC for communication, allowing seamless integration with software like Processing for receiving model output.

Q: Is it possible to run PoseNet locally without using cloud GPU credits?

Yes, PoseNet can be run locally within Runway without consuming any cloud GPU credits, making it an efficient option for real-time skeletal tracking.

Summary & Key Takeaways

• Introduction to Runway software for machine learning.

• Using the PoseNet model for real-time skeletal tracking.

• Configuring parameters and obtaining results in Processing.