This repository contains training scripts for the lightweight SSD-based face detector. The detector is based on the MobileNetV2 backbone and has a single SSD head with manually designed anchors. As a result, it has computational complexity 0.51 GMACs and 1.03 M of parameters.
The detection network model provides detection of 3 class objects: vehicle, pedestrian, non-vehicle (ex: bikes). This detector was trained on the data from crossroad cameras.
- Ubuntu* 16.04
- Python* 3.6
- PyTorch* 1.0.1
- OpenVINO™ 2019 R1 with Python API
- Create virtual environment and build mmdetection:
bash init_venv.sh
- Activate virtual environment:
. venv/bin/activate