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Update README.md (#3)
Browse files- Update README.md (13da5e6f5e9f36d1def7a48e8dceaf3be35025db)
Co-authored-by: Yuheng Lin <RozenWhite@users.noreply.huggingface.co>
README.md
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- en
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size_categories:
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- 100K<n<1M
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---
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- en
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size_categories:
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- 100K<n<1M
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---
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# MusicScore: A Dataset for Music Score Modeling and Generation
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Official dataset repository for [paper](https://arxiv.org/abs/2406.11462):
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**MusicScore: A Dataset for Music Score Modeling and Generation**.
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> Author list: [Yuheng Lin](https://rozenthegoat.github.io), [Zheqi Dai](https://github.com/dzq84) and [Qiuqiang Kong](https://github.com/qiuqiangkong)
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MusicScore is a large-scale music score dataset collected and processed from the International Music Score Library Project ([IMSLP](https://imslp.org/)).
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MusicScore consists of image-text pairs, where the image is a page of a music score and the text is the metadata of the music.
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The metadata of MusicScore is extracted from the general information section of the IMSLP pages.
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The metadata includes rich information about the composer, instrument, piece style, and genre of the music pieces.
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MusicScore is curated into small, medium, and large scales of [400](./MusicScore-400/), [14k](./MusicScore-400/), and [200k](./MusicScore-400/) image-text pairs with varying diversity, respectively.
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For codebase containing data processing scripts we used to craft MusicScore dataset and evaluation scripts for *music score generation* experiment along with FID measurement, please refer to [MusicScore-script](https://github.com/dzq84/MusicScore-script).
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## Dataset Description
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MusicScore dataset is curated into three scales of subsets:
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|Subset |Amount of images|
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|:--------------|:---------------|
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|MusicScore-400 |403 |
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|MusicScore-14k |14656 |
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|MusicScore-200k|204800 |
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For MusicScore-400, it contains 19 most popular piano and violin compositions.
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For MusicScore-14k and -200k, we filtered images by color depth and cover contents. For later one, we train a classification model simply based on ResNet18, for details, please refer to the corresponding codebase [MusicScore-script](https://github.com/dzq84/MusicScore-script).
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## Example
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An example sample (IMSLP913207_11.jpg from MusicScore-400), the image and its matching metadata stored in a JSON file.
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```json
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{
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"Work Title": "Violin Concerto",
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"Alternative. Title": "Violin Concerto [No.2]",
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"Name Translations": "Koncert skrzypcowy; Husľový koncert; Концерт для скрипки с оркестром; 바이올린 협주곡; concerto pour violon en mi mineur; Violin Concerto in E minor; Concierto para violín; Concertul pentru vioară; ไวโอลินคอนแชร์โต; Concert per a violí; Viulukonsertto; Концерт для скрипки з оркестром; Concerto per violino e orchestra op. 64; Violinkonzert e-Moll; ヴァイオリン協奏曲; Violinski koncert; Vioolconcert; کنسرتو ویلن در می مینور (مندلسون); 小提琴协奏曲; Violin Concerto (Mendelssohn); 小提琴協奏曲孟德爾頌; Violinkonsert; Houslový koncert e moll; Concerto para violino; Violinkoncert i e-mol; קונצ'רטו לכינור במי מינור; Kunċert għal vjolin u orkestra fil-Mi minuri, op. 64; Koncertas smuikui (Mendelsonas); Konserto Biola dalam E Minor; Violonkonĉerto en E-minoro",
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"Name Aliases": "멘델스존 바이올린 협주곡; 멘델스존 바이올린협주곡; Concierto para violin; Concierto para violín nº 2; Concierto para violín n.º 2; Concierto para violin n 2; Concierto para violin nº 2; Concierto para violin n.º 2; Concierto para violin nº2 de Mendelssohn; Concierto para violín n 2; Concierto para violin n 2 de Mendelssohn; Concierto para violín n 2 de Mendelssohn; Concierto para violin n. 2; Concierto para violín n. 2; Concierto para violín nº2 de Mendelssohn; ไวโอลินคอนแชร์โต ในบันไดเสียง อี ไมเนอร์; Concert per a violí de Mendelssohn; Mendelssohnin viulukonsertto; Violinkonzert; Violinkonzert e-Moll op. 64; メンコン; メン・コン; Violinski koncert- Mendelssohn; Vioolconcert in e-klein; Vioolconcert (Mendelssohn-Bartholdy); concerto n° 2 pour violon et orchestre en mi mineur; concerto pour violon n° 2 de Mendelssohn; concerto n° 2 pour violon et orchestre; concerto n° 2 pour violon; concerto pour violon n° 2; concerto pour violon et orchestre n° 2 de Mendelssohn; Violin Concerto in E Minor, Op. 64; קונצ'רטו לכינור במי מינור, אופוס 64; Konserto Biola dalam E Minor, Op. 64",
