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@@ -13,10 +13,54 @@ Download:&nbsp;<a href='https://rerdavies.github.io/pipedal/download.html'>v2.0.
Website:&nbsp;[https://rerdavies.github.io/pipedal](https://rerdavies.github.io/pipedal).
Documentation:&nbsp;[https://rerdavies.github.io/pipedal/Documentation.html](https://rerdavies.github.io/pipedal/Documentation.html).
#### Announcing PiPedal 2.0 (2.0.103). See the [documentation](https://rerdavies.github.io/pipedal/PiPedal2.html) for information, and instructions on how to install Pipedal 2.0. New features include support for Neural Amp Modeler A2 models, integration with Tone3000.com services for easy downloading of Neural Amp Modeler A2 models and IIRs, a new Channel Routing dialog for global routing of auxiliary input channels, and unprocessed re-amp output channels, and many other minor features, improvements, and bug fixes. Pipedal 2.0 also adds support for running PiPedal as a Progressive Web Application (PWA), which allows you to launch Pipedal from your desktop as a native desktop application. (A nice feature if you are accessing Pipedal from an Apple device). See the [documentation](https://rerdavies.github.io/pipedal/PiPedal2.html) for instructions on how to install Pipedal on your desktop as a standalone app.
#### Announcing PiPedal 2.0 (2.0.103)&mdash;a major update to PiPedal, including big new features. See the [documentation](https://rerdavies.github.io/pipedal/PiPedal.html) for information, and instructions on how to install Pipedal 2.0.
&nbsp;
_To download PiPedal v2.0.102, click [*here*](download.md).
To view PiPedal documentation, click [*here*](Documentation.md)._
Use your Raspberry Pi, or Ubuntu amd/x86-64 computer as a guitar effects pedal. Configure and control PiPedal remotedly, with your phone or tablet, or via a web browser.
PiPedal running on a Raspberry Pi 4 or Pi 5 provides stable super-low-latency audio via external USB audio devices, or internal Raspberry Pi audio hats.
PiPedal runs on Raspbery Pi OS (Bookworm or Trixie), or Ubuntu 24.x or later (amd64/x86-64 and aarch64). Make sure you follow the [Ubuntu post-install
instructions](https://rerdavies.github.io/pipedal/Configuring.html) to make sure your Ubuntu OS is using a realtime-capable kernel.
{% include gallery.html %}
New in PiPedal v2.0:
- Support for Neural Amp Modeler (NAM) A2 models.
- Direct single-step downloads of NAM A2 models to the Pipedal server using web services provided by <a href="https://tone3000.com/">Tone3000.com</a>.
- Install PiPedal as a Progressive Web App (PWA) on your Windows or Apple desktop or laptop in order to run PiPedal as a native application, without the clutter of browser chrome, address bars, and needless decorations.
- A new Channel Routing dialog which allows you to pass through Auxilliary audio channels, or unprocessed guitar inputs for later re-amping in a DAW or external hardware.
- New NAM A2-based Factory Presets, and a small selection of NAM A2 models pre-installed and ready to use.
PiPedal includes state-of-the-art AI-based guitar amp emulation, using the TooB Neural Amp Modeler technology. And PiPedal 2.0 now includes support for the brand new NAM A2 technology, which provides event more accurate amp simulations than NAM A1, while using even less CPU. Experience the ground-breaking quality of NAM A2 models now, with PiPedal's low-latency audio engine running on your Raspberry Pi or Ubuntu computer.
NAM changes everything! The quality of NAM A1 and A2 models is better than than amp emulations on top-of-the-line commercial guitar stomp boxes costing thousands of dollars. Simulations that not only sound like the real thing, but also respond to your playing dynamics in the same way as the real amp.
PiPedal 2.0 integrates with Tone3000.com's web services, allowing you to directly install new NAM A2 models on the pipedal server without ever leaving the PiPedal user interface. Or download and install commercially-developed NAM models from a rich ecosystem of model providers.
{% include demo.html %}
PiPedal can be remotely controlled via a web interface over Ethernet, or Wi-Fi. If you don't have access to a Wi-Fi router, PiPedal can be configured to
start a Wi-Fi hotspot automatically, whenever your Raspberry Pi can't connect to your home network.
Install the [PiPedal Remote Android app](https://play.google.com/store/apps/details?id=com.twoplay.pipedal) to get one-click access to PiPedal via Wi-Fi networks, or Wi-Fi hotspots. If you are using PiPedal away from home, you can configure PiPedal to automatically start a Wi-Fi hotspot whenever Pipedal is unable to detect your home network (Raspberry Pi OS only). The PiPedal Client Android app will allow to connect by simply launching the app, whether you are at home, or using a Wi-Fi auto-hotspot at a gig, when away from home.
PiPedal's user interface has been specifically designed to work well on small form-factor touch devices like phones or tablets. Clip a phone or tablet on your microphone stand on stage, and you're ready to play! Or connect via a desktop browser, for a slightly more luxurious experience. The PiPedal user-interface adapts to the screen size and orientation of your device, providing easy control of your guitar effects across a broad variety devices and screen sizes.
PiPedal includes a pre-installed selection of LV2 plugins from the ToobAmp collection of plugins; but it works with most LV2 Audio plugins. There are literally hundreds of free high-quality LV2 audio plugins that will work with PiPedal. Just install them on your Raspberry Pi, and they will show up in PiPedal.
If your USB audio adapter has MIDI connectors, you can use MIDI devices (keyboards, controllers, or midi floor boards) to control PiPedal while performing. A simple interface allows you to select how you would like to bind PiPedal controls to midi messages.
##################################################################################################
Use your Raspberry Pi as a guitar effects pedal. Configure and control PiPedal using a remote web browsers, from your phone or tablet.
PiPedal running on a Raspberry Pi 4 or Pi 5 provides stable super-low-latency audio via external USB audio devices, or internal Raspberry Pi audio hats. 
@@ -36,7 +80,7 @@ If your USB audio adapter has MIDI connectors, you can use MIDI devices (keyboar
<img src="docs/gallery/dark-sshot1.png"></img>
<img src="docs/gallery/rig.jpg" width="45%"></img> <img src="docs/gallery/jazz.png" width="45%"></img> <img src="docs/gallery/thunder.png" width="45%"></img> <img src="docs/gallery/midi-bindings.png" width="45%"></img> <img src="docs/gallery/hotspot.png" width="45%"></img>
<img src="docs/gallery/nam_models.png" width="45%"></img> <img src="docs/gallery/hotspot.png" width="45%"></img> <img src="docs/gallery/tuner.png" width="45%"></img><img src="docs/gallery/rig.jpg" width="45%"></img>
@@ -46,42 +90,46 @@ https://github.com/user-attachments/assets/9a9fd0c6-78fc-4284-8b44-6a1929c00cc6
----
&nbsp;
### [What PiPedal Is](https://rerdavies.github.io/pipedal/AboutPiPedal.html)
### [System Requirements](https://rerdavies.github.io/pipedal/SystemRequirements.html)
### [Installing PiPedal](https://rerdavies.github.io/pipedal/Installing.html)
### [PiPedal on Ubuntu](https://rerdavies.github.io/pipedal/Ubuntu.html)
#### [System Requirements](https://rerdavies.github.io/pipedal/SystemRequirements.html)
&nbsp;
### [Headless Operation](https://rerdavies.github.io/pipedal/HeadlessOperation.html)
### [Configuring PiPedal After Installation](https://rerdavies.github.io/pipedal/Configuring.html)
#### [Installing PiPedal](https://rerdavies.github.io/pipedal/Installing.html)
#### [Installing PiPedal on Ubuntu](https://rerdavies.github.io/pipedal/Ubuntu.html)
#### [Headless Operation](https://rerdavies.github.io/pipedal/HeadlessOperation.html)
#### [Configuring PiPedal After Installation](https://rerdavies.github.io/pipedal/Configuring.html)
&nbsp;
#### [What PiPedal Is](https://rerdavies.github.io/pipedal/WhatPiPedalIs.html)
#### [Machine Learning in PiPedal (A History)](https://rerdavies.github.io/pipedal/PiPedalHistory.html)
#### [How to Use PiPedal](https://rerdavies.github.io/pipedal/HowToUsePiPedal.html)
#### [How to Build Presets With PiPedal](https://rerdavies.github.io/pipedal/BuildingPresets.html)
#### [An Intro to Snapshots](https://rerdavies.github.io/pipedal/Snapshots.html)
#### [Neural Amp Modeler Calibration](https://rerdavies.github.io/pipedal/NamCalibration.html)
#### [Choosing a USB Audio Adapter](https://rerdavies.github.io/pipedal/ChoosingAUsbAudioAdapter.html)
#### [Optimizing Audio Latency](https://rerdavies.github.io/pipedal/AudioLatency.html)
#### [Command-Line Configuration of PiPedal](https://rerdavies.github.io/pipedal/CommandLine.html)
#### [Changing the Web Server Port](https://rerdavies.github.io/pipedal/ChangingTheWebServerPort.html)
&nbsp;
### [Using TooB Neural Amp Modeler](https://rerdavies.github.io/pipedal/UsingNAM.html)
### [An Intro to Snapshots](https://rerdavies.github.io/pipedal/Snapshots.html)
### [Choosing a USB Audio Adapter](https://rerdavies.github.io/pipedal/ChoosingAUsbAudioAdapter.html)
### [Optimizing Audio Latency](https://rerdavies.github.io/pipedal/AudioLatency.html)
### [Command-Line Configuration of PiPedal](https://rerdavies.github.io/pipedal/CommandLine.html)
### [Changing the Web Server Port](https://rerdavies.github.io/pipedal/ChangingTheWebServerPort.html)
#### [Using LV2 Audio Plugins](https://rerdavies.github.io/pipedal/UsingLv2Plugins.html)
#### [Which LV2 Plugins does PiPedal support?](https://rerdavies.github.io/pipedal/WhichLv2PluginsAreSupported.html)
#### [LV2 Plugins with MOD User Interfaces](https://rerdavies.github.io/pipedal/ModUiSupport.html)
&nbsp;
