-
Notifications
You must be signed in to change notification settings - Fork 76
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
train model #32
Comments
Hi @Leila-sd, Our training code is compatible with images coming from the SALICON dataset, where both saliency density map and fixation map are provided for each image. The error you reported seems to be related to the lack of fixation maps. |
Thanks for your consideration. |
Hi
Based on the paper, I want to get the output from the first and second time
steps. But when I changed the time step variable in the source code, I did
not get the desired output. Conversely my expectation, the output does not
change. Do you have any idea about this problem?
Kind regards,
…On Tue, Jul 9, 2019 at 4:30 PM Marcella Cornia ***@***.***> wrote:
Hi @Leila-sd <https://github.com/Leila-sd>,
sorry for the late reply.
Our training code is compatible with images coming from the SALICON
dataset, where both saliency density map and fixation map are provided for
each image. The error you reported seems to be related to the lack of
fixation maps.
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub
<#32?email_source=notifications&email_token=AL5IQZ45PXEXWXMUMWUXR6DP6R4VVA5CNFSM4H4M2PB2YY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGODZQBMMA#issuecomment-509613616>,
or mute the thread
<https://github.com/notifications/unsubscribe-auth/AL5IQZ2F7ZCTEGZHMH4TJNTP6R4VVANCNFSM4H4M2PBQ>
.
|
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Hi, I successfully run it on the samples images using your pretrained model. Now i'm trying to retrain the models using your code but get this error:
Using Theano backend.
/home/kntu/anaconda3/lib/python3.6/site-packages/keras/backend/theano_backend.py:1282: UserWarning: DEPRECATION: the 'ds' parameter is not going to exist anymore as it is going to be replaced by the parameter 'ws'.
mode='max')
/home/kntu/anaconda3/lib/python3.6/site-packages/keras/backend/theano_backend.py:1282: UserWarning: DEPRECATION: the 'st' parameter is not going to exist anymore as it is going to be replaced by the parameter 'stride'.
mode='max')
/home/kntu/anaconda3/lib/python3.6/site-packages/keras/backend/theano_backend.py:1282: UserWarning: DEPRECATION: the 'padding' parameter is not going to exist anymore as it is going to be replaced by the parameter 'pad'.
mode='max')
/home/kntu/anaconda3/lib/python3.6/site-packages/h5py/init.py:36: FutureWarning: Conversion of the second argument of issubdtype from
float
tonp.floating
is deprecated. In future, it will be treated asnp.float64 == np.dtype(float).type
.from ._conv import register_converters as _register_converters
Compiling SAM-ResNet
Training SAM-ResNet
Epoch 1/10
Exception in thread Thread-1:
Traceback (most recent call last):
File "/home/kntu/anaconda3/lib/python3.6/threading.py", line 916, in _bootstrap_inner
self.run()
File "/home/kntu/anaconda3/lib/python3.6/threading.py", line 864, in run
self._target(*self._args, **self._kwargs)
File "/home/kntu/anaconda3/lib/python3.6/site-packages/keras/engine/training.py", line 425, in data_generator_task
generator_output = next(generator)
File "main.py", line 46, in generator
Y_fix = preprocess_fixmaps(fixs[counter:counter + b_s], shape_r_out, shape_c_out)
File "/home/kntu/LS/new_sam/sam-master/sam-master/utilities.py", line 106, in preprocess_fixmaps
fix_map = scipy.io.loadmat(path)["I"]
KeyError: 'I'
Traceback (most recent call last):
File "main.py", line 97, in
ModelCheckpoint('weights.sam-resnet.{epoch:02d}-{val_loss:.4f}.pkl', save_best_only=True)])
File "/home/kntu/anaconda3/lib/python3.6/site-packages/keras/engine/training.py", line 1417, in fit_generator
'or (x, y). Found: ' + str(generator_output))
Exception: output of generator should be a tuple (x, y, sample_weight) or (x, y). Found: None
thanks.
The text was updated successfully, but these errors were encountered: