Allow training to succeed with negative images #102
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added 2 commits
January 7, 2016 22:47
Added an assert statement to ensure that there is at least one label and roi for the minibatch. If this is not the case, the training starts however results in a floating point error which doesn't give the clear cause. This situation can result from having images which are entirely negatives but not having TRAIN.BG_THRESH_LO set to zero.
Allows training to succeed when there are images present without any ground truth boxes. Previously, this failed due to merging empty matrices, argmax over empty matrices or the lack of an objective. This supercedes 75b3fd (Assert at least one label for training) which would pick up the lack of an objective.
This was referenced Mar 31, 2016
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Just put "sudo" before your comment, and if the problem still ,you can change number of batch. |
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When output the model result, it will get this error: |
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Oh, I find it is another error, since I have renamed |
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Allows training to succeed when there are images present without any ground
truth boxes. Previously, this failed due to merging empty matrices, argmax over
empty matrices or the lack of an objective.
This supercedes 75b3fd (Assert at least one label for training) which would
pick up the lack of an objective.