I am trying to SSD network on my own dataset. However, I keep getting boxloss to be 0. Classification loss is not 0. But only box loss is 0.
When my default anchors, labels and class_predictions go through MutliboxTarget, I get 0 for box_target, box_mask, and class_target.
I have tried lot of things
- Changed size of image
- Converted image from rectangular to sqare
- Tried with similar small dataset
- Random translation and others.
- Even passed some other dataset through my network (Where the network works fine and Multibox target returns some values apart from 0)
- Tried classifying on same dataset with 2 classes. (Background, Object)
- Let it run for long number of ephoces. (But still box loss is 0, class loss approaches 0 and eventually network gets converged only on class loss.
- Ensured that training_target function works fine (copy pasted the literal code from MXNet object detection module)
- Even tried it on small network with no body, still mutilbox target returns 0.]
- Played around with lots of different anchorsizes and ratios.
So my question is what could be wrong? What could be wrong with my dataset? Why does multibox target always return 0 for everything?
And what exactly does a multibox target function do?