### [Using LV2 Audio Plugins](https://rerdavies.github.io/pipedal/UsingLv2Plugins.md)
### [Which LV2 Plugins does PiPedal support?](https://rerdavies.github.io/pipedal/WhichLv2PluginsAreSupported.html)
### [Support for LV2 Plugins with MOD User Interfaces](https://rerdavies.github.io/pipedal/ModUiSupport.html)
&nbsp;
### [Frequently Asked Questions](https://rerdavies.github.io/pipedal/FAQ.html)
&nbsp;
### [Building PiPedal from Source](https://rerdavies.github.io/pipedal/BuildingPiPedalFromSource.html)
### [Build Prerequisites](https://rerdavies.github.io/pipedal/BuildPrerequisites.html)
### [The Build System](https://rerdavies.github.io/pipedal/TheBuildSystem.html)
### [How to Debug PiPedal](https://rerdavies.github.io/pipedal/Debugging.html)
#### [Frequently Asked Questions](https://rerdavies.github.io/pipedal/FAQ.html)
&nbsp;
#### [Building PiPedal from Source](https://rerdavies.github.io/pipedal/BuildingPiPedalFromSource.html)
#### [Build Prerequisites](https://rerdavies.github.io/pipedal/BuildPrerequisites.html)
#### [The Build Systems](https://rerdavies.github.io/pipedal/TheBuildSystem.html)
#### [How to Debug PiPedal](https://rerdavies.github.io/pipedal/Debugging.html)
#### [PiPedal Architecture](https://rerdavies.github.io/pipedal/Architecture.html)
 
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---
page_icon: img/playbot.jpg
---
## What PiPedal Is
To get the most out of PiPedal, you need to understand a little about what's going on the world of Guitar effects and amp simulations.
### PiPedal and the Machine Learning Revolution
{% include pageIcon.html %}
Machine Learning (Artificial Intelligence) has changed everything.
In the world of guitar effect pedals, the revolution started in 2019 when Jatin Chowdhury published [a paper](https://arxiv.org/pdf/2106.03037) describing the results of using machine learning to simulate guitar amplifier effects in real-time. To put things in perspective, LLM AIs like ChatGPT have billions of parameters. Jatin was more interested in how well AI techniques worked if you used small Neural Net models with a few thousand parameters—models small enough to run in real-time. The answer was surprisingly positive: you can use small models and get impressive results. He then proceeded to publish his source code, both for the real-time simulations and the tools used to train his models, under an open-source MIT license. This has created an avalanche of innovation.
Jatin Chowdhury's ML library continues to exist and can be freely downloaded and incorporated into guitar effect plugins available in most formats. The ML library and model training tools remain substantially the same as Chowdhury's initial release. There are significant gains in quality if you double the size of the Neural Networks he used in the original versions. Most models for the ML library now use a larger model, and many have gone through significantly more training than Chowdhury's originals. The result? The models sound amazing! Amp simulations based on Chowdhury's ML library can run in real-time on an ordinary computer and produce emulations that sound significantly better than previous-generation amp emulations used by commercial stomp boxes costing over $1,000.
Community developers have incorporated the ML library into free, open-source guitar plugins that run on Windows, Mac, and Linux, available in most plugin formats (VST2, VST3, AU, RTAS, etc.). Recently, they've also been made available as LV2 plugins that run well in real-time with low latency on Raspberry Pi.
Steven D. Atkinson has since released the Neural Amp Modeler library, which traces its heritage to Chowdhury's ML library while providing support for a wider variety of Machine Learning algorithms. Amazingly, the Neural Amp Modeler library has also been released under an open-source MIT license and incorporated into plugins for most formats and major computing platforms.
Subsequently, a large open-source-minded community has devoted itself to training new Neural Net models for these libraries. The compute time required is substantial, typically requiring rented time on NVIDIA AI hardware in the cloud. Training models also requires access to the equipment being modeled. While the compute time isn't particularly expensive, it takes time and effort to record good source material and train the models, which is why a community effort is necessary. There are now hundreds of high-quality, free models for both libraries, covering everything from heavy metal amps to sublime Tweed emulations, distortion/overdrive/fuzz pedals, and even famous tube-based mixing board strips.
The quality is readily apparent and not a subtle improvement. These are amp simulations that not only sound exactly like what they're simulating but also play and feel like the amps they're emulating. We're talking about 5150 emulations that actually chug, Twin emulations with that sparkly chime that makes your ears itch, and 1962 Fender Bassman emulations with the warmth and forgiveness jazz players seek. (These qualities are not often found in previous-generation amp emulations).
So let's just to put all of that in perspective, because the results of all of that have huge implications for the music industry going forward. Jatin Chowdhury's machine learning experiment escaped from the lab in 2019, and has since taken over the world. You can use his code (and derivatives thereof) for free, in guitar plugins that are available on all major audio platforms and on all major hardware platforms, for free, and get access to a huge library of community-developed models for those plugins which are also free. All of which sound better than $1000+ stompboxes.
### So Where Does PiPedal Fit In?
And now you can plug in a USB audio adapter (not free, I'm afraid) into your Raspberry Pi (also not free, but very cheap), and run those incredible amp models in realtime with low latency using PiPedal (which is also free). That isn't entirely what PiPedal started off as. But at this particular moment in time, that's what PiPedal is.
And yes, all of the easy effects (reverb, delay, chorus, flangers, modulators, phasers, etc. etc. etc) are either included with PiPedal, or are available for free as LV2 plugins that can also be downloaded from the internet. And Machine Learning plugins also provide good emulations of overdrive, fuzz pedals and other distortion effects, so that's covered. And convolution reverb and cab IR effects aren't particularly easy, but once you've covered that, you pretty much have it all.
But the living heart and soul of a guitar stomp box is the amp emulations, and how good they are. On Pipedal, thanks to Jatin Chowdhury's escaped monster, they are very good indeed.
### What PiPedal Is
PiPedal is a guitar stomp box implementation that runs on a Raspberry Pi (or comparable x64 micro pcs). It provides a basic set of plugin to get you started, among are which are, notably, TooB ML (using Jatin Chowdhury's ML library) and TooB Neural Amp Modeler (using Steven Atkinson's Neural Amp Model library). PiPedal provides a basic set of LV2 plugins to get you started. Among those plugins are TooB ML (which uses the ML library), and TooB Neural Amp Modeler (which uses the Neural Amp Modeler library). PiPedal uses Linux-standard LV2 plugins, allowing you to download and install additional LV2 plugins as needed.
You access all of those plugins and configure them using PiPedal's web interface, which is important. GPUs and real-time audio effects do not get along well together. So if the user interface you use to control PiPedal is remote, it means that PiPedal can be configured to run with extraordinarily low latency, and use 80% or more of available CPU to run what really matters: guitar effects plugins. GPUs, by the way, are why you can't really ever get low latency on a laptop or PC. PiPedal lets you use your phone, or your tablet or maybe even your laptop to run the user interface, and let your Raspberry Pi concentrate on processing low-latency realtime audio.
Unlike most other audio host applications, PiPedal runs as a daemon, whether you're logged on or not. So all you have to do is plug in your Raspberry Pi, and play - no login required.
When you're playing away from home, PiPedal provides an auto-hotspot feature, which automatically brings up a Wi-Fi hotspot on your Raspberry Pi whenever Pipedal can't see your home router (or an ethernet connection, if that's how you connect to your Pi at home). So all you have to do when you're playing away from home, is power on your Raspberry Pi, pull out your phone or tablet or laptop, and you're all ready to go.
But most importantly PiPedal sounds great because it leverages the work of Jatin Chowdhury, and Steven D. Atkinson. And in the end, whether it sounds great is all that really matters. So please do spend some serious time with the TooB ML and TooB Neural Amp Modeler plugins.
That's what PiPedal is.
PiPedal doesn't come with a lot of models, or a lot of effects. It is a platform. The TooB ML plugins (included with Pipedal) includes Jatin Chowdhury's original amp models, which sound pretty good, but are nowhere near as good as current-generation models. So download some models for TooB ML. And TooB Neural Amp Modeler doesn't come with any models at all. So download some models for TooB NAM as well. And PiPedal comes with a very bare minimum set of LV2 effects, just to get you started. The plugins it does have are (I think) good and useful plugins. TooB Freeverb is there because Freeverb is my favorite goto reverb even in a world filled with convolution reverbs; a convolution reverb, because not everyone agrees; a good flanger (which sounds unreasonable fabulous in stereo); a sensible no-nonsense delay; a decent chorus; a couple of cab simulator effects and a few others. So if you'e looking for anything but bare basics, download some LV2 plugins as well.
--------
[Up](Documentation.md) | [Installing PiPedal >>](SystemRequirements.md)
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@@ -55,4 +55,4 @@ You may want to watch out for temperature throttling of the CPUs. PiPedal can be
My development system has both a heat sink, and a fan. The CPU temperature rarely goes above 60C.
--------
[<< System Requirements](ChoosingAUsbAudioAdapter.md) | [Up](Documentation.md) | [Command-Line Configuration of PiPedal >>](CommandLine.md)
[<< Choosing a USB Audio Adapter](ChoosingAUsbAudioAdapter.md) | [Up](Documentation.md) | [Command-Line Configuration of PiPedal >>](CommandLine.md)
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---
page_icon: img/BuildingPresets_thumb.png
---
## How to Build Presets with PiPedal
{% include pageIcon.html %}
PiPedal does not provide a lot of Factory Presets. You may be used to guitar stomp boxes that provide hundreds of factory
presets out of the box (most of which are mediocre, or even ridiculous, or are targeted at some genre that is not you at all).
PiPedal is not that. Instead, it provides a very small set of Factory Presets that are intended to either give you a quick taste of
the quality an and variety of NAM A2 models that are available, or to give you some ideas about how to build presets around NAM A2 models that you like.
Instead, the versatility of PiPedal revolves around the versatility of Neural Amp Model (NAM) models. TooB Neural Amp Modeler is the plugin that provides NAM emulations. Start by finding an amp model you like from the thousands of amp models available on Tone3000.com, and then wrap it with effects that you personally are going to use. PiPedal is not about 256 factory presets; it is about 11,000 stunningly good amp models, and the ability to build your own presets around those models.
In short, focus your attention on amp models, not presets.
First of all, start by picking an amp model that you like. Maybe a Fender amp for sparkling cleans, or famous Fender edge-of breakup tones; or a Marshall amp for classic rock and high-gain lead tones; or a Peavey 6505 for chugging metal tones. If you are
chasing the sound of a favorite artist, perhaps check to see what kind of amps they prefer.
If you have found an amp model that is close to what you want, you can often adjust amp models to better suit your needs by adding EQ plugins before or after the amp model (or of course, using the Tone knob on your guitar). TooB Parametric EQ is a good choice for this, because it provide a lot of flexibility for shaping tones. Or, if you find TooB Parameter EQ overwhelmingly complicated, TooB 3 Band EQ is a simpler (but still very useful) alternative. You can often get good results by scooping mid-range frequency response a bit, or boosting high-frequency response, depending on what kind of tone you are going for. If you start with a model that is close to what you want, you can often get exactly what you want with a tiny bit of EQ tweaking.
You should also pay particular attention to whether the amp simulation is a head-only simulation or a full amp simulation (which includes
modeling of the speaker cabinet). Head-only simulations will require you to add a speaker cabinet simulator after the amp model (or have an actual physical guitar cabinet in your signal chain) in order to get good sound. Head-only simulations are quite common on Tone3000, because they allow you to choose your own speaker cabinet independently. The Toob Cab IR plugin is a good choice for this (and also allows you to easily download Cab IR files from Tone3000.com).
Neural Amp Models can also be used to simulate guitar effects peadals as well. So if you have a favorite distortion pedal, or fuzz pedal, or overdrive pedal, you can probably find a NAM model of that pedal on Tone3000.com as well. Also worth considering are NAM emulations of
studio console mixing strips, which are particularly useful for warming up the tone of accoustic guitars, or for adding some extra warmth and character to electric guitar tones, and a good way to get Limiter effects as well, should you find that useful.
And if you are listening to the output of PiPedal through headphones, or small speakers at home, you will generally want to add
some amount of reverb as well, to get really pleasant tones. TooB Freeverb is a good choice for this, because it is a simple, no-nonsense reverb that sounds good, is easy to use, and provides relatively little signal coloration. But if you want a more lush, more colorful reverb, or are looking for creative reverb effects (bathrooms, big halls, plates reverbs, etc.), you can try convolution reverb with good impulse responses files. The TooB Convolution Reverb plugin is a good choice for this. PiPedal provides a very basic set of convolution reverb impulse files to get you started, but they are not intended to be a comprehensive library of reverb impulse responses. Unfortunately, Tone3000 does not provide convolution reverb impulse response files yet; but there are many sources of
free and commercial convolution reverb impulse response files available on the internet.
And then and only then should you start adding modulation effects, or delays, or other effects around the core amp model. In the real
world, guitarists add effects pedals before the guitar amp, because they have to. When building digital presets, you may find that you often get better results if you place effects after the amp model, rather than before. You get more clarity (particular for reverb effects); but sometimes lose some of the character that an effect in front of the amp can provide. For example, high-gain leads with a lot of distortion produce lovely phasing effects while pitch bending if you place an echo/delay ahead of the amp model. So experiment with different placements of effects in your presets, and see what works best for you.
If you have the luxury of stereo ouput, you can also experiment with placing stereo modulation effect plugins (chorus, flangers, phasers, stereo delays) last in the signal chain, where they produce truly marvelous results.
## Going Beyond the Pre-installed Factory Plugins
PiPedal includes a selection of pre-installed plugins from the TooB plugin collection that are intended to cover most basic needs for
guitar effects. See the [Using Lv2 Plugins](UsingLv2Plugins.md) section of the documentation for more details.
--------
[<< How to Use PiPedal](HowToUsePiPedal.md) | [Up](Documentation.md) | [An Intro to Snapshots >>](Snapshots.md)
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Cheap USB audio adapters, claim to to support 24-bit audio, and happily provide 24 bits of data. The problem is that they are usually providing less than 16-bits of signal (the remaining bits being pure noise).
You will get decent results; but not great results. Stepping up to a more expensive USB adapter dramatically improves the quality of signal you're going to get. With a decent USB audio adapters, some of the state-of-the art Machine Learning plugin produce results that are as good as or better the Helix or Kemperer amp emulations.
You will get good results; but not astounding results. Stepping up to a more expensive USB adapter dramatically improves the quality of signal you're going to get. With a decent USB audio adapters, NAM A2 amp emulations are significantly better than Helix or Kemperer amp emulations.
I think it's worthwhile, at this point, to make a brief discursus into the state of the art when it comes to machine learning models of guitar amps. There are two major Machine Learning amp simulators that are in the public domain. Jatin Chowdhury produced some of the first really impressive Machine Learning amp simulators (I believe) as part of his PhD thesis. Jatin Chowdhury's ML amp simulation library (which was graciously provided under an open-source MIT license) forms the core of the ToobML plugin included with PiPedal. Steven Atkins' Neural Amp Modeler library (also provided under an MIT license) is the other major ML implementation, that implements a variety of Machine Learning algorithms that have been developed since Jatin Chowdhury's initial publication of his results. TooB Neural Amp Modeler uses Steven Atkins' Neural Amp Modeler library. And both have large community-developed libraries of amp models. The quality of amp simulations produced by both of these libraries is breathtaking. As I said previously, as good as or better than Helix or Kemperer amp emulations.
I personally use and recommend the both the MOTU M2, and Focusrite Scarlett 2i2 4th gen (not the Solo, or 3rd gen models which have significantly less dynamic range). There are plenty of other pro-quality audio adapters that will probably work as well. Check the specs carefully, signal-to-noise-ratio is what matters, not bits of data. (This may show up on a datasheet as Dynamic Range, as well). Cheaper USB audio adapters that sell for less than US$70 will almost certainly not provide adequate signal-to-noise ratio for best results, and invariably won't provide S/N ratio specs for very very good reasons.
But to get Helix-quality (or better) results, you need a good USB adapter. For amp simulators, particularly, every extra bit of input signal is precious.
Ideally, you want a USB adapter that provides an input volume knob, and an instrument-level input jack, and it's enormously helpful to have a VU meter to display input signal level to the device. Microphone and RCA jacks will have the wrong input impedance, which may affect your guitar tone.
I personally use and recommend the Motu M2 USB audio adapter, although there are plenty of other pro-quality audio adapters that will probably work as well. Although, the MOTU devices are -- in my experience, exceptional. Check the specs carefully, signal-to-noise-ratio is what matters, not bits of data. Cheaper USB audio adapters that sell for less than US$70 will almost certainly not provide adequate signal-to-noise ratio for best results, and invariably won't provide S/N ratio specs for very very good reasons.
