FPGA boards are a challenging environment for Deep Learning models. To fit the requirements, we came up with a highly optimized detection model with only 600 Kb of weights. Apart from bounding box prediction, it also computes a precise view-agnostic projection to the 2D floor map — that can be used to analyze space utilization.