Comments (5)
Hi @jackyhkust,
thanks for downloading our code.
Have you checked the keras.json
file? It should be in the following format:
{ "image_dim_ordering": "th", "epsilon": 1e-07, "floatx": "float32", "backend": "theano" }
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hello @marcellacornia
I have similar issue but when i changed "image_dim_ordering": "th" in keras.json follow this :
{
"floatx": "float32",
"epsilon": 1e-07,
"backend": "theano",
"image_data_format": "channels_last",
"image_dim_ordering": "th"
}
i got this error :
Using Theano backend.
/home/nimol/venv3/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/nimol/venv3/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/nimol/venv3/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')
Compiling SAM-ResNet
Traceback (most recent call last):
File "main.py", line 119, in
raise NotImplementedError
NotImplementedError
My keras : 1.1.0 and theano 0.9
i am waiting your help .Thank you
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Hi @Thuonnimol,
thanks for downloading our code.
First, you have to remove "image_data_format": "channels_last"
from your keras.json
file.
The NotImplementedError
is probably due to a wrong parameter when running the code. For testing, the correct format is: python main.py test path/to/images/folder/
where path/to/images/folder/
is the path of a folder containing the images for which you want to calculate the saliency maps.
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hello @marcellacornia thank you for your answer .
Now,i will try
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Hello @marcellacornia now it's working ,thank you
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Related Issues (20)
- raise NotImplementedError HOT 2
- 'NoneType' object is not subscriptable HOT 2
- Why dose the "loss" reduce first and then increase during the training? HOT 1
- Support in TX2 HOT 2
- where is the prediction HOT 1
- train model HOT 3
- On the CPU HOT 1
- ImportError: cannot import name get_from_module HOT 1
- Error in virtual env HOT 1
- I met this error about CorrMM images and kernel must have the same stack size HOT 1
- Retraining the models
- how to calculate this fix and map
- Getting this IOError HOT 1
- Adapting different testing image shapes? HOT 1
- fix_map = scipy.io.loadmat(path)["I"] HOT 1
- How to learn the prior maps in your method?
- Is there a Pytorch version
- Outputs must be theano variables or Out instances
- cannot import name 'RMSprop' from 'keras.optimizers' HOT 2
- how to visualize the Saliency Maps?
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