For best results, you want the input signal to the DAC to be as high as possible without clipping. Digitally clipped input signals sound horrible. And every db below "as high as possible" brings up the noise floor. Which is why a VU meter on the
USB adapter is helpful. The input signal should be peaking solidly in the yellow range of the VU meter, and must NEVER go into the red range.
Ideally, you want a USB adapter that provides an input volume knob, and an instrument-level input jack, and it's enormously helpful to have a VU meter to display input signal level to the device. Line-level or RCA jacks will have the wrong input impedance, and that has strange effects when 20 feet of guitar cable and tone controls that are designed for instrument-level impedance are involved. For best results, you want the input signal to be as high as possible without clipping. Clipped input signals sound horrible. And every db below "as high as possible" brings up the noise floor. Which is why a VU meter on the
USB adapter is helpful.
We recommend "gain-staging" your input signal to -6dbFS. Input and output signals of each successive plugin in your signal chain should be adjusted so that the signal is approximately -6dBFS when you are playing loudly. This is a good general rule of thumb for getting the best possible sound out of your plugins, and is particularly important for getting the best possible sound out of NAM A2 amp models. And this rule applies to the input signal coming into PiPedal from your USB adapter as well. Gain-staging the input signal to -6dBFs provides a little bit of safe headroom to avoid hard-clippping of the input signal. If you select the Start node in your PiPedal preset, you can see
the level of the input signal level coming into PiPedal from your USB adapter on the left-side VU meter. If you prefer to use a lower input trim on your USB adapter, adjust the input trim control in the Start node so that the right-side VU meter is peaking at around -6dBFS when you are playing loudly.
If you don't have an audio adapter with a VU meter, pay close attention to the input VU meter of the first effect in your guitar effect chain. That will indicate the signal level coming into the USB adapter. Ideally, you want the value peaking solidly in the yellow range of the VU meter, and NEVER going red.
Again, the MOTU M2 excels in this regard. It provides large volume knobs for input and output trim, along with very readable VU meters on the front panel which indicate both input and output signal levels.
--------
[<< An Intro to Snapshots](Snapshots.md) | [Up](Documentation.md) | [Optimizing Audio Latency >>](AudioLatency.md)
[<< Neural Amp Modeler Calibration](NamCalibration.md) | [Up](Documentation.md) | [Optimizing Audio Latency >>](AudioLatency.md)
docs/Configuring.md
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@@ -187,4 +187,4 @@ When the Raspberry Pi hosts the hotspot, mDNS discovery is definitely enabled; s
--------
[<< Headless Operation](HeadlessOperation.md) | [Up](Documentation.md) | [Using TooB Neural Amp Modeler >>](UsingNAM.md)
[<< Headless Operation](HeadlessOperation.md) | [Up](Documentation.md) | [What PiPedal Is >>](WhatPiPedalIs.md)
docs/Documentation.md
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@@ -3,17 +3,20 @@
&nbsp;
#### [What PiPedal Is](AboutPiPedal.md)
#### [System Requirements](SystemRequirements.md)
&nbsp;
#### [Installing PiPedal](Installing.md)
#### [PiPedal on Ubuntu](Ubuntu.md)
#### [Installing PiPedal on Ubuntu](Ubuntu.md)
#### [Headless Operation](HeadlessOperation.md)
#### [Configuring PiPedal After Installation](Configuring.md)
&nbsp;
#### [Using TooB Neural Amp Modeler](UsingNAM.md)
#### [An intro to Snapshots](Snapshots.md)
#### [What PiPedal Is](WhatPiPedalIs.md)
#### [Machine Learning in PiPedal (A History)](PiPedalHistory.md)
#### [How to Use PiPedal](HowToUsePiPedal.md)
#### [How to Build Presets With PiPedal](BuildingPresets.md)
#### [An Intro to Snapshots](Snapshots.md)
#### [Neural Amp Modeler Calibration](NamCalibration.md)
#### [Choosing a USB Audio Adapter](ChoosingAUsbAudioAdapter.md)
#### [Optimizing Audio Latency](AudioLatency.md)
#### [Command-Line Configuration of PiPedal](CommandLine.md)
@@ -34,9 +37,5 @@
#### [Build Prerequisites](BuildPrerequisites.md)
#### [The Build Systems](TheBuildSystem.md)
#### [How to Debug PiPedal](Debugging.md)
&nbsp;
 
#### [PiPedal Architecture](Architecture.md)
docs/FAQ.md
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@@ -32,13 +32,14 @@ Devices that would make excellent choices:
- MOTU M2
- Focusrite Scarlett 2i2 (4th gen)
-PreSonus Quantum ES 2 USB-C Audio Interface
- PreSonus Quantum ES 2 USB-C Audio Interface
- Solid State Logic SSL 2 MK II
- Universal Audio Volt 176
Or other devices in that sort of class and price range.
or other devices in that sort of class and price range. (The Focusrite Scarlett Solo, and 3rd gen 2i2 models have significantly
less dynamic range).
The MOTU M2, and the Focusrite Scarlett 2i2 are relatively affordable.
Of these, the MOTU M2, and the Focusrite Scarlett 2i2 are relatively affordable.
#### Q. My Neural Amp Modeler amp models don't sound that great. Am I doing something wrong? the output signal not loud enough.
docs/HeadlessOperation.md
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@@ -7,13 +7,13 @@ icon_float: right
{% include pageIcon.html %}
To get the best possible audio latency, your PiPedal server should run headless. GPU activity interferes with low-latency audio. Drawing to the screen (or even moving the mouse) can cause audio underruns. This does not mean that you cannot use a desktop install; but it does mean that you should not be using the PiPedal server's desktop when using PiPedal. Use a browser on a remote machine, or use a phone or tablet to control PiPedal. PiPedal is very much designed on the expectation that you will be using a remote device to control it.
To get the best possible audio latency, your PiPedal server should run headless, or at least be running without graphical activity on the server's desktop. GPU activity interferes with low-latency audio. Drawing to the screen (or even moving the mouse) can cause audio underruns. This does not mean that you cannot use a desktop install; but it does mean that you should not be using the PiPedal server's desktop when using PiPedal. Use a browser on a remote machine, or use a phone or tablet to control PiPedal. PiPedal is very much designed on the expectation that you will be using a remote device to control it.
It is not entirely clear why GPUs don't play well with realtime low-latency audio. It's probably not caused by interrupts, but may be caused by contention for system memory and various system buses. Or perhaps by graphics drives that cheat a bit in order to get better benchmark scores. If you are running a very powerful PC with a GPU that doesn't share system memory for its framebuffer, you may be able to run a desktop while using PiPedal; but if you are not getting the latency you think you should, try going back to headless operation. The difference is dramatic. A system that may struggle to achieve 15ms latency with a desktop running (256x3 buffer configuration), should easily be able to achieve sub-5ms latency (32x3 buffer configuration) when running headless. As a point of reference, 10ms latency is generally considered the maximum threshold for usable realtime audio that doesn't feel spongy and unpleasant.
It is not entirely clear why GPUs don't play well with realtime low-latency audio. It's probably not caused by interrupts, but may be caused by contention for system memory, memory caches, and various system buses. Or perhaps by graphics drivers that cheat a bit in order to get better benchmark scores. If you are running a very powerful PC with a GPU that doesn't share system memory for its framebuffer, you may be able to run a desktop while using PiPedal; but if you are not getting the latency you think you should, try going back to headless operation. The difference is dramatic. A system that may struggle to achieve 15ms latency with a desktop running (256x3 buffer configuration), should easily be able to achieve sub-5ms latency (32x3 buffer configuration) when running headless. As a point of reference, 10ms latency is generally considered the maximum threshold for usable realtime audio that doesn't feel spongy and unpleasant.
If you are running on a Raspberry Pi, it doesn't seem that strange run the Pi without a monitor connected. If you are using a laptop or desktop computer, running Ubuntu 24.x, this may seem a bit odd. But it matters! Running headless makes the difference between ordinary and extra-ordinary. You may want to consider purchasing a dedicated host for PiPedal&mdash;perhaps, a tiny N95, N100 or N150 micro-pc, or, of course, a Raspberry Pi 5. It's perfectly fine to run PiPedal on a desktop, or laptop. But just make sure you are not using the GPU when you run PiPedal.
Headless, in this context means that nothing is using the GPU. On a Raspberry Pi, it is sufficient to just disconnect the HDMI cables, and not be using a remote desktop connection. It is uncertain whether Ubuntu will stop using the GPU if there is an active desktop that is (for example) updating status indicators on the status bar. If in doubt, try disabling automatic login. The system will then stop at the login screen, which does not do any drawing until you start typing credentials. Configuring your PiPedal server to use a text-mode interface instead of a graphical interface would, of course, be perfect; but it seems unnecessarily inconvenient. Personally, I prefer to have a graphical desktop available if I need it to tinker with the system, or run software updates. On an Ubuntu server install, there is no graphical desktop, so this is not a problem. But see the section in [PiPedal on Ubuntu](Ubuntu.md) about configuring Ubuntu Server network services before you choose an Ubuntu Server install.
