Result is very worse followed by the ipynb file

[UpCoder]

Hi, I execute the cascaded_unet_inference.ipynb that doesn't report any questions, but the result is worse. The result of step1 is shown as follow:

Any one know the reason? Thank you very much

[fuentesdt]

@UpCoder i'm getting the same thing on ubuntu 16.04 with cpu only version. are you able to run it from the docker? with gpu?

[UpCoder]

No, I still not solve the problem. Then I train the model from scratch with tensorflow version. The segmentation of liver is acceptable, but the lesions's can be acceptable. I don't run it from the docker, I directly use the GPU server.

[fuentesdt]

thanks @mohamed-ezz

seems that you need to use the same caffe version from the docker:

root@maeda:/opt/caffe# cat .git/config [core] repositoryformatversion = 0 filemode = true bare = false logallrefupdates = true [remote "origin"] url = https://github.com/mohamed-ezz/caffe.git fetch = +refs/heads/:refs/remotes/origin/ [branch "master"] remote = origin merge = refs/heads/master [branch "jonlong"] remote = origin merge = refs/heads/jonlong root@maeda:/opt/caffe# git log commit 876e387a6d7f8974f68f42beacd3728b4fc92ff7 Author: Mohamed Ezz moh.ezz8@gmail.com Date: Thu Feb 18 01:24:04 2016 +0100

Add class weighting feature for softmax_loss layer

$ git clone https://github.com/mohamed-ezz/caffe.git caffe/docker $ cd caffe/docker; git branch docker 876e387a6d7f8974f68f42beacd3728b4fc92ff7 ; git checkout docker