Closed 2m closed 6 years ago
This is interesting. From your full log I don't see the feature extraction code part running (line 113-127 in neural_paint.lua
. Could you add some printing information in that part to ensure it has been executed?
I printed out #cnn
just before this loop
and it was 0
.
Could ypou try re-downloading the VGG_ILSVRC_19_layers_deploy.prototxt
and VGG_ILSVRC_19_layers.caffemodel
? The VGG_ILSVRC_19_layers.caffemodel
should have MD5 sum: b5c644beabd7cf06bdd9065cfd674c97
.
The caffemodel checksum seems to be fine:
➜ deep-painterly-harmonization git:(master) ✗ md5sum models/VGG_ILSVRC_19_layers.caffemodel
b5c644beabd7cf06bdd9065cfd674c97 models/VGG_ILSVRC_19_layers.caffemodel
I see. What about the file VGG_ILSVRC_19_layers_deploy.prototxt
: ccbbdda59210208be39f8974f5b5765e
?
If they also match, I suspect it to be the problem from loadcaffe
package. Can you run:
loadcaffe.load(params.proto_file, params.model_file, 'nn')
in CPU model after reinstalling it?
Thanks! Fujun
Yea, the prototxt also matches:
➜ deep-painterly-harmonization git:(master) ✗ md5sum models/VGG_ILSVRC_19_layers_deploy.prototxt
ccbbdda59210208be39f8974f5b5765e models/VGG_ILSVRC_19_layers_deploy.prototxt
Can you elaborate more on
in CPU model after reinstalling it?
I do not have much experiance with loadcaffe
. :)
Sorry. I mean re-installing loadcaffe using: luarocks install loadcaffe
and load the VGG19 in CPU mode.
I just ran this command on an ubuntu 16.04:
Based on your previous full log, it seems our libprotobuf
version might be different since mine prints the warning message. Are you using Mac OSX? I have only tested the code in ubuntu 16.04 LTS currently.
Can you call cnn:get(i)
after loading it? If so, a simple yet ugly workaround for this would be hardcoding the number of layers to 46 since VGG-19 is fixed.
I got same Issue.
I've checked md5checksum. I think loadcaffe does load models but it doesn't look like variable cnn has the data
Can you tell me any idea ?
It looks like #cnn is 0 so it doesn't goes into for statement at the line num166 and error occurs at line 144~
Please help me with this issue
What about replacing #cnn
with cnn:size()
or table.getn(cnn)
?
That was it! Now it works! Thank you very much for the hint.
I get
while trying to reproduce the results while folllowing the directions in the README.
Full logs: