Object Detection and Tracking with Convolutional Neural Network

Let me clarify a bit about my project for better understanding. It's a project about object detection, classification, and tracking using Convolutional Neural Network. The project is already done and working fine. The method used in my project is Single Shot Detector(SSD) and language is C++ using OpenCV library. For trained data, Caffe has been used as a deep neural framework. I would like to know how the trained data has been created from the dataset and explain to me step by step. The trained data and data model can be downloaded from the following link. [login to view URL] These are named by "[login to view URL]" and "[login to view URL]"