Headless, in this context means that nothing is using the GPU. On a Raspberry Pi, it's fine to have a desktop display, as long as you are not doing anything with it. It is uncertain whether Ubuntu will stop using the GPU if there is an active desktop that is (for example) updating status indicators on the status bar. If in doubt, try disabling automatic login. The system will then stop at the login screen, which does not do any drawing until you start typing credentials. Configuring your PiPedal server to use a text-mode interface instead of a graphical interface would, of course, be perfect; but it seems unnecessarily inconvenient. Personally, I prefer to have a graphical desktop available if I need it to tinker with the system, or run software updates. On an Ubuntu server install, there is no graphical desktop, so this is not a problem. But see the section in [PiPedal on Ubuntu](Ubuntu.md) about configuring Ubuntu Server network services before you choose an Ubuntu Server install.
--------
docs/HowToUsePiPedal.md
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---
page_icon: img/ServerClient_thumb.jpg
---
## How to Use PiPedal
{% include pageIcon.html %}
There are two parts to Pipedal: there is the Pipedal Server, which runs the realtime audio engine and plugins; and there is the PiPedal
user interface, provided by a web application, which is what you use to control and configure the PiPedal server.
By original design, the server and the user interface should run on separate computers. GPU activity and screen rendering interfere with
realtime audio processing; so to get the best possible latency and stability, you should not run the web application on the PiPedal server, and avoid using the PiPedal server machine for anything that will render graphics to the screen on the server machine. PiPedal was originally created to run on a Raspberry Pi 4, and subsequently ported to AMD64/x86-64 sytems, in the expectation that tiny N150-class micro-Pcs would also make a sensible platform on which to run Pipedal. Doing so, of course, means that you can also use PiPedal on a powerful desktop or laptop computer as well. But in all cases, the best possible performance and lowest possible latency is achieved if you run the web application on a separate machine from the PiPedal server.
If you are running the PiPedal server on a Raspberry Pi 4. In that case, you must run the web application
interface on a separate computer.
If you are using a Pi 5, or an N150-class micro-PC, you might be able to run the web
application on the server, with some signifant affect on what latencies and maximum CPU use you can safely use.
If you are running the PiPedal server on a powerful AMD64/x86-64 desktop or laptop computer, you can run both browser and server on the same machine; but even then, you will get better latency and stability if you run the web application on a separate computer.
On a Raspberry Pi, you will need an external USB adapter, or an audio hat of some kind. PiPedal will not work with the Raspberry Pi's built-in audio, which is not of sufficient quality or latency to be useful. On AMD64/x68-64 systems, you may be able to use the builtin-in audio systems, but you would be better off using an external USB audio adapter anyway. There are difficult problems with line-level conversions, and input and output impedances, all of which go away if you use an external USB audio adapter.
There are a lot of different USB audio adapters out there, not all of which provide optimum results with PiPedal.
The quality of PiPedal's amp simulations relies to a significant extent on the dynamic range (ratio of loudest to quietest signal) of the input signal you are using. This is not the same as the number of bits that an audio adapter provides. Low-end audio adapters that claim to support 24-bit audio will often have a signal-to-noise ratio that is less than 16-bits worth of dynamic range (sometimes dramatically
less). If you are just trying PiPedal out to get a sense of what it is capable of, you can get good results with a low-end USB audio adapter&mdash;probably better than what you would get with most previous-generation amp simulation technologies. But to get truly extraordinary results, it is worth investing in a good mid-range USB audio adapter that has a signal-to-noise ratio of at least 110dB. Models that I can particularly personally recommend: MOTU M2, or Focusrite Scarlett 2i2 (4th gen) (not the Solo, or 3rd gen models which have significantly less dynamic range). Both of those USB audio adapters have a signal-to-noise ratio that exceeds 110dB, which is more than enough to get the best possible results out of PiPedal's amp simulations. Guitar amplifiers dramatically compress the available dynamic range of the signal, and raise the noise floor. So every bit of dynamic range/signal to noise ratio that your audio adapter provides matters.
The Factory Presets that PiPedal provides are based on the premise that the audio output from PiPedal is going to headphones, a PA system, a front-of-house mixer, or some kind of speaker that has more-or-less linear response. It is perfectly reasonable to use PiPedal in front of an actual guitar amplifier as well; but in that case, you will need to modify presets to take into account the fact that the output from PiPedal is going to a guitar amp, which has a very different frequency response and linearity than a PA system or a front-of-house mixer.
It's probably worth mentioning at this point that the Pipedal server does not run as a normal application; instead it runs as a systemd service. This allows the Pipedal server to run both the web server and the realtime audio engine at realtime priority, under a service account, and ensures that the PiPedal server automatically starts after a reboot, even if you have not logged in interactively.
This may cause slightly odd interactions with audio services running in an interactive desktop session. First off, PiPedal gets the first claim on the audio device it is configured to use at boot time, because it runs before the desktop has a chance to use it, and because it opens the audio device for exclusive use by PiPedal. It also means that if you are changing PiPedal's audio device, you may need to get your desktop to release the device, by choosing another device for the desktop to use before PiPedal can select the device in question. You can tell whether something else has opened an audio device in the PiPedal UI. If the device is in use, it will appear in the list available audio devices, but it will be grayed out and you won't be able to select it. If something else is using the device, it is invariably the desktop that is using it, and you will need to get the desktop to release the device before PiPedal can use it.
--------
[<< Machine Learning in PiPedal (A History)](PiPedalHistory.md) | [Up](Documentation.md) | [How to Build Presets With PiPedal >>](BuildingPresets.md)
docs/ModUiSupport.md
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@@ -6,7 +6,7 @@ icon_width: 120px
{% include pageIconL.html %}
Some LV2 plugins (currently a minority of plugins) provide custom plugin user interfaces based on [MOD Audio's](https://mod.audio/desktop/)
Many LV2 plugins provide custom plugin user interfaces based on [MOD Audio's](https://mod.audio/desktop/)
[ModUi framework](https://wiki.mod.audio/wiki/MOD_Web_GUI_Framework). When using such a plugin, you can choose whether to use the MOD Web GUI Framework user interface (the MOD UI) or the default PiPedal user interface. For the most part, the same functionality is available in both interfaces.
Plugins that are distributed via Linux distributions usually do not implement MOD user interfaces; but all (or almost all) of the plugins that are available from the [PatchStorage website](https://patchstorage.com/platform/lv2-plugins/) do implement MOD user interfaces. Many plugins that are available from GitHub or other sources also implement MOD user interfaces. Often you can find updated versions of a plugin that is published by a distro on PatchStorage which does provide a MOD UI.
docs/UsingNAM.md → docs/NamCalibration.md
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# Using TooB Neural Amp Modeler
The living breathing heart of Pipedal is actually the TooB Neural Amp Modeler plugin, although you would be forgiven for not guessing that's the case.
Steven Atkinson's [Neural Amp Modeler](https://www.neuralampmodeler.com/) project is an open-source project that provides a framework for creating digital models of guitar amplifiers, speaker cabinets, and effects pedals, using machine learning techniques. The models are created by training a neural network on input-output pairs of audio data, where the input is the signal from a guitar plugged into a real amplifier or effect pedal, and the output is the signal recorded from the output of that amplifier or pedal. The result is a digital model that can replicate the sound of the original hardware with remarkable fidelity.
The results are astonishing. Models are capable of producing sounds that are virtually indistinguishable from the real hardware, including the complex nonlinearities and dynamic response characteristics that are difficult to capture with traditional modeling techniques. "This changes everything" is a phrase that comes up often when discussing Neural Amp Modeler. PiPedal didn't really start out this way, but it has gradually evolved into a platform whose principle purpose is providing access to Neural Amp Modeler models in a live performance context. That's how good NAM is.
PiPedal allows you to use Neural Amp Modeler models (.nam files) with the TooB Neural Amp Modeler plugin, which is bundled with PiPedal.
Although TooB ML models produce exceptionally good results, TooB Neural Amp Modeler produces significantly better results. Awkwardly, none of the built-in factory presets for Pipedal currently contain TooB Neural Amp Modeler plugins, because I am still working on obtaining NAM models that are licensed under terms that are compatible with Pipedal's MIT license. (Expect some progress soon).
So I would urge you, in the meantime, to experiment with TooB Neural Amp Modeler using free .nam files downloaded from [Tone 3000](www.tone3000.com), or perhaps purchase some commercial NAM models from any of several providers of non-free NAM models on the Internet. (Totally worth it!)
The remainder of this page deals with issues relating to how to get the absolute best results out of TooB Neural Amp Modeler. This is not required reading. You will get excellent results if you never read what follows. The purpose of what follows is to provide an explanation of model calibration in TooB Neural Amp Modeler&mdash;how it works, why you might or might not want to use it, and how to get good results even if you don't use it. "Calibration" is a confusing feature. It doesn't entirely do what you might it expect it do do. But it does provide useful functionality that may allow you to make even better use of NAM.
