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Error code: DatasetGenerationCastError Exception: DatasetGenerationCastError Message: An error occurred while generating the dataset All the data files must have the same columns, but at some point there are 1 new columns ({'model'}) This happened while the csv dataset builder was generating data using hf://datasets/wearemusicai/moisesdb/benchmark/oracle4.csv (at revision 7577c73577f3ba0c9c13a170e2557713619c41ce) Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations) Traceback: Traceback (most recent call last): File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2011, in _prepare_split_single writer.write_table(table) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 585, in write_table pa_table = table_cast(pa_table, self._schema) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2302, in table_cast return cast_table_to_schema(table, schema) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2256, in cast_table_to_schema raise CastError( datasets.table.CastError: Couldn't cast Unnamed: 0: int64 track_id: string model: string stem: string sdr: double -- schema metadata -- pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 820 to {'Unnamed: 0': Value(dtype='int64', id=None), 'track_id': Value(dtype='string', id=None), 'stem': Value(dtype='string', id=None), 'sdr': Value(dtype='float64', id=None)} because column names don't match During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1321, in compute_config_parquet_and_info_response parquet_operations = convert_to_parquet(builder) File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 935, in convert_to_parquet builder.download_and_prepare( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1027, in download_and_prepare self._download_and_prepare( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1122, in _download_and_prepare self._prepare_split(split_generator, **prepare_split_kwargs) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1882, in _prepare_split for job_id, done, content in self._prepare_split_single( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2013, in _prepare_split_single raise DatasetGenerationCastError.from_cast_error( datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset All the data files must have the same columns, but at some point there are 1 new columns ({'model'}) This happened while the csv dataset builder was generating data using hf://datasets/wearemusicai/moisesdb/benchmark/oracle4.csv (at revision 7577c73577f3ba0c9c13a170e2557713619c41ce) Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Unnamed: 0
int64 | track_id
string | stem
string | sdr
float64 |
---|---|---|---|
0 | 014f3712-293b-42af-9f29-0ed1785be792 | drums | 14.063471 |
1 | 0d528a19-cb0f-4421-b250-444f9343e51c | drums | 9.744113 |
2 | 1f98fe4d-26c7-460f-9f68-33964bc4d8d3 | drums | 12.559717 |
3 | 2c020edb-5947-4fa7-afea-ebc592cea683 | drums | 12.554443 |
4 | 3c3b5fdb-f15e-4ba4-884a-b083ce2426c6 | drums | 12.258883 |
5 | 4a896cde-57c6-4646-b610-1b0b654d0349 | drums | 14.873862 |
6 | 6681f493-c996-424a-9bdb-c671912ea9db | drums | 9.450497 |
7 | 73efd911-79c3-4235-a4ae-45b41d6997b9 | drums | 8.126162 |
8 | 8427760a-b82e-4136-8f12-dfd53cad9bc9 | drums | 11.663337 |
9 | 95378cf3-e939-42e0-b486-ebf2ca951664 | drums | 8.960332 |
10 | ad9bbefc-8762-46c9-b847-da14b10802b6 | drums | 11.812558 |
11 | bdcc429e-ed95-40d3-a1af-bad268d66b25 | drums | 10.619111 |
12 | d4262245-3143-4c05-8423-6cbdc6253042 | drums | 8.350298 |
13 | e37cdb09-e648-4e9b-bc06-d178a964161c | drums | 10.71603 |
14 | f76e2c13-9a9a-4cac-b6dd-45b5111aac6d | drums | 9.598362 |
15 | 01c8ba69-8eee-485b-bab0-41a76f9e8892 | drums | 10.121008 |
16 | 0e0d57cd-8662-4091-86d4-ed3e35d04ef6 | drums | 14.613385 |
17 | 1fc37390-1769-452d-9bea-19025be4c467 | drums | 10.375368 |
18 | 2d39a32d-5993-4f66-89ff-bf9dabb8e45b | drums | 14.005346 |
19 | 3c557409-3a34-43c2-9159-5421bbad5ecb | drums | 10.1493 |
