Hi,
I’ve been recently trying to implement UNet using PyTorch. You can find the implementation here 25
I’m encountering a so weird problem here!
The networks apparently converges (reduction in loss value) but when I start to inference on some query images (from training set), the output is very poor, more often blank image. I’m using Sigmoid/BCELos() and Adam optimiser. The data and other stuff have been examined to be as what expected.
On the other hand, I have a successful implementation of UNet using theano, and I tried my best to keep the training procedure of two networks all the same (e.g. fixed training set, fixed hyper-parameters and so on), but very poor performance with Pytorch!
Others have also shared the same issue with their implementations! like this
I do not see any other reason for poor performance except bugs with PyTorch backends!!
Do you guys have any comment on the implementation?
Thanks
Saeed