Simon Karlsson
Simon Karlsson
Hi @kohheekyung, sorry for the late answer. Image sizes are tricky since the layers in the models automatically add padding, as default behaviour by keras, which results in changes in...
Hi @Erfandarzi, I would suggest using the keras function model.load_weights("path_to_weights") before line 239, and maybe force the correct epoch number to start on
Hi @fdcqqqq, I believe both errors come från the same problem. Since our reasearch never handled .tif images the load_data.py does not handle them. To fix this, modify on row...
Hi @fdcqqqq, In our research we used 16 bit .png images of the size 304x256 pixels with one channel.
It could perhaps be a normalization error. Look at the values in the resulting image and try to draw conclusions. Maybe multiply the whole image with 255?
I simply meant to scale and translate your output to the expected values the image viewer you are using wants. I guess between 0-255 are common so perhaps try that.
Hi @hala3, The Keras version used was 2.1.2 and I believe the lastest Keras-contrib version should work.
Try doing as the error suggests and change the function _keep_dims_ to _keepdims_. Changing the image size should not be a problem. Not all sizes will work though since the...
Hi @hamyadkiani, @fdcqqqq Seemed to figure it out, what was your solution @fdcqqqq?
Hi @manvirvirk, sorry for the late answer. I believe it has something to do with keras version. Check if 'Container' perhaps has depricated from keras.engine.topology