### Calibrating TooB Neural Amp Modeler
## TooB Neural Amp Modeler Calibration
This feature isn't what you think it is.
@@ -111,4 +95,4 @@ If you must feed output of a NAM effect simulation to a downstream NAM amp model
--------
[<< Configuring PiPedal After Installation](Configuring.md) | [Up](Documentation.md) | [An Intro to Snapshots >>](Snapshots.md)
[<< An Intro to Snapshots](Snapshots.md) | [Up](Documentation.md) | [Choosing a USB Audio Adapter >>](ChoosingAUsbAudioAdapter.md)
docs/PiPedalHistory.md
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---
page_icon: img/playbot.jpg
---
## Machine Learning and Guitar Amp Simulation (A History)
{% include pageIcon.html %}
Machine Learning (Artificial Intelligence) has changed everything.
In the world of guitar effect pedals, the revolution started in 2019 when Jatin Chowdhury published [a paper](https://arxiv.org/pdf/2106.03037) describing the results of using machine learning to simulate guitar amplifier effects in real-time. To put things in perspective, LLM AIs like ChatGPT have billions of parameters. Jatin was more interested in how well AI techniques worked if you used small Neural Net models with a few thousand parameters—models small enough to run in real-time. The answer was surprisingly positive: you can use small models and get impressive results. He then proceeded to publish his source code, both for the real-time simulations and the tools used to train his models, under an open-source MIT license. This has launched an avalanche of innovation.
Jatin Chowdhury's ML library continues to exist and can be freely downloaded and incorporated into guitar effect plugins available in most formats. The ML library and model training tools remain substantially the same as Chowdhury's initial release. There are significant gains in quality if you double the size of the Neural Networks he used in the original versions. Most models for the ML library now use a larger model, and many have gone through significantly more training than Chowdhury's originals. The result? The models sound amazing! Amp simulations based on Chowdhury's ML library can run in real-time on an ordinary computer and produce emulations that sound significantly better than previous-generation amp emulations.
Community developers quickly incorporated the ML library into free, open-source guitar plugins that run on Windows, Mac, and Linux. The TooB ML plugin, included with Pipedal, uses Jatin Chowdhury's ML library to implement amp simulations using ML technology. And some of Jatin Chowdhury's original ML models are also pre-installed by PiPedal. Original ML models, are still pretty good, but are not as good as current-generation NAM A1 and A2 models.
But the story does not end there.
Steven Atkinson has since released the [Neural Amp Modeler library](https://github.com/sdatkinson/NeuralAmpModelerCore), which traces its heritage to Chowdhury's ML library while providing support for a wider variety of Machine Learning algorithms. The Neural Amp Modeler library has also been released under an open-source MIT license and incorporated into plugins for most plugin formats and major computing platforms. The TooB Neural Amp Modeler plugin (bundled with Pipedal) uses the Neural Amp Modeler Core library to implement NAM A2 models. Credit also needs to be given to Mike Oliphant, whose [NeuralAudio library](http:s://github.com/mikeoliphant/NeuralAudio) provides a highly-optimized implementation of the NAM A1 algorithms that allow NAM A1 models to be used on a Raspberry Pi 4.
And finally (for now), in June of 2025, Steven Atkinson released NAM A2&mdash;the next generation of Neural Amp Modeler technology, which provides even more accurate amp simulations than NAM A1, while using even less CPU. NAM A2 models are also supported by the TooB Neural Amp Modeler plugin bundled with Pipedal, and very much form the living breathing core of PiPedal.
And the quality of NAM models is breathtaking! Game changing, even (a phrase that comes up suprisingly often when people are talking about NAM).
Subsequently, a large open-source-minded community has devoted itself to training new Neural Net models for NAM. Of these initiatives, [Tone3000.com](https://www.tone3000.com) is the most important. Tone3000 provides easy access to thousands of free, high-quality, downloadable NAM models. Models were originally available in NAM A1 format, but Tone3000.com has just retrained all of the models on Tone3000.com using NAM A2 technology. If you have a favorite amp, you will probably find good models for your amp on Tone3000. And Tone3000 also provides an easy way to [generate .nam models](https://www.tone3000.com/capture) from captures of your own amps and pedals as well!
So let's just to put all of that in perspective, because the results of all of that have huge implications for the music industry going forward. Jatin Chowdhury's machine learning experiment escaped from the lab in 2019, and has since taken over the world. You can use his code (and derivatives thereof) for free, in guitar plugins that are available on all major audio platforms and on all major hardware platforms, for free, and get access to a huge library of community-developed models for those plugins which are also free. All of which sound better than $1000+ stompboxes. All of which runs on a hardware platform that costs less than $150, when you use PiPedal! And sounds beter than other commercial digital amp simulations running on hardware costing thousands of dollars more.
## How PiPedal Fits Into All of This
PiPedal as first conceived, was a Pandemic Project that I wrote to explore better ways to do amp simulations. At that time, Guitarix was the go-to solution for open-source amp emulations. But as a player, I was not at all satisfied with any of the available digital amp simulation technologies. Nor was I particularly impressed by commercial digital amp simulations, which, while they often sounded somewhat
like the amp that were being simulated, but often felt cold and lifeless and unpleasant to play. That was somewhat overtaken by the release of ML libraries, which do provide much better amp simulations than the line of research I was pursuing at the time. But PiPedal was completely overtaken by the NAM revolution.
And, of course, somewhere along the line of development (after including an ML-based amp simulator, but before including support for NAM), it became more and more clear to me that PiPedal was becoming something quite extraordinary. It had vastly exceeded my personal expectations, and I felt that I had a duty (not a word used lightly) to share it with the world. So I released it as open source software, and have been sharing it with the world ever since. Yes, it has gone through a lot of polishing and refinement.
As a professional software developer, I have standards for the software I write; and I have been working hard to make sure that PiPedal is a product that meets those standards. As a professional developer, it has to be product that I can confidently associate my name with. All that to say, that it didn't neccesarily start out that way, but it has evolved into something that I am proud of, something that seems strangely larger on the inside than it is on the outside, and something that I am happy to share with the world.
Currently, the heart and soul of PiPedal is the open-source work of Jatin Chowdhury and Steven Atkinson, and the incredible community of developers who have built on their work to create the plugin code and models that run on PiPedal. Credit where credit is due. Pipedal would not be what it is without the open-source contributions of these people. And the folks at Tone3000.com, who have done an amazing job of making it easy to find and download high-quality NAM models, and to create your own NAM models from captures of your own amps and pedals. And, of course, Mike Oliphant, whose NeuralAudio library provides a highly-optimized implementation of the NAM A1 algorithms that allow NAM A1 models to be used on a Raspberry Pi 4.
PiPedal 2.0 is a major new release that completes the transition to NAM-based amp simulations (and picks up NAM A2 support as bonus). The Factory Presets are now all based on NAM A2 models, and a small selection of NAM A2 models are pre-installed and ready to use. The updated TooB Neural Amp Modeler plugin, which provides support for both NAM A1 and A2 models, is bundled with PiPedal. And the ability to download NAM A2 models directly from Tone3000.com's web services is built into the TooB Neural Amp Modeler plugin as well.
In the end, what really counts in a guitar stomp box is the amp emulations, and how good they are. On Pipedal, thanks to Jatin Chowdhury's escaped monster, they are very good indeed. And thanks to Steven Atkinson's amazing NAM A2 technology, Pipedal is a platform for running the best amp simulations in the world, on a Raspberry Pi or Ubuntu AMD64/x86-64 computer, using a phone or tablet to control the PiPedal server (for which I would like to take a little bit of credit).
--------
[<< What PiPedal Is](WhatPiPedalIs.md) | [Up](Documentation.md) | [How to Use PiPedal >>](HowToUsePiPedal.html)
docs/Snapshots.md
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@@ -29,15 +29,11 @@ Note how PiPedal has been configured to use <i>banks</i> as containers for songs
#### Accessing Snapshots in the PiPedal User Interface.
#### Creating Snapshots in the PiPedal User Interface.
You can create, modify, and select snapshots in two places in the PiPedal user interface.
You can create, modify, and select snapshots in the main PiPedal preset editor.
The first is via the <b><i>Snapshot</i></b> icon button in the middle row of controls in the main page of pipedal. It's the button that looks like a camera. The second is via the <b><i>Performance View</i></b>, which is accessible via the <b><i>Performance View</i></b> menu entry in the main PiPedal menu.
It's easier to create an initial set of snapshots from the main PiPedal page. You edit the current controls of the current preset, and you can then save current control values to a snapshot by first pressing the <b><i>Snapshots</i></b> icon button (the camera icon), and then pressing the <b><i>Save</i></b> button for a particular snapshot in the popup dialog.
On the other hand, you may find it easier to edit an existing set of snapshots from the <b><i>Performance View</i></b>. When you click the <b><i>Edit</i></b> button for a particular snapshot, PiPedal displays the <b><i>Snapshot Editor</i></b> which allows you to edit the control values for that snapshot directly.
