All Projects → GuitarML → Chameleon

GuitarML / Chameleon

Licence: GPL-3.0 license
Vintage guitar amp using neural networks.

Programming Languages

C++
36643 projects - #6 most used programming language
shell
77523 projects
Inno Setup
370 projects
CMake
9771 projects
python
139335 projects - #7 most used programming language

Projects that are alternatives of or similar to Chameleon

pi-stomp
pi-stomp is a DIY high definition, multi-effects stompbox platform for guitar, bass and keyboards
Stars: ✭ 42 (-14.29%)
Mutual labels:  guitar
guitar-tabs-to-MIDI
A program that converts Guitar Tabs into MIDI files.
Stars: ✭ 38 (-22.45%)
Mutual labels:  guitar
Anomaly Detection
anomaly detection with anomalize and Google Trends data
Stars: ✭ 38 (-22.45%)
Mutual labels:  machinelearning
Rethink-BiasVariance-Tradeoff
Rethinking Bias-Variance Trade-off for Generalization of Neural Networks
Stars: ✭ 46 (-6.12%)
Mutual labels:  machinelearning
fretonator
The ultimate interactive free guitar theory tool.
Stars: ✭ 42 (-14.29%)
Mutual labels:  guitar
word2vec-tsne
Google News and Leo Tolstoy: Visualizing Word2Vec Word Embeddings using t-SNE.
Stars: ✭ 59 (+20.41%)
Mutual labels:  machinelearning
awesome-open-mlops
The Fuzzy Labs guide to the universe of open source MLOps
Stars: ✭ 304 (+520.41%)
Mutual labels:  machinelearning
soundshed-app
Desktop app to browse and manage guitar amp tones. Control your bluetooth amp, jam to video backing tracks.
Stars: ✭ 36 (-26.53%)
Mutual labels:  guitar
mlf-core
CPU and GPU deterministic and therefore fully reproducible machine learning pipelines using MLflow.
Stars: ✭ 32 (-34.69%)
Mutual labels:  machinelearning
ml-time-series-analysis-on-sales-data
Time Series Decomposition techniques and random forest algorithm on sales data
Stars: ✭ 34 (-30.61%)
Mutual labels:  machinelearning
dst
yet another custom data science template via cookiecutter
Stars: ✭ 59 (+20.41%)
Mutual labels:  machinelearning
Nutshell-Machine-Learning
This is a repository built by the community for the community.
Stars: ✭ 77 (+57.14%)
Mutual labels:  machinelearning
MarzWorkbench
FreeCAD Workbench for guitar design
Stars: ✭ 40 (-18.37%)
Mutual labels:  guitar
human-in-the-loop-machine-learning-tool-tornado
Tornado is a human-in-the-loop machine learning framework that helps you exploit your unlabelled data to train models through a simple and easy to use web interface.
Stars: ✭ 37 (-24.49%)
Mutual labels:  machinelearning
tablecloth
Dataset manipulation library built on the top of tech.ml.dataset
Stars: ✭ 167 (+240.82%)
Mutual labels:  machinelearning
practicesharp
A playback practice tool for musicians that allows slowing down, changing pitch, defining presets and loops on music files.
Stars: ✭ 27 (-44.9%)
Mutual labels:  guitar
juce-cookbook
Collection of tutorials & resources for the C++ library JUCE
Stars: ✭ 58 (+18.37%)
Mutual labels:  juce-framework
Lemons
A library of utilities and building blocks for JUCE-based apps and plugins
Stars: ✭ 28 (-42.86%)
Mutual labels:  juce-framework
Forecasting-Solar-Energy
Forecasting Solar Power: Analysis of using a LSTM Neural Network
Stars: ✭ 23 (-53.06%)
Mutual labels:  machinelearning
artificial neural networks
A collection of Methods and Models for various architectures of Artificial Neural Networks
Stars: ✭ 40 (-18.37%)
Mutual labels:  machinelearning

Chameleon

CI License: GPL v3 Downloads

app

Chameleon is a guitar plugin using neural networks to create three distinct sounds from a vintage style amp head. EQ and gain were added to allow further modification of the three core sounds, named Red (high gain), Gold (crunchy), and Green (crisp and clean). In the same way a real amp head is used with a cabinet and other effects, this plugin is intended to be used in the signal chain along with IR's (cab sim), reverb, and any number of guitar effects.

Chameleon's core sound comes from a neural net inference engine which allows the plugin to disguise itself as a high end tube amplifier. The engine uses a stateful LSTM model, which improves the sound quality of the previous stateless LSTM used in the SmartAmpPro. It also improves CPU usage compared to the SmartAmpPro and SmartGuitarAmp.

Check out sound demos on YouTube: Heavy Demo, Funky Demo
Check out the tech article on Towards Data Science

Chameleon is part of the 2021 KVR Audio Developer Challenge

Installing the plugin

  1. Download the appropriate plugin installer (Windows, Mac)
  2. Run the installer and follow the instructions. May need to reboot to allow your DAW to recognize the new plugin.

Info

Re-creation of the LSTM inference model from Real-Time Guitar Amplifier Emulation with Deep Learning

The Automated-GuitarAmpModelling project was used to train the .json models.
GuitarML maintains a fork with a few extra helpful features, including a Colab training script.

The plugin uses RTNeural, which is a highly optimized neural net inference engine intended for audio applications.

Swapping Models

Even though Chameleon is intended to have three set models, it is easy to swap these for user created json models. Simply overwrite the "red.json", "gold.json", or "green.json" file with the user created model of the same name before running Chameleon. To reset to the originals, delete the custom model. The next time you run Chameleon, the original tones will be written to the tone directory.

The locations of the json tone files are:

Windows 10: C:/Users/<username>/Documents/GuitarML/Chameleon/tones
Mac:  /Users/<username>/Documents/GuitarML/Chameleon/tones

Note: NeuralPi json files are compatible with Chameleon. The LSTM layer of user-trained models must have a size of 20.

Build Instructions

Build with Cmake

# Clone the repository
$ git clone https://github.com/GuitarML/Chameleon.git
$ cd Chameleon

# initialize and set up submodules
$ git submodule update --init --recursive

# build with CMake
$ cmake -Bbuild
$ cmake --build build --config Release

The binaries will be located in Chameleon/build/Chameleon_artefacts/

Build with Projucer

  1. Clone or download this repository.
  2. Download and install JUCE This project uses the "Projucer" application from the JUCE website.
  3. Initialize and set up submodules git submodule update --init --recursive
  4. Open the Chameleon.jucer file and in the appropriate Exporter Header Search Path field, enter the appropriate include paths from the modules folder.
  5. Build Chameleon from the Juce Projucer application.

Note: Make sure to build in Release mode unless actually debugging. Debug mode will not keep up with real time playing.

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].