Technologies: OpenCV, Yolo2/Faster RCNN / Mask R-CNN, COCO, Jetson Xavier

The aim of the project was to implement traffic counting (multiple object detection + tracking)  for installations placed in the countryside with low power consumption requirements.

Using background subtraction, deep neural networks and other methods we optimized the models to run on Jetson Xavier hardware platform meeting the clients’ requirements.

Significant part of the job was to adapt the computation environment to the hardware.