Comments (4)
I've found the site where VGG-16 models weights file is accessible. The URL link is down below:
https://mega.nz/#!YU1FWJrA!O1ywiCS2IiOlUCtCpI6HTJOMrneN-Qdv3ywQP5poecM
Notice that in the vgg16.py file within the hed/model directory, the first line indicates the GitHub website where the similar code was inherited from. You can just get into the website, where cited
To use the VGG networks, the npy files for VGG16 NPY or VGG19 NPY has to be downloaded.
This is where I've found the URL link above.
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Hello! I am not able to access the link as it's insecure. Is there a parallel link through which it could be downloaded?
from holy-edge.
Hi,
I have the same problem:
"Failed to interpret file %s as a pickle" % repr(file))
OSError: Failed to interpret file 'vgg16.npy' as a pickle
could you guys update such file (vgg16.npy)
please
P.S. could I use this file instead of the vgg16.npy in the repo?
from holy-edge.
from holy-edge.
Related Issues (20)
- About Loss Function HOT 1
- cannot clone pre-trained model file HOT 3
- Wrong loss function HOT 2
- Dimension Mismatch HOT 2
- Training does not converge HOT 3
- Error setting up VGG-16 model, Failed to interpret file '/home/xxx/holy-edge/hed/models/vgg16.npy' as a pickle HOT 3
- test error
- This repository is over its data quota. Purchase more data packs to restore access HOT 2
- Could anyone can provide a pretrained model in google drive or baiduyun? HOT 2
- a question about weight decay?
- why the loss changes a little like the picture bllow
- Does anyone have problems with Permission denied when running code with gpu?
- This backport is for Python 2.7 only HOT 1
- How to use the output model with Tensorflow lite for Mobile HOT 1
- Does the optimizer work when the loss is not a tensor?
- Is it true that you didn't train the parameters of VGG16? HOT 2
- How to test and output my own single image using the pretrained model
- Checkpoint can't be downloaded due to data limit reached on git lfs HOT 3
- Reupload the pretrained model?
- Requirements list Tensorflow 2, but code is in Tensorflow 1
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