You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
{{ message }}
This repository has been archived by the owner on Sep 16, 2024. It is now read-only.
When I tried to use the converted model like "model.ckpt-init" or "model.ckpt-pretrained", I met the following error:
Traceback (most recent call last):
File "/home/wxy/Proj/test.py", line 21, in
model = DeepLFOV(weights_path)
......
File "/home/wxy/Proj/test.py", line 53, in _create_variable
weights = cPickle.load(f) # load pre-trained weights
EOFError
The text was updated successfully, but these errors were encountered:
I have tried several times in a separate script using two computer, but I still got the EOFError,
And when I used the "vim" command to edit the file, I see [incomplete last line] [converted]. So I add a line break into the file, it still didn't work.
Sorry for misleading you - the docs have not been updated in a while: there are two ways of restoring weights, one is via the weights_path and another via restore_from. The weights_path loads the file using the pickle mechanism (after converting the weigths from Caffe), while restore_from uses the inner TensorFlow format. Now, the files that are provided are already in the TensorFlow format, so you do not need to pass the weights_path variable at all, just restore_from.
Let me know if you have any more questions
Sign up for freeto subscribe to this conversation on GitHub.
Already have an account?
Sign in.
When I tried to use the converted model like "model.ckpt-init" or "model.ckpt-pretrained", I met the following error:
Traceback (most recent call last):
File "/home/wxy/Proj/test.py", line 21, in
model = DeepLFOV(weights_path)
......
File "/home/wxy/Proj/test.py", line 53, in _create_variable
weights = cPickle.load(f) # load pre-trained weights
EOFError
The text was updated successfully, but these errors were encountered: