I used the same database to train model by fasterRCNN.
When I use resnet50 as the network, there comes a warning
'Invalid bounding boxes from 110 out of 477 training images were removed. The following rows in trainingData have invalid bounding box data' and
'Bounding boxes must be fully contained within their associated image and must have positive width and height.'
However, I don't meet this problem when use alexnet as the network.
I also check the bounding box in the list images, and guess may be some of the bounding box are lying the the boundary of the image.
So I pading the image by one pixel on each side and run again. But there still comes these warning but 74 out of 477 image were removed.
Because every time the training data were select randomly, I'm not sure if pading is helpful.
Is there some parameter should be modified in resnet50?
