---
license: cc-by-nc-sa-4.0
task_categories:
- audio-classification
language:
- en
tags:
- MIDI
- music
- score
- representations
- tokenized
- music AI
pretty_name: godzillapiano
size_categories:
- 1M<n<10M
dataset_info:
  features:
  - name: dataset
    dtype: string
  - name: md5
    dtype: string
  - name: score
    sequence: int64
  splits:
  - name: train
    num_bytes: 56796114600
    num_examples: 1138048
  download_size: 7136701973
  dataset_size: 56796114600
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---

# Godzilla Piano
## 1.1M+ select normalized solo piano scores representations from [Godzilla MIDI dataset](https://huggingface.co/datasets/projectlosangeles/Godzilla-MIDI-Dataset)

![Godzilla-Piano-Logo.png](https://cdn-uploads.huggingface.co/production/uploads/5f57ea2d3f32f12a3c0692e6/hxmRb6PZE6EpoLaiUaQ5X.png)

```
Godzilla's Musical Transformation by Microsoft Copilot

In the neon glow of a midnight throng,
A beast with headphones hums along.
Where thunderous roars once led the fray,
Now delicate keystrokes steal the day.

Godzilla, master of storm and lore,
Swaps terror for tunes, a musical score.
Each note a spark on the ebony keys,
Transforming chaos into rhythmic ease.

Under moonlit skies and electric sound,
The once-feared monster becomes beautifully profound.
A gentle reminder in each playful beat,
Even legends can find joy in something sweet.

So let the bass and melody entwine,
In a magical dance, uniquely divine.
For in each unexpected twist and gleam,
Lies the heart of a dreamer and a dreamer's dream.
```

***

## Installation and use

***

### Load dataset

```python
#===================================================================

from datasets import load_dataset

#===================================================================

godzilla_piano = load_dataset('asigalov61/Godzilla-Piano')

dataset_split = 'train'
dataset_entry_index = 0

dataset_entry = godzilla_piano[dataset_split][dataset_entry_index]

midi_dataset = dataset_entry['dataset']
midi_hash = dataset_entry['md5']
midi_score = dataset_entry['score']

print(midi_dataset)
print(midi_hash)
print(midi_score[:15])
```

***

### Decode score to MIDI

```python
#===================================================================
# !git clone --depth 1 https://github.com/asigalov61/tegridy-tools
#===================================================================

import TMIDIX

#===================================================================

def decode_to_ms_MIDI_score(midi_score):

    score = []

    time = 0
    
    for m in midi_score:

        if 0 <= m < 128:
            time += m * 32

        elif 128 < m < 256:
            dur = (m-128) * 32

        elif 256 < m < 384:
            pitch = (m-256)

        elif 384 < m < 512:
            vel = (m-384)

            score.append(['note', time, dur, 0, pitch, vel, 0])

    return score
    
#===================================================================

ms_MIDI_score = decode_to_ms_MIDI_score(midi_score)

#===================================================================

detailed_stats = TMIDIX.Tegridy_ms_SONG_to_MIDI_Converter(ms_MIDI_score,
                                                          output_signature = midi_hash,
                                                          output_file_name = midi_hash,
                                                          track_name='Project Los Angeles'
                                                          )
```

***

## Citations

```bibtex
@misc{GodzillaMIDIDataset2025,
  title        = {Godzilla MIDI Dataset: Enormous, comprehensive, normalized and searchable MIDI dataset for MIR and symbolic music AI purposes},
  author       = {Alex Lev},
  publisher    = {Project Los Angeles / Tegridy Code},
  year         = {2025},
  url          = {https://huggingface.co/datasets/projectlosangeles/Godzilla-MIDI-Dataset}
```

```bibtex
@misc {breadai_2025,
    author       = { {BreadAi} },
    title        = { Sourdough-midi-dataset (Revision cd19431) },
    year         = 2025,
    url          = {\url{https://huggingface.co/datasets/BreadAi/Sourdough-midi-dataset}},
    doi          = { 10.57967/hf/4743 },
    publisher    = { Hugging Face }
}
```

```bibtex
@inproceedings{bradshawaria,
  title={Aria-MIDI: A Dataset of Piano MIDI Files for Symbolic Music Modeling},
  author={Bradshaw, Louis and Colton, Simon},
  booktitle={International Conference on Learning Representations},
  year={2025},
  url={https://openreview.net/forum?id=X5hrhgndxW}, 
}
```

***

### Project Los Angeles
### Tegridy Code 2025