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Runtime error
fixed it breaking on some files, sorry!
Browse files- app.py +17 -9
- beat_manipulator/__pycache__/__init__.cpython-310.pyc +0 -0
- beat_manipulator/__pycache__/analyze.cpython-310.pyc +0 -0
- beat_manipulator/__pycache__/beatmap.cpython-310.pyc +0 -0
- beat_manipulator/__pycache__/effect.cpython-310.pyc +0 -0
- beat_manipulator/__pycache__/generate.cpython-310.pyc +0 -0
- beat_manipulator/__pycache__/image.cpython-310.pyc +0 -0
- beat_manipulator/__pycache__/main.cpython-310.pyc +0 -0
- beat_manipulator/__pycache__/mix.cpython-310.pyc +0 -0
- beat_manipulator/__pycache__/wrapper.cpython-310.pyc +0 -0
- beat_manipulator/image.py +7 -4
- beat_manipulator/main.py +3 -1
app.py
CHANGED
@@ -7,19 +7,27 @@ def _safer_eval(string:str) -> float:
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string = eval(''.join([i for i in string if i.isdecimal() or i in '.+-*/']))
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return string
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-
def BeatSwap(audiofile, pattern: str, scale:float, shift:float, caching:bool, variableBPM:bool):
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print(f'___ PATH = {audiofile} ___')
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scale=_safer_eval(scale)
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shift=_safer_eval(shift)
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if audiofile is not None:
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try:
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song=bm.song(path=audiofile, filename=audiofile.split('.')[-2][:-8]+'.'+audiofile.split('.')[-1], caching=caching)
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except Exception as e:
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print(e)
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song=bm.song(path=audiofile, caching=caching)
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else:
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lib = 'madmom.BeatDetectionProcessor' if variableBPM is False else 'madmom.BeatTrackingProcessor'
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song.beatmap.generate(lib=lib, caching=caching)
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try:
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song.beat_image.generate()
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image = song.beat_image.combined
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@@ -28,17 +36,17 @@ def BeatSwap(audiofile, pattern: str, scale:float, shift:float, caching:bool, va
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image = np.clip(cv2.resize(image, (y,y), interpolation=cv2.INTER_NEAREST).T/255, -1, 1)
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#print(image)
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except Exception as e:
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print(e)
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image = [[0
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song.quick_beatswap(output=None, pattern=pattern, scale=
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song.audio = (np.clip(np.asarray(song.audio), -1, 1) *
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#song.write_audio(output=bm.outputfilename('',song.filename, suffix=' (beatswap)'))
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print('___ SUCCESS ___')
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return ((song.samplerate, song.audio), image)
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audiofile=Audio(source='upload', type='filepath')
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patternbox = Textbox(label="Pattern, comma separated:", placeholder="1, 3, 2, 4!", value="1,
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scalebox = Textbox(value=
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shiftbox = Textbox(value=0, label="Beatmap shift, in beats (applies before scaling):", placeholder=0, lines=1)
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cachebox = Checkbox(value=True, label="""Enable caching beatmaps. If enabled, a text file with the beatmap will be saved to the server (your PC if you are running locally), so that beatswapping for the second time doesn't have to generate the beatmap again.
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string = eval(''.join([i for i in string if i.isdecimal() or i in '.+-*/']))
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return string
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+
def BeatSwap(audiofile, pattern: str = 'test', scale:float = 1, shift:float = 0, caching:bool = True, variableBPM:bool = False):
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print()
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print(f'___ PATH = {audiofile} ___')
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if scale == '' or scale is None: scale = 1
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if shift == '' or shift is None: shift = 0
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if pattern == '' or pattern is None: pattern = 'test'
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scale=_safer_eval(scale)
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shift=_safer_eval(shift)
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if audiofile is not None:
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try:
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song=bm.song(path=audiofile, filename=audiofile.split('.')[-2][:-8]+'.'+audiofile.split('.')[-1], caching=caching)
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except Exception as e:
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print(f'Failed to load audio, retrying: {e}')
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song=bm.song(path=audiofile, caching=caching)
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else:
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print(f'Audiofile is {audiofile}')
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return
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lib = 'madmom.BeatDetectionProcessor' if variableBPM is False else 'madmom.BeatTrackingProcessor'
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song.beatmap.generate(lib=lib, caching=caching)
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song.beatmap.shift(shift)
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song.beatmap.scale(scale)
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try:
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song.beat_image.generate()
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image = song.beat_image.combined
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image = np.clip(cv2.resize(image, (y,y), interpolation=cv2.INTER_NEAREST).T/255, -1, 1)
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#print(image)
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except Exception as e:
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print(f'Image generation failed: {e}')
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image = np.asarray([[0.5,-0.5],[-0.5,0.5]])
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song.quick_beatswap(output=None, pattern=pattern, scale=1, shift=0, lib=lib)
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song.audio = (np.clip(np.asarray(song.audio), -1, 1) * 32766).astype(np.int16).T
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#song.write_audio(output=bm.outputfilename('',song.filename, suffix=' (beatswap)'))
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print('___ SUCCESS ___')
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return ((song.samplerate, song.audio), image)
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audiofile=Audio(source='upload', type='filepath')
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patternbox = Textbox(label="Pattern, comma separated:", placeholder="1, 3, 2, 4!", value="1, 2!", lines=1)
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scalebox = Textbox(value=1, label="Beatmap scale, beatmap's beats per minute will be multiplied by this:", placeholder=1, lines=1)
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shiftbox = Textbox(value=0, label="Beatmap shift, in beats (applies before scaling):", placeholder=0, lines=1)
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cachebox = Checkbox(value=True, label="""Enable caching beatmaps. If enabled, a text file with the beatmap will be saved to the server (your PC if you are running locally), so that beatswapping for the second time doesn't have to generate the beatmap again.
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beat_manipulator/__pycache__/__init__.cpython-310.pyc
DELETED
Binary file (322 Bytes)
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beat_manipulator/__pycache__/analyze.cpython-310.pyc
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Binary file (1.65 kB)
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beat_manipulator/__pycache__/beatmap.cpython-310.pyc
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Binary file (13.5 kB)
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beat_manipulator/__pycache__/effect.cpython-310.pyc
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Binary file (3.5 kB)
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beat_manipulator/__pycache__/generate.cpython-310.pyc
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Binary file (1.39 kB)
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beat_manipulator/__pycache__/image.cpython-310.pyc
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Binary file (7.19 kB)
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beat_manipulator/__pycache__/main.cpython-310.pyc
DELETED
Binary file (27.4 kB)
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beat_manipulator/__pycache__/mix.cpython-310.pyc
DELETED
Binary file (1.28 kB)
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beat_manipulator/__pycache__/wrapper.cpython-310.pyc
DELETED
Binary file (6.36 kB)
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beat_manipulator/image.py
CHANGED
@@ -134,23 +134,26 @@ class beat_image(image):
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# maximum is needed to make the array homogeneous
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maximum=self.beatmap[0]
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values=[]
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values.append(self.beatmap[0])
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for i in range(len(self.beatmap)-1):
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self.image[0].append(self.audio[0][self.beatmap[i]:self.beatmap[i+1]])
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self.image[1].append(self.audio[1][self.beatmap[i]:self.beatmap[i+1]])
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maximum = max(self.beatmap[i+1]-self.beatmap[i], maximum)
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values.append(self.beatmap[i+1]-self.beatmap[i])
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if 'max' in mode: norm=maximum
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elif 'med' in mode: norm=numpy.median(values)
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elif 'av' in mode: norm=numpy.average(values)
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for i in range(len(self.image[0])):
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beat_diff=
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if beat_diff>0:
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self.image[0][i].extend([numpy.nan]*beat_diff)
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self.image[1][i].extend([numpy.nan]*beat_diff)
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elif beat_diff<0:
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self.image[0][i]=self.image[0][i][:beat_diff]
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self.image[1][i]=self.image[1][i][:beat_diff]
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self.image=numpy.asarray(self.image)*255
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self.mask = self.image == numpy.nan
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self.image=numpy.nan_to_num(self.image)
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# maximum is needed to make the array homogeneous
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maximum=self.beatmap[0]
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values=[]
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#print(self.beatmap)
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values.append(self.beatmap[0])
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for i in range(len(self.beatmap)-1):
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self.image[0].append(self.audio[0][self.beatmap[i]:self.beatmap[i+1]])
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self.image[1].append(self.audio[1][self.beatmap[i]:self.beatmap[i+1]])
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maximum = max(self.beatmap[i+1]-self.beatmap[i], maximum)
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values.append(self.beatmap[i+1]-self.beatmap[i])
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if 'max' in mode: norm=int(maximum)
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elif 'med' in mode: norm=int(numpy.median(values))
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elif 'av' in mode: norm=int(numpy.average(values))
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for i in range(len(self.image[0])):
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beat_diff=norm-len(self.image[0][i])
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if beat_diff>0:
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self.image[0][i].extend([numpy.nan]*beat_diff)
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self.image[1][i].extend([numpy.nan]*beat_diff)
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#print(0, len(self.image[0][i]), len(self.image[1][i]))
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elif beat_diff<0:
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self.image[0][i]=self.image[0][i][:beat_diff]
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self.image[1][i]=self.image[1][i][:beat_diff]
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#print(1, len(self.image[0][i]), len(self.image[1][i]))
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self.image=numpy.asarray(self.image)*255
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self.mask = self.image == numpy.nan
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self.image=numpy.nan_to_num(self.image)
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beat_manipulator/main.py
CHANGED
@@ -768,10 +768,12 @@ def beatswap(pattern: str, audio = None, scale: float = 1, shift: float = 0, out
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audio.quick_beatswap(pattern = pattern, scale=scale, shift=shift, output=output)
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return audio.path
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def generate_beat_image(audio = None, output='', samplerate = None, bmap = None, log = True, ext='png', maximum=4096):
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audio = _tosong(audio=audio, bmap=bmap, samplerate=samplerate, log=log)
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output = _outputfilename(output=output, filename=audio.path, ext=ext, suffix = '')
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audio.beatmap.generate()
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audio.beat_image.generate()
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audio.beat_image.write(output=output, maximum = maximum)
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return output
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audio.quick_beatswap(pattern = pattern, scale=scale, shift=shift, output=output)
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return audio.path
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def generate_beat_image(audio = None, scale: float = 1, shift: float = 0, output='', samplerate = None, bmap = None, log = True, ext='png', maximum=4096):
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audio = _tosong(audio=audio, bmap=bmap, samplerate=samplerate, log=log)
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output = _outputfilename(output=output, filename=audio.path, ext=ext, suffix = '')
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audio.beatmap.generate()
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audio.beatmap.scale(scale)
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audio.beatmap.shift(shift)
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audio.beat_image.generate()
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audio.beat_image.write(output=output, maximum = maximum)
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return output
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