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"""Given a correspondence.csv file from alignment.py, this script will set up (copy and crop)
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the dataset files."""
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import argparse
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import pandas as pd
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import os
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import librosa
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from shutil import copyfile
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import numpy as np
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from pathlib import Path
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def clip_and_copy_audio(in_path, out_path, start=None, end=None, padding=0.5):
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"""
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Clip the given wav file (if desired), and copy it to a new location.
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Parameters
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----------
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in_path : string
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Path of the input wav file.
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out_path : string
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Output path for the resulting wav file.
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start : float
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Starting time (in seconds) of the output file. (This many seconds will be clipped
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from the beginning of the input.) None for no start clipping.
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end : float
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Endd time (in seconds) for the output file. (The final sample in the output file
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will be the sample at this time in the input file.) None for no end clipping.
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padding : float
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Padding (in seconds) to add to the beginning of the piece if start is greater than
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this amount. That is, instead of shifting the audio at the start time to
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time 0, it is shifted to this time, and the beginning is padded with 0s. However, no
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sound will ever be shifted forward of its original time due to this value (so if
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padding > start, it is instead set to start).
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"""
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if np.isnan(start) and np.isnan(end):
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if in_path != out_path:
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copyfile(in_path, out_path)
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return
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s = 0.0 if np.isnan(start) else start
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dur = None if np.isnan(end) else end - s
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data, sr = librosa.core.load(in_path, sr=None, mono=False,
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offset=s,
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duration=dur)
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if s > 0:
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samples = int(sr * padding)
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if len(data.shape) == 1:
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zeros = np.zeros(samples)
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data = np.append(zeros, data)
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else:
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zeros = np.zeros((data.shape[0], samples))
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data = np.asfortranarray(np.concatenate( (zeros,data),axis=1))
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librosa.output.write_wav(out_path, y=data.astype(np.float32), sr=sr, norm=False)
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if __name__ == '__main__':
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parser = argparse.ArgumentParser(description='Initialize the performed_midi dataset by '
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'cutting maestro audio files and moving them into their correct locations.',
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formatter_class=argparse.ArgumentDefaultsHelpFormatter)
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parser.add_argument('-m', '--maestro', help='The location of the downloaded maestro data.',
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default='../maestro-v2.0.0', type=str)
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parser.add_argument('--metadata', help='The correspondence.csv metadata file.',
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default='metadata.csv', type=pd.read_csv)
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args = parser.parse_args()
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print("Cutting and copying maestro audio performances")
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counter = 0
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for idx, row in args.metadata.iterrows():
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if not row.isna()["maestro_audio_performance"]:
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try:
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maestro_path = str(Path(row["maestro_audio_performance"])).replace('{maestro}', str(args.maestro))
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clip_and_copy_audio(str(maestro_path),
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str(Path(row["audio_performance"])),
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start=row.start, end=row.end)
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except Exception as e:
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print("Failed for", idx,row["midi_performance"])
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print(e)
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counter+=1
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if counter%20 == 0:
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print("{}/520 completed".format(counter))
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