Click on the <b><i>Snapshot</i></b> icon button in the middle row of controls in the main page of pipedal. It's the button that looks like a camera.
@@ -45,12 +41,10 @@ On the other hand, you may find it easier to edit an existing set of snapshots f
As a general rule, it's best to get the structure (which plugins are loaded, and how they are connected together) settled before you start creating snapshots. If you change the structure of a preset, it may affect snapshots that belong to that preset.
Each preset has its own set of preset control settings which are independent of the control settings in each snapshot. But all share the same plugin structure (which plugins are loaded, and how they are connected together).
When you click the edit button in the Performance View, you are editing control settings associated with the snapshot. When you press the back button from the snapshot editor, control settings for that snapshot are saved immediately. Saved control settings for the preset are not modified. You can avoid saving snapshot control settings by pressing the Cancel icon button (X) at the end of the toolbar for the snapshot editor. You cannot change the structure of the plugins in the preset to which snapshots belong from within the Snapshot editor. Nothing you do in the snapshot editor will affect the saved control values for the currently loaded preset.
Things are different when you are editing presets in the main PiPedal page. Changes to preset controls are not saved until you press the Save button. And you can make structural changes. When you make structural changes to the preset, you may also affect the control settings included in each snapshot. You can move plugins around freely. Snapshot controls will still apply to the plugin even if it has moved. But if you remove a plugin, the settings for that plugin in each snapshot will be removed. Even if you re-add a new instance of of the same plugin, settings in snapshots will not be remembered. And if you add a plugin, selecting a snapshot will set controls for the new plugin to default values (not the values of the controls in the main preset). So as a general rule, it's best to get the structure of a preset more-or-less settled before you start creating snapshots.
Each snapshot has its own set of preset control settings which are independent of the control settings in each snapshot. But all share the same plugin structure (which plugins are loaded, and how they are connected together).
If you make structural changes to a preset that add a new plugin, there will not be control settings for the new plugins in any of the snapshots (they will default to the values of the controls in the main preset, or whichever snapshot was last loaded, which may lead to unexpected results when switching between snapshots). You can actually re-order plugins within a preset, or remove plugins without affecting the control settings in a snapshot. But if you add a new plugin, there will be no saved values for the controls of the new plugin in each of the snapshots. If you do add a new plugin, it would be a good idea to go through each of the snapshots, and resave them to make sure that control settings for each of the snapshots are what you expect them to be.
--------
[<< Using TooB Neural Amp Modeler](UsingNAM.md) | [Up](Documentation.md) | | [Choosing a USB Audio Adapter >>](ChoosingAUsbAudioAdapter.md)
[<< How to Build Presets With PiPedal](BuildingPresets.md) | [Up](Documentation.md) | [Neural Amp Modeler Calibration >>](NamCalibration.md)
docs/SystemRequirements.md
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* PiPedal will also run well on a Raspberry Pi 4.
* A Raspberry Pi 3 (or equivalent SBC) can run PiPedal, but may struggle to keep up. Not recommended.
* At least 2GB of RAM (4GB recommended).
* To compile PiPedal from source, at least 8GB of RAM is required.
* To compile PiPedal from source, at least 8GB of RAM is required (16GB recommended).
### Audio System Requirements:
* On Raspberry Pi's, you will need an external USB Audio Adapter, or a Pi audio hat with at least one audio input. You cannot use the built-in audio inputs and outputs.
@@ -44,7 +44,7 @@ You should not run Pipedal using a browser on the same machine that is running t
The Pipedal server does update itself automatically (it prompts for permission from the browser interface if there is an update available). However, it does not take care of Operating System updates. You should make sure to keep your OS up to date, and to install security updates as they become available. You will need to do that yourself from a commandline terminal, or using a desktop environment on the machine running the PiPedal server.
You may find it much easier to set up and maintain your PiPedal server if you enable SSH access on the server machine.
You may find it much easier to set up and maintain your headless PiPedal server if you enable SSH access on the server machine, and even easier if you install a graphical desktop that you can access remotely using VNC or RDP.
### Older Versions of PiPedal
@@ -55,5 +55,5 @@ Older versions of PiPedal (v1.1.31) have been tested on the following operating
--------
[<< Changing the Web Server Port](AboutPiPedal.md) | [Up](Documentation.md) | [Installing PiPedal >>](Installing.md)
[Up](Documentation.md) | [Installing PiPedal >>](Installing.md)
docs/WhatPiPedalIs.md
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---
page_icon: img/PiPedal20Thumb.jpg
---
## What PiPedal Is
{% include pageIcon.html %}
PiPedal is a Linux-based guitar effects processor&mdash;a "stomp box"&mdash;that is designed to run on a Raspberry Pi, or a small AMD64/x86-64 micro-PC running Ubuntu. It provides a web-based user interface that you can access from any modern web browser on the same network as the PiPedal server.
PiPedal is built around Neural Amp Modeler (NAM) A1 and A2 guitar amp simulation technology, which provide the best amp simulations in the world, bar none. Sounds like the real thing; and feels like the real thing when you play!
Small computers like a Raspberry Pi 4, or a small N150-class micro-PC provide more processing power than commercial guitar stomp boxes costing thousands of dollars more. PiPedal takes advantage of that processing power to provide state-of-the-art NAM A2 guitar amp simulations. Up to three NAM A2 models can be run simultaneously on a Raspberry Pi 4, and up to seven NAM A2 models can be run simultaneously on a Pi 5, or an N150-class micro-PC. (Even more if you use the Threading feature of Toob Neural Amp Modeler). All with plenty of processing power left over for running additional guitar plugins within the same preset.
PiPedal is designed to be easy to use whether you are at home, or performing onstage, or in a studio. Configure the PiPedal server to automatically start a Wi-Fi hotspot whenever it is unable to see your home Wi-Fi network, and you can confidently use PiPedal when you are on the road, even though you don't have a shared Wi-Fi connection with the PiPedal server! The [PiPedal Android Remote](https://play.google.com/store/apps/details?id=com.twoplay.pipedal) provides one-click access to your PiPedal server on your Android phone or tablet whenever you are on the same Wi-Fi network, and will automatically connect to the PiPedal server Hotspot whenever you are away from home.
The PiPedal Remote Android app allows you to quickly connect to your PiPedal server no matter where you are.
PiPedal allows installation of the Pipedal client as a Progressive Web App (PWA). This allows you to use PiPedal as a native application on your Windows or Apple desktop or laptop, without the unnecessary clutter of browser-hosted web applications.
Major features of PiPedal include:
- Stable ultra-low-latency audio processing on the Pipedal server.
- Direct support for Neural Amp Modeler (NAM) A1 and A2 guitar simulations, providing the best amp simulations in the world, all running on a Raspberry Pi or Ubuntu AMD64/x86-64computer.
- Support for direct downloads of NAM A2 models from Tone3000.com's web services.
- A web-based user interface that can be accessed from any modern web browser on the same network as the PiPedal server.
- A UI designed specifically for use on small form-factor touch devices like phones and tablets (although it works equally well in desktop browsers).
- A suite of 26 bundled effects from the TooB effect plugin bundle, specifically designed for use as guitar effects that provide out-of-the-box functionality required to build most guitar effect signal chains.
- The TooB Convolution Reverb provides dramatic and accurate reverb effects based on recordings of real spaces, along with a powerful set
of controls that allow you to shape reverb IRs to your exact preference.
- Support for most LV2 guitar effect plugins, including support for LV2 plugins that have MOD web interfaces.
- Support for MIDI control of PiPedal parameters from external MIDI controllers, or MIDI floorboards, via USB or Bluetooth connections.
- A brand new set of NAM A2-based Factory Presets, and a small selection of NAM A2 models pre-installed and ready to use.
- A Progressive Web App (PWA) implementation that allows you to install PiPedal as a native application (without associated browser controls) on a Windows or Apple computer.
- An auto Hotspot on the PiPedal server that starts up whenever the Pipedal server is unable to connect to your home network. This allows you to confidently use PiPedal when you are gigging or in the studio, even though you don't have a shared Wi-Fi connection with the PiPedal server.
- The [PiPedal Remote Android app](https://play.google.com/store/apps/details?id=com.twoplay.pipedal) provides one-click access to the PiPedal server on your Android phone or tablet whenever you are on the same Wi-Fi network, and will automatically search for and connect to the PiPedal server Hotspot when you are not at home.
- Up to six snapshots per preset, which allow you to build flexible presets that can be reconfigured on the fly during a live performance.
- A Performance View, which provides a minimal interface for easy and efficient use of PiPedal on stage.
PiPedal started as a Pandemic Project labor of love, but has evolved into the solution of choice for running live guitar effects in performance on Linux, in no small part due to contributions made by other open-source developers like Jatin Chowdhury, Steven Atkinson and Mike Oliphant.
PiPedal is open-source software released under an MIT license. You can download the source code, and contribute to the project, on GitHub: [https://github.com/rerdavies/pipedal](https://github.com/rerdavies/pipedal). If you would like to sponsor further development of PiPedal, you can do so via [PiPedal's GitHub Sponsorship page](https://github.com/sponsors/rerdavies).