20 | 4b9f86f4-23e4-458b-839e-8a63b584bea3 | drums | 12.895807 |
21 | 69dff382-cfcb-457c-98e5-978450e1b76a | drums | 13.688639 |
22 | 747d5c98-665b-4470-a696-7a6cf6968ef1 | drums | 8.933956 |
23 | 87a5da23-f17b-44da-accf-c04832f81a14 | drums | 11.465437 |
24 | 9653a690-c28c-4e8f-962e-ff7ed18b8ee9 | drums | 12.962962 |
25 | adb5e3fd-d039-42e4-b09b-fd0784fa0c82 | drums | 8.202137 |
26 | bdd109ec-d5dd-4d91-92ad-66b679518026 | drums | 9.335252 |
27 | d45bb3a6-eb80-44b3-b2ef-56cc9d5b4914 | drums | 12.858176 |
28 | e3ab3975-033b-40e2-b538-09396b3d4244 | drums | 9.176045 |
29 | f97e0ccd-e2a1-4da9-b8b8-c58e11adc4d9 | drums | 9.404155 |
30 | 028c6f6a-f4f6-4795-84f2-a81222b38e7e | drums | 8.961246 |
31 | 0f5fb60c-51d4-4618-871d-650c9e927b79 | drums | 12.630867 |
32 | 212bb137-fd01-465e-80f3-a890fb0ebcdd | drums | 10.921397 |
33 | 2dc237cd-1637-46f0-8f58-ca68dc6f6031 | drums | 7.961818 |
34 | 3e389000-8fdc-4b63-b8b8-ab044273790d | drums | 15.310251 |
35 | 4cbd6c36-87a2-4d50-86e3-52d39b98fad3 | drums | 8.482244 |
36 | 6a67c964-4514-4bdd-86d4-e290e67ab593 | drums | 11.598865 |
37 | 7524054e-dc67-47e0-8c26-ea1d4d70d2fb | drums | 10.736233 |
38 | 8804c154-6294-481a-ad63-bc61162cae2f | drums | 12.344469 |
39 | 97b07e0e-274e-4212-a66b-44210a48724d | drums | 9.318475 |
40 | aefc1609-976b-423e-8516-f7d588d64ff7 | drums | 12.518002 |
41 | c228818e-eabe-434b-9d60-2fb84a6c5b2a | drums | 10.483864 |
42 | d4df499c-e394-4753-b459-e167e6a58bad | drums | 8.524217 |
43 | e4de8632-6f69-4c63-8081-f4c2b77b40df | drums | 8.524276 |
44 | f9a1d21b-bfc7-45e1-b744-c57d0a0880c3 | drums | 7.112644 |
45 | 02ee37da-eea3-42b4-83bf-ab7f243afa13 | drums | 12.924012 |
46 | 11845abc-8ca3-4fb2-bd84-521aeeff56f4 | drums | 14.982256 |
47 | 215391aa-1168-42dd-9cab-f8b0c6ff566b | drums | 11.315831 |
48 | 2e5d996d-43f3-4359-b7c5-afebe9997556 | drums | 14.949336 |
49 | 3e41f238-7c48-4a42-ba70-5ee39824a844 | drums | 9.299854 |
50 | 524ab371-f6c6-4ff7-b896-e83750c8bef7 | drums | 11.223104 |
51 | 6b168ae6-9d8a-4dc2-9d27-898e6871bf8b | drums | 13.430676 |
52 | 75be2864-8b5f-45a1-ae09-6ba10f070f33 | drums | 8.43942 |
53 | 88b545e5-4d06-4d55-a306-1bd3a2915ee5 | drums | 9.698023 |
54 | 9ac2612b-e25f-4d27-8d43-b957e7e5a74b | drums | 12.714972 |
55 | afca84b2-0277-4b1b-8696-5f14543f338c | drums | 9.187442 |
56 | c2330200-ad8e-4848-8c2b-b70612f4b80e | drums | 11.640663 |
57 | d4fe2408-c123-4739-93bb-22f558ae99d7 | drums | 12.444949 |
58 | e62afdcd-0c96-4bee-80c7-1c17b897a6d7 | drums | 7.624206 |
59 | f9e58f4d-e361-4598-9c9a-d0a83529cc68 | drums | 9.053375 |
60 | 04204031-4f98-44ba-9c47-98c2f2e6b8fc | drums | 9.52111 |
61 | 125fc63d-9b69-4170-a46a-42c91bc28446 | drums | 9.854384 |
62 | 21ce1331-6066-4ff4-9a54-f6f62bb5fb0d | drums | 14.374102 |
63 | 30cfc60a-5a57-4000-a05e-65006c8f6f74 | drums | 8.000004 |
64 | 3e656eec-84d4-4a45-b410-d3817d849f92 | drums | 7.864262 |
65 | 53808b95-cfe9-461d-a113-ffadf32817a1 | drums | 11.651188 |
66 | 6b48c9de-fa34-4635-9718-04e01a03a0fe | drums | 6.743264 |
67 | 763641c7-488f-4959-a554-fdbce9582644 | drums | 13.682885 |
68 | 89c515c9-5e93-4cb4-9806-20432d2d074d | drums | 11.779605 |
69 | 9c8a5c66-f6d8-4425-8671-6b7aa6a2663b | drums | 8.374802 |
70 | b207da3d-4baf-485a-98e1-657602479b3a | drums | 9.829205 |
71 | c2ba72ec-cf74-4155-a7c1-ddd921ac41d3 | drums | 13.402029 |
72 | d624037a-1a76-4dd9-9e60-4ba380748a0b | drums | 12.539806 |
73 | e9336d31-c0df-4c91-be2b-7c4420c9cd34 | drums | 9.563725 |
74 | fa46f72c-696d-45bc-bcc5-2b3305800565 | drums | 11.736802 |
75 | 045dcfd1-e960-4332-80cc-fdacc4a7c6a7 | drums | 12.79642 |
76 | 13f233aa-a2e5-4683-8533-2f1e344b55b4 | drums | 5.400906 |
77 | 22d265ef-ee2b-4aba-8d60-c3430295cd6d | drums | 9.033714 |
78 | 312bec8d-1c61-43e0-924a-1fb87ddc3e41 | drums | 9.834611 |
79 | 3e7985e5-408f-4cf8-92b9-b9f62f738dd3 | drums | 11.618738 |
80 | 553048ce-7afd-4e0e-b4cb-4896620287a1 | drums | 13.665794 |
81 | 6c70d5e0-5972-444a-86f8-a558dbb92d92 | drums | 12.787972 |
82 | 765d5131-afd9-4ad7-8786-8bef5705c1c2 | drums | 11.944251 |
