That's strange with [neuralnet~]. Do you have the respective binary?
@joao : did you add neuralnet to your paths? i'm just checking since i experienced exactly this: since the [neuralnet] is named like the library path, Pd finds it without a specific path. that's not the case for [neuralnet~] though.
cheers, ben
On Tue, Sep 17, 2024 at 9:26 AM Alexandros Drymonitis adrcki@gmail.com wrote:
Damn, I have the [omniFilter_abs~] there too? I missed that. You can get it here https://github.com/alexdrymonitis/filter_abstractions
The [command] object is a replacement of [shell]. If I'm not mistaken, it doesn't work on Windows. You don't necessarily need it though, I use it to load training data, but I do provide trained models, so you can test them without needing to train them from scratch.
That's strange with [neuralnet~]. Do you have the respective binary?
On 9/17/24 10:22, João Pais wrote:
This abstraction is in the examples/abstractions directory. I just realised that I have my local osc_abs prepended to the abstraction name. Just remove that and it should load.
Ah yes - but then the omniFilter_abs~ is also not present. Also the [command] object isn't loaded, from which library does it come?
Strangely, on 06 and 07 examples, [neuralnet~ models/audio_autoencoder~ encoder] doesn't create, but [neuralnet models/audio_autoencoder~ encoder] does. (I'm on windows)
Well, using a neural network boils down to the training dataset that you'll assemble. Get as many input/output combinations as you can. Then you'll have to choose the right structure and activation and loss functions, plus optimizer (although, usually the latter is an Adam).
Your question is a bit vague, and explaining how to set up a neural network in an email is not an easy task. Especially for me, since I'm not an expert (even though I coded this library).
that's true. in this context, it would envolve getting a 1-(or 2-)dimensional data, and detecting a pattern over time (probably between 0.1 and 1.5 seconds).
Cheers
On 9/15/24 23:37, João Pais wrote:
Hi, is the patch osc_abs/fm_3 missing from the package?
I'm looking for a way to make a model for leapmotion to recognize gestures (coming from combinations of xyz or velocity vectores for each finger, for example). Would you advise using this library for this?
Best,
JOao
[neuralnet] update! Version 0.3 has just been released!
New activation functions added Access to the internal structure of a trained network (e.g. the latent space) Storing weights and biases during training for visualization Save models during training Signal-rate version of the object! Audio autoencoder example added!
Binaries for Linux, Raspberry Pi 3,4,5, macOS, and Windows (thanks Ben Wesch for macOS and Windows) are available through deken. Souces are available on GitHub https://github.com/alexdrymonitis/neuralnet Thanks to Ben Wesch, Dan Wilcox, IOhannes m zmoelnig, Christof Ressi, and others!
Enjoy!
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