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alibabasglab
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•
5db2663
1
Parent(s):
31adb1a
Update basis.py
Browse files
basis.py
CHANGED
@@ -14,7 +14,6 @@ class ScoreBasis:
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depending on the score."""
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# imports
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#import soundfile as sf
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import resampy
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from museval.metrics import Framing
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@@ -29,6 +28,8 @@ class ScoreBasis:
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for index, audio in enumerate(audios):
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audio = resampy.resample(audio, data['rate'], score_rate, axis=0)
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audios[index] = audio
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if window is not None:
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framer = Framing(window * score_rate, window * score_rate, maxlen)
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@@ -40,74 +41,5 @@ class ScoreBasis:
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else:
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result = self.windowed_scoring(audios, score_rate)
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return result
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"""
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audios = []
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maxlen = 0
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if isinstance(test_files, str):
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test_files = [test_files]
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print(f'test_files: {test_files}')
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if not self.intrusive and len(test_files) > 1:
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if self.verbose:
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print(' [%s] is non-intrusive. Processing first file only'
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% self.name)
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test_files = [test_files[0],]
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for file in test_files:
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# Loading sound file
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if isinstance(file, str):
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audio, rate = sf.read(file, always_2d=True)
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else:
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rate = array_rate
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if rate is None:
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raise ValueError('Sampling rate needs to be specified '
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'when feeding numpy arrays.')
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audio = file
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# Standardize shapes
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if len(audio.shape) == 1:
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audio = audio[:, None]
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if len(audio.shape) != 2:
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raise ValueError('Please provide 1D or 2D array, received '
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'{}D array'.format(len(audio.shape)))
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if self.fixed_rate is not None and rate != self.fixed_rate:
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if self.verbose:
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print(' [%s] preferred is %dkHz rate. resampling'
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% (self.name, self.fixed_rate))
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audio = resampy.resample(audio, rate, self.fixed_rate, axis=0)
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rate = self.fixed_rate
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if self.mono and audio.shape[1] > 1:
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if self.verbose:
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print(' [%s] only supports mono. Will use first channel'
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% self.name)
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audio = audio[..., 0, None]
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if self.mono:
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audio = audio[..., 0]
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maxlen = max(maxlen, audio.shape[0])
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audios += [audio]
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audio = audios[1]
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audio[:maxlen-320] = audio[320:]
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audios[1] = audio
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for index, audio in enumerate(audios):
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if audio.shape[0] != maxlen:
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new = np.zeros((maxlen,) + audio.shape[1:])
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new[:audio.shape[0]] = audio
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audios[index] = new
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if self.window is not None:
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framer = Framing(self.window * rate,
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self.hop * rate, maxlen)
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nwin = framer.nwin
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result = {}
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for (t, win) in enumerate(framer):
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result_t = self.test_window([audio[win] for audio in audios],
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rate)
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#or metric in result_t.keys():
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# if metric not in result.keys():
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# result[metric] = np.empty(nwin)
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# result[metric][t] = result_t[metric]
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result[t] = result_t
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else:
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result = self.test_window(audios, rate)
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return result
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"""
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depending on the score."""
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# imports
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import resampy
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from museval.metrics import Framing
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for index, audio in enumerate(audios):
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audio = resampy.resample(audio, data['rate'], score_rate, axis=0)
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audios[index] = audio
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data['rate'] = score_rate
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data['audio'] = audios
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if window is not None:
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framer = Framing(window * score_rate, window * score_rate, maxlen)
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else:
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result = self.windowed_scoring(audios, score_rate)
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return result
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