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Merge branch 'mir-dataset-loaders:master' into master
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jimearruti authored Nov 10, 2022
2 parents 84f3c17 + a5db106 commit 23d398a
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2 changes: 1 addition & 1 deletion .github/PULL_REQUEST_TEMPLATE/new_loader.md
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Expand Up @@ -19,7 +19,7 @@ Please include the following information at the top level docstring for the data
- [ ] Run the script on the canonical version of the dataset and save the index in `mirdata/indexes/` e.g. `my_dataset_index.json`.
- [ ] Create a module in mirdata, e.g. `mirdata/my_dataset.py`
- [ ] Create tests for your loader in `tests/datasets/`, e.g. `test_my_dataset.py`
- [ ] Add your module to `docs/source/mirdata.rst` and `docs/source/quick_reference.rst`
- [ ] Add your module to `docs/source/mirdata.rst` and `docs/source/table.rst`
- [ ] Run `tests/test_full_dataset.py` on your dataset.

If your dataset **is not fully downloadable** there are two extra steps you should follow:
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16 changes: 16 additions & 0 deletions docs/source/mirdata.rst
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Expand Up @@ -91,6 +91,22 @@ da_tacos
:inherited-members:


filosax
^^^^^^^

.. automodule:: mirdata.datasets.filosax
:members:
:inherited-members:


four_way_tabla
^^^^^^^^^^^^^^

.. automodule:: mirdata.datasets.four_way_tabla
:members:
:inherited-members:


freesound_one_shot_percussive_sounds
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

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20 changes: 20 additions & 0 deletions docs/source/table.rst
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Expand Up @@ -109,6 +109,26 @@
- .. image:: https://licensebuttons.net/l/by-sa/4.0/80x15.png
:target: https://creativecommons.org/licenses/by-sa/4.0

* - Filosax
- - audio: 🔑
- annotations: 🔑
- midi: 🔑
- - :ref:`f0`
- :ref:`beats`
- :ref:`chords`
- :ref:`tempo`
- :ref:`notes`
- 48
- ❌

* - Four-Way Tabla Stroke
- - audio: ✅
- annotations: ✅
- - :ref:`tags`
- 236
- .. image:: https://licensebuttons.net/l/by-sa/4.0/80x15.png
:target: https://creativecommons.org/licenses/by-sa/4.0

* - Freesound One-Shot Percussive Sounds
- - audio: ✅
- annotations: ✅
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4 changes: 2 additions & 2 deletions docs/source/tutorial.rst
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Expand Up @@ -359,12 +359,12 @@ The following is a simple example of a generator that can be used to create a te
import mirdata
import numpy as np
import tensorflow as tf
import tensorflow as tf
def orchset_generator():
# using the default data_home
orchset = mirdata.initialize("orchset")
track_ids = orchset.track_ids()
track_ids = orchset.track_ids
for track_id in track_ids:
track = orchset.track(track_id)
audio_signal, sample_rate = track.audio_mono
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