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wav2mid's Issues

Numpy reshape error while training | ValueError: cannot reshape array of size 1362680 into shape (7,352)

Hello, I am now attempting to train a new model using a new dataset, and the code was running Well until I encountered this issue.
ValueError: cannot reshape array of size 1362680 into shape (7,352).

It was raised in readmm function from File "...AMT Projectswav2midpreprocess.py", line 26, and readmm was called from keras train.py in line 194
[ trainGen = DataGen(os.path.join(path,'data','train'),batch size,args) ]

if anyone can assist.
pls.

Pretty_midi error

Hello, we are trying to run the pre-processing code. We were previously able to run it.
However, suddenly we are getting an error like :
pretty_midi error
Basically, it seems like a fluidsynth import error.
Could you please suggest how to solve this issue? Thanks.

Memory Error in Preprocessing MAPS dataset

Hi Jon,

We were trying to run the MAPS dataset, with the preprocessing setup as in this repo.
However, we get an error called "memoryerror", in the np. concatenate call in lines -
inputs = np.concatenate(inputs)
outputs = np.concatenate(outputs)

Any suggestions would really help us .

Thanks a lot.

question in a comment

in the wav2input function of the preprocess file there's a comment that says:

IMPORTANT NOTE:

Since we pad the the spectrogram frame,

the onset frames are actually offset frames.

To obtain a window of the center frame at each true index, we take a slice from i to i+window_size

starting at frame 0 of the padded spectrogram

can you explain it to me, i don't understand it

thank you.

Wrong in Keras_train

In Keras_train.py line 192: DataGen (), and preprocess.py line 39.
There is nothing in the self.mmdirs. Just wondering what is suppose to be in the mmdir?

Nans in training

Hi Jon,

We are yet facing another issue. We have been able to proceed to the training part.
But the training loss is going to nan when the training data has "AkpnCGDd" data set in it. On removing it the training proceeds fine. When ran just by itself it runs fine. So we are unable to figure out what is causing this issue, if it is this data set or something else.

Any suggestions would be of great help. Thanks.

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