Set of tools to create nn_tilde compatible models.
Project description
Build Instructions
macOS
Pre-built binaries are available in the release section of this repo.
- Download libtorch 1.10 (CPU) here and unzip it to a known directory
- Run the following commands:
git clone https://github.com/acids-ircam/nn_tilde --recursive
cd nn_tilde
mkdir build
cd build
cmake ../src/ -DCMAKE_PREFIX_PATH=/path/to/libtorch -DCMAKE_BUILD_TYPE=Release
make
- Copy the produced
.mxo
external inside~/Documents/Max 8/Packages/nn_tilde/externals/
Windows
- Download Libtorch 1.10 (CPU) and dependencies here and unzip to a known directory.
- Install Visual Studio and the C++ tools
- Run the following commands:
git clone https://github.com/acids-ircam/nn_tilde --recurse-submodules
cd nn_tilde
mkdir build
cd build
cmake . -S ..\src -DCMAKE_BUILD_TYPE:STRING=Release -G "<generator name of your Visual Studio version>" -A x64 -DTorch_DIR="<unzipped libtorch directory>\share\cmake\Torch"
cmake --build . --config Release
Use cmake --help
to find the generator name for your Visual Studio version
- Copy all the DLLs from
<unzipped libtorch directory>\lib
to the Max 7/8 installation directory, next toMax.exe
Raspberry Pi
While nn~ can be compiled and used on Raspberry Pi, you may have to consider using lighter deep learning models. We currently only support 64bit OS.
Install nn~ for PureData using
curl -s https://raw.githubusercontent.com/acids-ircam/nn_tilde/master/install/raspberrypi.sh | bash
Project details
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