snippets for MIREX AME task
- Salamon, melodia
- Durrieu, separateLeadStereo
Bosch, SourceFilterContoursMelodyKum, MelodyExtraction_MCDNN- Bittner, ismir2017-deepsalience
- Hsieh, Melody-extraction-with-melodic-segnet
- Kum, melodyExtraction_JDC
- Basaran, ismir2018_dominant_melody_estimation
- Lu, Vocal-Melody-Extraction
- MedleyDB (vocal/instrumental)
- RWC Popular, RWC Royalty free
- ADC 2004 (vocal/instrumental)
- Orchset (instrumental)
- Mirex-05 (vocal/instrumental)
- iKala
Except for the requirements needed by the algorithms repos above, the code use Python 3.6 or higher version, and requirements is listed in requirements.txt
. You could install the requirements with command pip install -r requirements.txt
.
Since this repo does not include any dataset files and algorithms repos, you should have download them independently and configure the path to the datasets and algorithms in the configs/configs.py
.
train the proposed model.
Usage: train.py [OPTIONS]
Options:
--resume BOOLEAN resume training state from .pkl file
--debug BOOLEAN use small dataset to debug faster
--help Show this message and exit.
inference using the trained model. Pretrained models can be downloaded from google drive, download and put them in the data/
folder.
Usage: predict.py [OPTIONS] AUDIOFILE [MELFILE]
Options:
--model TEXT pretrained model path
--cpu BOOLEAN use when have no cuda support
--help Show this message and exit.
example: python predict.py <path-to-input-audio-file> <path-of-output-csv-file>
evaluate state-of-the-art algorithms on various datasets.
Usage: evalAlgos.py [OPTIONS]
Options:
--force BOOLEAN overwrite evaluation results
--dataset TEXT using specific dataset
--algorithm TEXT using specific algorithm
--help Show this message and exit.
a convenient command line interface for calling algorithms.
Usage: algorithmsCLI.py [OPTIONS] ALGO AUDIOFILE [MELFILE]
Options:
--help Show this message and exit.