This repository contains the code for person traing using SSD and centriod.
├── ckpt_ # Weight file
├── images # Images
├── input-data # Input data for detection.
├── Readme # Readme for Face-detection-SSD
├── requiremnts # Requirements file for Facenet-detection-SSD
Single-shot MultiBox Detector is a one-stage object detection algorithm. This means that, in contrast to two-stage models, SSDs do not need an initial object proposals generation step. This makes it, usually, faster and more efficient than two-stage approaches such as Faster R-CNN, although it sacrifices performance for detection of small objects to gain speed.
virtualenv --python=python3 env_fds
source env_fds/bin/activate
pip install -r requirements.txt
Single class object detection models will need less learnable features. Less parameters mean that the network will be smaller. Smaller networks run faster because it requires less computations.
