Using Gaming Datasets for Game Automation with Computer Vision
Blog post from Roboflow
The blog post by Ananth Vivekanand explores the application of computer vision in gaming, specifically within Minecraft, using the Roboflow platform. It details the process of using Roboflow to create a computer vision model that detects tree trunks in Minecraft by annotating images, applying data augmentation, and training the model. The author demonstrates how to use OBS Studio to stream the game as a virtual webcam, allowing the model to perform real-time object detection using the infer-async.py script. The article illustrates the potential for extending computer vision applications to other desktop games or applications and highlights the use of automation tools like autohotkey or Hammerspoon to programmatically control games. The post also references a related paper by OpenAI on using general computer-using agents, encouraging readers to explore further developments in the field.