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"Authorities": "WorldCat; Wikipedia; LCCN: n91030067; GND: 300101902",
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"Composer": "Mendelssohn, Felix",
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"Opus/Catalogue NumberOp./Cat. No.": "Op.64 ; MWV O 14",
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"I-Catalogue NumberI-Cat. No.": "IFM 196",
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"Key": "E minor",
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"Movements/SectionsMov'ts/Sec's": "3 movements:\nAllegro molto appassionato (528 bars)\nAndante - Allegretto non troppo (123 bars)\nAllegro molto vivace (234 bars)",
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"Year/Date of CompositionY/D of Comp.": "1838-1844 (Sept. 16), rev.1845",
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"First Performance.": "1845-03-13 in Leipzig, Saal des Gewandhauses\nFerdinand David (violin), Gewandhaus orchestra, Niels Gade (conductor)",
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"First Publication.": "1845 – Leipzig: Breitkopf und Härtel // London: J. J. Ewer & Co. // Milan: J. Ricordi\n(Hofmeister's Monatsbericht (1845), p.98)",
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"Dedication": "Ferdinand David",
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"Average DurationAvg. Duration": "30 minutes",
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"Composer Time PeriodComp. Period": "Romantic",
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"Piece Style": "Romantic",
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"Instrumentation": "violin, orchestra",
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"InstrDetail": "18 parts \n2 flutes, 2 oboes, 2 clarinets, 2 bassoons2 horns, 2 trumpets, timpani, strings",
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"Related Works": "Grande Allegro di Concerto by BottesiniAnalytical studies for Mendelssohn's Violin Concerto by Ševčík",
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"Discography": "MusicBrainz",
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"External Links": "Wikipedia articleAll Music Guide",
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"id": "IMSLP913207"
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}
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```
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For MusicScore-400 subset, user can use the following method in your dataset definition:
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```python
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from torch.util.data import Dataset
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import json
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class MusicScore(Dataset):
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def __init__(self):
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self.meta_path = "/path/to/your/metadata"
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with open(self.meta_path, 'r') as f:
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self.meta_json = json.load(f)
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def __getitem__(self, index):
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example = {}
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image_path = self.instance_data_root[index % self.num_instance_images]
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...
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score_id = image_path.split("_")[0]
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try:
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meta = next(item for item in self.meta_json if item['id'] == score_id)
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except StopIteration:
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print(f"Metadata with score_id {score_id} cannot be found")
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raise ValueError
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composer, instrumentation, piece_style, key, genre = meta["Composer"], meta["Instrumentation"], meta["Piece Style"], meta["key"], meta["genre"]
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example["caption"] = (
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f"a music score, composer is {composer}, instrumentation is {instrumentation}, piece style is {piece_style}, key is {key}, genre is {genre}"
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)
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return example
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```
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## Citation
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```bibtex
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@misc{lin2024musicscore,
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title={MusicScore: A Dataset for Music Score Modeling and Generation},
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author={Yuheng Lin and Zheqi Dai and Qiuqiang Kong},
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year={2024},
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journal={arXiv preprint arXiv:2406.11462},
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}
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```
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