83 | 89f2c781-5c67-4508-a2d6-236744b8c197 | drums | 7.589781 |
84 | 9ce23a79-20eb-431a-80d2-eda3260ef503 | drums | 9.560091 |
85 | b876b54b-6007-4d36-a6f4-efed8829d5fc | drums | 8.793537 |
86 | c6d73235-1dd5-4085-a3b3-50a3466c6168 | drums | 11.290126 |
87 | d7d28204-a8ac-4c2b-bb3c-c941f4a00b85 | drums | 12.181682 |
88 | ea29ab4d-7f72-4331-b2a4-d3945c754211 | drums | 10.963622 |
89 | faad432d-6ad0-492d-96f1-321eeb9685b5 | drums | 15.980753 |
90 | 046ab651-a333-46e1-9d27-ab14ee036c42 | drums | 9.925768 |
91 | 152d4f5d-4093-4fa4-a4a4-8a9b3502d89d | drums | 10.554828 |
92 | 22ea41a3-1766-4a76-8071-380b27f1869a | drums | 10.178224 |
93 | 322f4d9d-b0c9-4ab3-9e30-544a25331ffd | drums | 11.496467 |
94 | 3f5233cb-57fa-4772-b389-f295a6f416ae | drums | 7.7859 |
95 | 5640831d-7853-4d06-8166-988e2844b652 | drums | 10.006413 |
96 | 6cd44645-ed19-4ecc-a57c-58d400005b29 | drums | 17.218605 |
97 | 78ef22ce-472f-4f82-8656-16df73b9465f | drums | 10.884977 |
98 | 8a307c5d-9d65-4f1c-a024-5eaeff1faa34 | drums | 9.796275 |
99 | 9eb8bc50-cffb-4c19-be0e-d27423e3e102 | drums | 8.877535 |
MoisesDB
Moises Dataset for Source Separation
Dataset Summary
MoisesDB is a dataset for source separation. It provides a collection of tracks and their separated stems (vocals, bass, drums, etc.). The dataset is used to evaluate the performance of source separation algorithms.
Download the data
Please download the dataset at our research website, extract it and configure the environment variable MOISESDB_PATH
accordingly.
export MOISESDB_PATH=./moises-db-data
The directory structure should be
moisesdb:
moisesdb_v0.1
track uuid 0
track uuid 1
.
.
.
Install
You can install this package with
pip install git+https://github.com/moises-ai/moises-db.git
Usage
MoisesDB
After downloading and configuring the path for the dataset, you can create an instance of MoisesDB
to access the tracks. You can also provide the dataset path with the data_path
argument.
from moisesdb.dataset import MoisesDB
db = MoisesDB(
data_path='./moisesdb',
sample_rate=44100
)
The MoisesDB
object has iterator properties that you can use to access all files within the dataset.
n_songs = len(db)
track = db[0] # Returns a MoisesDBTrack object
MoisesDBTrack
The MoisesDBTrack
object holds information about a track in the dataset, perform on-the-fly mixing for stems and multiple sources within a stem.
You can access all the stems and mixture from the stem
and audio
properties. The stem
property returns a dictionary whith available stems as keys and nd.array
on values. The audio
property results in a nd.array
with the mixture.
track = db[0]
stems = track.stems # stems = {'vocals': ..., 'bass': ..., ...}
mixture track.audio # mixture = nd.array
The MoisesDBTrack
object also contains other non-audio information from the track such as:
track.id
track.provider
track.artist
track.name
track.genre
track.sources
track.bleedings
track.activity
The stems and mixture are computed on-the-fly. You can create a stems-only version of the dataset using the save_stems
method of the MoisesDBTrack
.
track = db[0]
path = './moises-db-stems/0'
track.save_stems(path)
Performance Evaluation
We run a few source separation algorithms as well as oracle methods to evaluate the performance of each track of the MoisesDB
. These results are located in csv
files at the benchmark
folder.
Citing
If you used the MoisesDB
dataset on your research, please cite the following paper.
@misc{pereira2023moisesdb,
title={Moisesdb: A dataset for source separation beyond 4-stems},
author={Igor Pereira and Felipe Araújo and Filip Korzeniowski and Richard Vogl},
year={2023},
eprint={2307.15913},
archivePrefix={arXiv},
primaryClass={cs.SD}
}
Licensing
MoisesDB
is distributed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0).
For the complete license terms, please visit: https://creativecommons.org/licenses/by-nc-sa/4.0/
See LICENSE file for details.
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