keunwoochoi/auralisation

Auralisation of learned features in CNN (for audio)

auralisation's Issues

Switched Pooling

Hi keunwoochoi, thank for this tool it works great on your network! :)

I wonder how I can get this tool to work with a network that I will define and train myself :

• get_unpooling2d(images, switches, ds=2) takes the argument switches, I guess it's from a custom MaxPooling2D function, am I right? If not, which function did you use in your CNN and where can I find it?

• Is the code generic and can easily generalize to other CNN architecture? Some functions look quite specific ( load_weights() for example, but could be easy to change)

• What is the structure of the file .keras? Is it enough if I save a model in the HDF5 format?

Thank you in advance :)

PS : If you could give a concrete example on how to use it with another model it would be so great but I would understand if you don't want to reveal your custom function.

KeyError: "Unable to open object (object 'param_0' doesn't exist)"

Hello @keunwoochoi @mpariente
While loading weights from .keras file giving me this error. Can anyone help me with this?

Traceback (most recent call last):
File "example.py", line 33, in
W, layer_names = auralise.load_weights()
File "D:\MP_ASR\Auralisation-master\auralise.py", line 175, in load_weights
print(f[key]['param_0'][:,:,:,:])
File "h5py_objects.pyx", line 54, in h5py._objects.with_phil.wrapper
File "h5py_objects.pyx", line 55, in h5py._objects.with_phil.wrapper
File "C:\Users\Jeet\Anaconda3\lib\site-packages\h5py_hl\group.py", line 264, in getitem
oid = h5o.open(self.id, self._e(name), lapl=self._lapl)
File "h5py_objects.pyx", line 54, in h5py._objects.with_phil.wrapper
File "h5py_objects.pyx", line 55, in h5py._objects.with_phil.wrapper
File "h5py\h5o.pyx", line 190, in h5py.h5o.open
KeyError: "Unable to open object (object 'param_0' doesn't exist)"

Thanks in advance.

Bias values of the model

import h5py
model_name = "vggnet5"
keras_filename = "vggnet5_local_keras_model_CNN_stft_11_frame_173_freq_257_folding_0_best.keras"

f = h5py.File(keras_filename)

In auralise.py, I only use param_0, which is weights. Bias values are in param_1

>>> f['layer_3']['param_0']
<HDF5 dataset "param_0": shape (64, 64, 3, 3), type "<f4">
>>> f['layer_3']['param_1']
<HDF5 dataset "param_1": shape (64,), type "<f4">