omnizart patch-cnn¶
Lists the detailed available options of each sub-commands.
transcribe¶
omnizart patch-cnn transcribe¶
Transcribe a single audio and output CSV and audio file.
The transcribed F0 contour will be stored in the <filename>_f0.csv file, where filename is the input file name. Also there will be another rendered audio file (with postfix <filename>_trans.wav) of the pitch contour for quick validation.
Supported modes are: Melody
omnizart patch-cnn transcribe [OPTIONS] INPUT_AUDIO
Options
- -m,--model-path<model_path>¶
Path to the pre-trained model or the supported transcription mode.
- -o,--output<output>¶
Path to output the prediction file (could be MIDI, CSV, …, etc.)
- Default
./
Arguments
- INPUT_AUDIO¶
Required argument
generate-feature¶
omnizart patch-cnn generate-feature¶
Pre-process the dataset for training.
omnizart patch-cnn generate-feature [OPTIONS]
Options
- -d,--dataset-path<dataset_path>¶
Required Path to the downloaded dataset
- -o,--output-path<output_path>¶
Path for saving the extracted feature. Default to the folder under the dataset.
- -n,--num-threads<num_threads>¶
Number of threads used for parallel feature extraction.
- Default
4
train-model¶
omnizart patch-cnn train-model¶
Train a new model or continue to train on a pre-trained model
omnizart patch-cnn train-model [OPTIONS]
Options
- -d,--feature-path<feature_path>¶
Required Path to the folder of extracted feature
- -m,--model-name<model_name>¶
Name for the output model (can be a path)
- -i,--input-model<input_model>¶
If given, the training will continue to fine-tune the pre-trained model.
- -e,--epochs<epochs>¶
Number of training epochs
- -s,--steps<steps>¶
Number of training steps of each epoch
- -vs,--val-steps<val_steps>¶
Number of validation steps of each epoch
- -b,--batch-size<batch_size>¶
Batch size of each training step
- -vb,--val-batch-size<val_batch_size>¶
Batch size of each validation step
- --early-stop<early_stop>¶
Stop the training if validation accuracy does not improve over the given number of epochs.