# piano_transcription_inference

**Repository Path**: garlong/piano_transcription_inference

## Basic Information

- **Project Name**: piano_transcription_inference
- **Description**: 片挨那儿传石刻破行引发论是，mp3提取钢琴midi，机器深度学习，转载自某大侠
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 1
- **Forks**: 0
- **Created**: 2021-04-13
- **Last Updated**: 2021-07-15

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# 半成品，需要乐器检测和乐器滤波器，才能全部提取。钢琴虽然好，只是一种乐器呀。
# Piano transcription inference

This toolbox is a piano transcription inference package that can be easily installed. Users can transcribe their favorite piano recordings to MIDI files after installation. To see how the piano transcription system is trained, please visit: https://github.com/bytedance/piano_transcription.

## Demos
Here is a demo of our piano transcription system: https://www.youtube.com/watch?v=5U-WL0QvKCg

## Installation
The piano transcription system is developed with Python 3.7 and PyTorch 1.4.0 (Should work with other versions, but not fully tested).
Install PyTorch following https://pytorch.org/. Users should have **ffmpeg** installed to transcribe mp3 files.

```
pip install piano_transcription_inference
```

Installation is finished! 

## Usage
Want to try it out but don't want to install anything? We have set up a [Google Colab](https://colab.research.google.com/github/qiuqiangkong/piano_transcription_inference/blob/master/resources/inference.ipynb).

```
python3 example.py --audio_path=resources/cut_liszt.mp3 --output_midi_path=cut_liszt.mid --cuda
```

This will download the pretrained model from https://zenodo.org/record/4034264. 

Users could also execute the inference code line by line:
```
from piano_transcription_inference import PianoTranscription, sample_rate, load_audio

# Load audio
(audio, _) = load_audio(audio_path, sr=sample_rate, mono=True)

# Transcriptor
transcriptor = PianoTranscription(device='cuda', checkpoint_path=None)  # device: 'cuda' | 'cpu'

# Transcribe and write out to MIDI file
transcribed_dict = transcriptor.transcribe(audio, 'cut_liszt.mid')
```

## Visualization of piano transcription

**Demo.** Lang Lang: Franz Liszt - Love Dream (Liebestraum) [[audio]](resources/cut_liszt.mp3) [[transcribed_midi]](resources/cut_liszt.mid)

<img src="resources/cut_liszt.png">

## FAQs
This repo support Linux and Mac. Windows has not been tested.

If users met "audio.exceptions.NoBackendError", then check if ffmpeg is installed.

If users met the problem of "Killed". This is caused by there are not sufficient memory.

## Applications

We have built a large-scale classical piano MIDI dataset https://github.com/bytedance/GiantMIDI-Piano using our piano transcription system.

## Cite
[1] High-resolution Piano Transcription with Pedals by Regressing Onsets and Offsets Times, [To appear], 2020