Using Computer Vision to Win at Duck Hunt

Abhinav Mandava, a Master of Applied Computer Science student, explores the use of computer vision to create an aimbot for the classic video game Duck Hunt, leveraging object detection models and Roboflow. By gathering and annotating 253 screenshots of gameplay, Mandava used tools like the EfficientDet-D0 model and TensorFlow Object Detection API, despite initial challenges with misidentifying the crosshair as a duck. The project highlights the potential of computer vision not just in gaming, but also in automating everyday tasks like identifying a mouse cursor on a screen. Mandava praises Roboflow’s user experience and model library, expressing enthusiasm for future projects in the field.