RapidLib is a lightweight library for interactive machine learning. It currently features classification (using kNN), regression (multilayer perceptron), and series classification (using dynamic time warping).
More at: https://mzed.github.io/RapidLib/
Bela is a platform for ultra-low latency audio and sensor processing.
See Releases.
- Requires "experimental" Bela image with recent CMake: https://github.com/BelaPlatform/bela-image-builder/releases/tag/v0.5.0alpha2.
- Highly recommended to install
distcc
(guide). git clone
RapidLib onto Bela (connecting to network on Bela)- Comment out DTW multi-threading test (see mzed#20).
- Build commands from inside
RapidLib
dir:
mkdir build && cd build
CC="distcc-clang" CXX="distcc-clang++" cmake -DCMAKE_CXX_FLAGS="-Werror" ..
CC="distcc-clang" CXX="distcc-clang++" cmake
ctest
- Run
ldconfig /root/RapidLib/build
to add the binary path to the linker cache.
include "rapidLib.h"
make
parameters for RapidLib projects (see Bela Blog):
LDFLAGS=-L/root/RapidLib/build;LDLIBS=-lrapidLib;CPPFLAGS=-I/root/RapidLib/src;
Currently very simple, based on https://github.com/mzed/ofxRapidLib
- Benchmark RapidLib performance on Bela
- Add C++ examples using
AuxiliaryTask
- Add C++ examples using sensor inputs and audio outputs
- Add C++ examples with Bela GUIs
- Add
install
to CMake to simplify installation - Scope out SuperCollider / Pure Data support and examples