Pre-trained model(Imagenet) results

[kaminocode]

I reproduced the result on the ring image using the pretrained model on imagenet. Since the image is 640 x 480, the last 32 pixels where left out. Still the image doesn't seem to match with result shown on the paper.

Further the patches are very much visible. Do you do some kind of post processing after stitching the 64 x 64 images?

[kaminocode]

Further on this particular image the results are poor. How should I change the alpha parameter if I'm using the pretrained model on imagenet?

[githublzb]

when I run paper_demo.py, there was an error:
Traceback (most recent call last):
File "/home/GithubDown/OneNet/admm/paper_demo.py", line 432, in
testset_filelist = load_data.load_testset_path_list()
File "../projector/load_celeb.py", line 74, in load_testset_path_list
return load_testset_path()['image_path'].tolist()
AttributeError: 'list' object has no attribute 'tolist'
How do I overcome this?
Thanks ahead.