Closed emmanuelbernieri closed 6 years ago
however the output is a vector of 0 & 1 corresponding to inditifed taggs
Really? I'm using Sigmoid as an activation function in the output layer, so it can't be like that if you're using the result as it is.
Does the music file format has an importance ? I cannot analyse mp3 so I convert them into wav and then I analyse.
after preprocessing the audio input with librosa it gives me an output like that:
[[[ 0. 0. 0. ..., 0.04826343 0.05228163 0.05081845]]]
Yes, whatever the file format is, it should be decoded which you do when you're using librosa.load
.
even when I use the 1100103.clip.npy. The output of the prediction is still [0.....1]
I'm using
python 3.6 Keras 2.0.6 Tensorflow 1.3.0 Theano 0.9.0 Librosa 0.5.1
Please check out the keras version (and possibly others) as readme. I think the theano version was either 0.7 or 0.8 at the moment.
I'll try to set up exactly the same config as yours tomorrow and let you know the result
I didn't succeed in reproducing your result.
Do you have a docker for a demo ?
Kind regards
Emmanuel
Do you have a docker for a demo ?
No I don’t.
On 7Sep 2017, at 15:18, emmanuelbernieri notifications@github.com wrote:
I didn't succeed in reproducing your result.
Do you have a docker for a demo ?
Kind regards
Emmanuel
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thanks for everything i'll let you know when I find where the problem is
Hello again,
i've implemented the compact-cnn neural network however the output is a vector of 0 & 1 corresponding to inditifed taggs. Is it possible like in the CRNN to only have the dominant taggs like :
[('jazz', '0.444'), ('instrumental', '0.151'), ('folk', '0.103'), ('Hip-Hop', '0.103'), ('ambient', '0.077')]
Kind regards
Emmanuel