Hi @thomelane
Thank you for clarification. I am trying to do object detection for printed text, hence all my objects have fixed vertical size but variable horizontal size.
Using the tutorial I came up with varying size of bounding boxes that have fixed vertical size and variable horizontal size.
I have followed same tutorial, in my case I see decline in the classification loss but my L1 loss (for bounding box prediction) some how doesn’t reduce after certain point. Surprising factor is that L1 loss is as low as 0.000x since starting point which doesn’t make sense.
And all bounding boxes that are produces by MultiboxTarget somehow has same starting point which is left top of the page and variable vertical size output. For visualization purpose please see my this question. I have illustrated my loss fucntion graph and sample result of produced by my network after 100 epoch
So what I am trying to do is debug this issue. And one question that came naturally was that why is it producing vertical box, your explanation is clear but output result is very strange and it doesn’t go with the intuition of learning horizontal boxes.