Comments (4)
Hi, @sbordt! Thanks for the report. Are you running from source?
from keras-rcnn.
As far as I can tell, it does not generate enough positive examples during training, where every Anchor that has a IoU with a ground-truth bounding box of over 0.7 should be labelled as a positive example (as far as I understand Faster R-CNN).
You can find the code here:
from keras-rcnn.
Thanks for the quick reply!
I understand that it happens somewhere within these lines, but I must admit that I don't fully understand the code.
However I have created a small example that should work with the current master to illustrate the issue
https://gist.github.com/sbordt/58cc34c29fce54ffb8f114f605ea9f37
Shouldn't there be more positive examples (in blue) versus ground-truth bounding boxes (in red)?
from keras-rcnn.
@sbordt Hi,I'm very sorry to bother you, but I really can't see how this library is used. I've been learning RCNN recently and hope to learn from a source code, but I can't see the structure of the library at all, even the questions you ask is strange for me. For example, where is the content of the RPN your are training ? I didn't find it in the repository.
from keras-rcnn.
Related Issues (20)
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- Generator limits image pixel range 0 to 1
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from keras-rcnn.