This repository hosts the code for TinyissimoYOLO and DSORT-MCU as presented in Ultra-Efficient On-Device Object Detection on AI-Integrated Smart Glasses with TinyissimoYOLO and DSORT-MCU: Detecting Small Objects in Real Time on MCUs.
Ultra-Efficient On-Device Object Detection on AI-Integrated Smart Glasses with TinyissimoYOLO
Julian Moosmann* 1,
Pietro Bonazzi*1,
Yawei Li1,
Sizhen Bian 1,
Philipp Mayer1 ,
Luca Benini 1 ,
Michele Magno1
1 ETH Zurich, Switzerland
For more details on how to train TinyissimoYOLO models, follow this guide.
DSORT-MCU is a framework for training and running models with improved detection performance on small objects that does not increase memory footprint and thus enables detection on resource constrained platforms.
DSORT-MCU: Detecting Small Objects in Real Time on MCUs
Liam Boyle 1,
Julian Moosmann1,
Nicolas Baumann 1,
Seonyeong Heo2 ,
Michele Magno1
1 ETH Zurich, Switzerland
2 Kyung Hee University, Republic of Korea
For a guide on how to train models with the adaptive tiling presented in DSORT-MCU follow these instructions.