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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Deep Learning for Guitar Effect Emulation
| Date | Stars |
|---|---|
| 2026-07-31 | 349 |
| 2026-08-06 | 350 |
| 2026-08-14 | 350 |
| 2026-08-15 | 350 |
| 2026-08-18 | 350 |
| 2026-09-30 | 351 |
| 2026-10-23 | 352 |
| 2026-11-02 | 354 |
| 2026-11-04 | 354 |
Today
— stars today
This week
+2 stars this week
This month
+3 stars this month
Momentum
0.0
growth rate 0.57%/day
# PedalNet
Re-creation of model from [Real-Time Guitar Amplifier Emulation with Deep
Learning](https://www.mdpi.com/2076-3417/10/3/766/htm)
See my [blog
post](http://teddykoker.com/2020/05/deep-learning-for-guitar-effect-emulation/)
for a more in depth description along with song demos.
## Data
`data/in.wav` - Concatenation of a few samples from the
[IDMT-SMT-Guitar](https://www.idmt.fraunhofer.de/en/business_units/m2d/smt/guitar.html) dataset<br>
`data/ts9_out.wav` - Recorded output of `in.wav` after being passed through an
Ibanez TS9 Tube Screamer (all knobs at 12 o'clock).<br>
`models/pedalnet.ckpt` - Pretrained model weights
## Usage
**Run effect on .wav file**:
Must be single channel, 44.1 kHz
```bash
# must be same data used to train
python prepare_data.py data/in.wav data/out_ts9.wav
# specify input file and desired output file
python predict.py my_input_guitar.wav my_output.wav
# if you trained you own model you can pass --model flag
# with path to .ckpt
```
**Train**:
```bash
python prepare_data.py data/in.wav data/out_ts9.wav # or use your own!
python train.py
python train.py --gpus "0,1" # for multiple gpus
python train.py -h # help (see for other hyperparameters)
```
**Test**:
```bash
python test.py # test pretrained model
python test.py --model lightning_logs/version_{X}/epoch={EPOCH}.ckpt # test trained model
```
Creates files `y_test.wav`, `y_pred.wav`, and `x_test.wav`, for the ground truth
output, predicted output, and input signal respectively.
Excerpt of 1,505 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:174bb685f009a8d9, llm:Repository description: "Deep Learning for Guitar Effect Emulation" (language: Python).
matched fp:174bb685f009a8d9, llm:Repository description: "Deep Learning for Guitar Effect Emulation" (language: Python).
matched fp:174bb685f009a8d9, llm:Repository description: "Deep Learning for Guitar Effect Emulation" (language: Python).