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In the previous post we discussed the network structure and the prediction scheme of SSD. Now we move on to combine default boxes and the ground truth, so the quality of the prediction can be determined (and be improved via training). (Reminder: The SSD paper and the Pytorch implementation used in this post) Map Default Boxes to Coordinates On Input Images Parameters of default boxes for each feature map are pre-calculated and hard-coded in data/config.py: ...

Recently I’m trying to pick up PyTorch as well as some object detection deep learning algorithms. So to kill two birds with one stone, I decided to read the Single Shot MultiBox Detector paper along with one of the PyTorch implementation written by Max deGroot. Admittedly, I have some trouble understanding some ideas in the paper. After reading the implementation and scratching my head for a while, I think I figured out at least some parts of them. So the following is my notes on some confusing concept after my first and second pass of reading. ...