--------
[<< Configuring PiPedal After Installation](Configuring.md) | [Up](Documentation.md) | [Machine Learning in PiPedal (A History)](PiPedalHistory.md)
docs/_includes/gallery.html
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let galleryPath = "gallery/";
let images = [
"dark-sshot1.png",
"jazz.png",
"midi-bindings.png",
"hotspot.png",
"thunder.png",
"rig.jpg",
"nam_models.png",
"hotspot.png",
"midi-bindings.png",
];
let captions = [
"PiPedal Guitar Effects Pedal running on a Raspberry Pi.",
"Control via browser, phone or tablet",
"Stage Rig",
"Download NAM A2 Models from Tone3000.com",
"Easy Wi-Fi hotspot configuration (Raspberry Pi only)",
"Bind controls to midi messages.",
"Easy Wi-Fi hotspot configuration.",
"Neural Net amp models",
"Stage rig."
];
let maxWidth = 680;
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}
LI {
margin-bottom: 0.5em;
}
.header-offset {
display: block;
height: 54px;
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docs/index.md
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<h2 style="font-weight: 300; font-size: 1.6em;line-height: 1em; padding-top: 32px; padding-bottom: 0px;margin-bottom: 4px">PiPedal Guitar Effects Processor</h2>
<p style="padding-top: 0px; opacity: 0.6; padding-bottom: 16px">A Raspberry Pi-based stomp box designed to be controlled from a phone or tablet.</p>
<div style="padding-left:48px; padding-right: 48px; padding-top: 32px; padding-bottom: 16px;
background-color: #DCDCFF; border-radius: 8px; border: 0px solid #555;
margin-bottom: 48px; margin-top: 16px;
margin-left: 16px; margin-right: 48px;
box-shadow: 1px 4px 12px rgba(0, 0, 0, 0.3);">
<div style="opacity: 0.8;">
<h2 style='font-weight: 300; font-family: "Roboto Light", "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol"; font-weight: 400; font-size: 1.3em;line-height: 1.2em; padding-top: 0px; padding-bottom: 16px;margin-bottom: 8px'
>Announcing <a href="PiPedal2.html">PiPedal 2.0</a></h2>
<p>
The first public preview release of Pipedal version 2.0.103-alpha is now available!
</p>
<p>This release includes </p>
<ul>
<li style="margin-bottom: 8px">
Support for Neural Amp Modeler A2 models&mdash;the next generation of the ground-breaking
Neural Amp Modeler technology.</li>
<li style="margin-bottom: 8px">
Integration with Tone3000.com services for easy downloading of Neural Amp Modeler A2 models and IIRs.</li>
<li style="margin-bottom: 8px">
A new Channel Routing dialog for global routing of auxiliary input channels, and unprocessed re-amp output channels.</li>
<li>Install Pipedal as a Progressive Web Application (PWA), which allows you to launch Pipedal from your desktop as a native desktop application. (A nice feature if you are accessing Pipedal from an Apple device).</li>
<li style="margin-bottom: 8px">
Many other minor features, improvements, and bug fixes.</li>
</ul>
<p>For more information, and to download PiPedal v2.0.103-alpha <a href="PiPedal2.html">click here</a>.
</p>
</div>
</div>
<a href="https://rerdavies.github.io/pipedal/ReleaseNotes"><img src="https://img.shields.io/github/v/release/rerdavies/pipedal?color=%23808080"/></a>
<a href="https://rerdavies.github.io/pipedal/download"><img src="https://img.shields.io/badge/Download-008060" /></a>
<a href="https://rerdavies.github.io/pipedal/Documentation"><img src="https://img.shields.io/badge/Documentation-0060d0"/></a>
_To download PiPedal v1.5.99, click [*here*](download.md).
_To download PiPedal v2.0.102, click [*here*](download.md).
To view PiPedal documentation, click [*here*](Documentation.md)._
Use your Raspberry Pi as a guitar effects pedal. Configure and control PiPedal with your phone or tablet.
Use your Raspberry Pi, or Ubuntu amd/x86-64 computer as a guitar effects pedal. Configure and control PiPedal remotedly, with your phone or tablet, or via a web browser.
PiPedal running on a Raspberry Pi 4 or Pi 5 provides stable super-low-latency audio via external USB audio devices, or internal Raspberry Pi audio hats.
PiPedal will also run on Ubuntu 24.x or later (amd64/x86-64 and aarch64). Make sure you follow the [Ubuntu post-install
PiPedal runs on Raspbery Pi OS (Bookworm or Trixie), or Ubuntu 24.x or later (amd64/x86-64 and aarch64). Make sure you follow the [Ubuntu post-install
instructions](https://rerdavies.github.io/pipedal/Configuring.html) to make sure your Ubuntu OS is using a realtime-capable kernel.
{% include gallery.html %}
PiPedal includes state-of-the-art AI-based guitar amp emulation plugins based on the famous Neural Amp Modeler (NAM) and ML libraries which provide amp modelling that will blow your mind.
New in PiPedal v2.0:
- Support for Neural Amp Modeler (NAM) A2 models.
- Direct single-step downloads of NAM A2 models to the Pipedal server using web services provided by <a href="https://tone3000.com/">Tone3000.com</a>.
- Install PiPedal as a Progressive Web App (PWA) on your Windows or Apple desktop or laptop in order to run PiPedal as a native application, without the clutter of browser chrome, address bars, and needless decorations.
- A new Channel Routing dialog which allows you to pass through Auxilliary audio channels, or unprocessed guitar inputs for later re-amping in a DAW or external hardware.
- New NAM A2-based Factory Presets, and a small selection of NAM A2 models pre-installed and ready to use.
PiPedal includes state-of-the-art AI-based guitar amp emulation, using the TooB Neural Amp Modeler technology. And PiPedal 2.0 now includes support for the brand new NAM A2 technology, which provides event more accurate amp simulations than NAM A1, while using even less CPU. Experience the ground-breaking quality of NAM A2 models now, with PiPedal's low-latency audio engine running on your Raspberry Pi or Ubuntu computer.
NAM changes everything! The quality of NAM A1 and A2 models is better than than amp emulations on top-of-the-line commercial guitar stomp boxes costing thousands of dollars. Simulations that not only sound like the real thing, but also respond to your playing dynamics in the same way as the real amp.
PiPedal 2.0 integrates with Tone3000.com's web services, allowing you to directly install new NAM A2 models on the pipedal server without ever leaving the PiPedal user interface. Or download and install commercially-developed NAM models from a rich ecosystem of model providers.
{% include demo.html %}
PiPedal can be remotely controlled via a web interface over Ethernet, or Wi-Fi. If you don't have access to a Wi-Fi router, PiPedal can be configured to
start a Wi-Fi hotspot automatically, whenever your Raspberry Pi can't connect to your home network.
Install the [PiPedal Remote Android app](https://play.google.com/store/apps/details?id=com.twoplay.pipedal) to get one-click access to PiPedal via Wi-Fi networks, or Wi-Fi hotspots. If you are using PiPedal away from home, you can configure PiPedal to automatically start a Wi-Fi hotspot on your Raspberry Pi
whenever Pipedal is unable to detect your home network. The PiPedal Client Android app will allow to connect by simply launching the app, whether you are at home, or using a Wi-Fi auto-hotspot at a gig, when away from home.
Install the [PiPedal Remote Android app](https://play.google.com/store/apps/details?id=com.twoplay.pipedal) to get one-click access to PiPedal via Wi-Fi networks, or Wi-Fi hotspots. If you are using PiPedal away from home, you can configure PiPedal to automatically start a Wi-Fi hotspot whenever Pipedal is unable to detect your home network (Raspberry Pi OS only). The PiPedal Client Android app will allow to connect by simply launching the app, whether you are at home, or using a Wi-Fi auto-hotspot at a gig, when away from home.
PiPedal's user interface has been specifically designed to work well on small form-factor touch devices like phones or tablets. Clip a phone or tablet on your microphone stand on stage, and you're ready to play! Or connect via a desktop browser, for a slightly more luxurious experience. The PiPedal user-interface adapts to the screen size and orientation of your device, providing easy control of your guitar effects across a broad variety devices and screen sizes.
PiPedal includes a pre-installed selection of LV2 plugins from the ToobAmp collection of plugins; but it works with most LV2 Audio plugins. There are literally hundreds of free high-quality LV2 audio plugins that will work with PiPedal. Just install them on your Raspberry Pi, and they will show up in PiPedal.
PiPedal includes a pre-installed selection of LV2 plugins from the ToobAmp collection of plugins; but it works with most LV2 Audio plugins. There are literally hundreds of free high-quality LV2 audio plugins that will work with PiPedal. Just install them on your Raspberry Pi, and they will show up in PiPedal.
If your USB audio adapter has MIDI connectors, you can use MIDI devices (keyboards, controllers, or midi floor boards) to control PiPedal while performing. A simple interface allows you to select how you would like to bind PiPedal controls to midi messages.