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alfonsolink / tf_rfcn

experimental tensorflow implementation of R-FCN
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Training error. Too high accuracy after couple iterations. #4

Open vaklyuenkov opened 7 years ago

vaklyuenkov commented 7 years ago

Surprisingly high accuracy - more than 90% after only 100 iterations. The same picture on another datasets. It seems, that incorrectly calculated the loss and accuracy. Where may be mistake?

alfonsolink commented 7 years ago

anchor accuracy for rpn proposal network (object/non-object) is likely to get high fast to above 90 percent, but what should take longer is cls accuracy (or class prediction accuracy) -- at least for PASCAL VOC. I got cls accuracy to 90 + only after around 30k iterations

On 30 Nov 2016 14:59, "Klyuenkov Vladimir" notifications@github.com wrote:

Surprisingly high accuracy - more than 90% after only 100 iterations. The same picture on another datasets. It seems, that incorrectly calculated the loss and accuracy. Where may be mistake?

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vaklyuenkov commented 7 years ago

Sorry for bothering you, but i verify this out multiple times. How can it be, that in empty model (without any .ckpt loading) we have rcnn and rpn 90%+ accuracy on test set from first iterations? 1 If I look on results of model at demo, I can see that after thousands iterations accuracy of rpn isn't bed on my pictures, after 50 iterations - roi with best scores not even near goal gt, but as u can see on picture - accuracy , calculated in code, is not bad. Where can be error in calculating accuracy?

And the same can say about losses. bbox_losses starts from small values like 0.08, but on pictures we can see good bboxes only after thousand iterations.