This repository contains an implementation of the Single-Shot Detector (SSD) model from scratch for object detection. The SSD model is a popular deep learning architecture used for efficiently detecting objects in images with a single forward pass.
The SSD model performs object detection by discretizing the output space of bounding boxes into a set of default boxes over different aspect ratios and scales per feature map location. The model predicts both the presence of object classes in those boxes and the shape offsets relative to the default boxes to better match the object shapes.
