return options, args if __name__ == '__main__': opts, args = parse_args() if len(args) != 2: cmd = './' + os.path.basename(sys.argv[0]) + ' -h' os.system(cmd) sys.exit(1) if opts.generate_dot: essentia.translate(PitchExtractor, 'streaming_extractorpitch', dot_graph=True) elif opts.generate_cpp: essentia.translate(PitchExtractor, 'streaming_extractorpitch', dot_graph=False) # find out replay gain loader = EqloudLoader(filename=args[0], sampleRate=analysisSampleRate, downmix='mix') rgain = ReplayGain(applyEqloud=False) pool = essentia.Pool() loader.audio >> rgain.signal
return options, args if __name__ == '__main__': opts, args = parse_args() if len(args) != 2: cmd = './'+os.path.basename(sys.argv[0])+ ' -h' os.system(cmd) sys.exit(1) if opts.generate_dot: essentia.translate(RhythmDescriptorsExtractor, "streaming_extractorrhythmdescriptors", dot_graph=True) elif opts.generate_cpp: essentia.translate(RhythmDescriptorsExtractor, "streaming_extractorrhythmdescriptors", dot_graph=False) pool = essentia.Pool() loader = essentia.streaming.MonoLoader(filename=args[0]) rhythm = RhythmDescriptorsExtractor() loader.audio >> rhythm.signal for desc, output in rhythm.outputs.items(): output >> (pool, desc) essentia.run(loader) stats = ['mean', 'var', 'min', 'max', 'dmean', 'dmean2', 'dvar', 'dvar2'] poolStats = essentia.standard.PoolAggregator(defaultStats=stats)(pool) essentia.standard.YamlOutput(filename=args[1])(poolStats)
return options, args if __name__ == '__main__': opts, args = parse_args() if len(args) != 2: cmd = './'+os.path.basename(sys.argv[0])+ ' -h' os.system(cmd) sys.exit(1) if opts.generate_dot: essentia.translate(PanningExtractor, 'streaming_extractorpanning', dot_graph=True) elif opts.generate_cpp: essentia.translate(PanningExtractor, 'streaming_extractorpanning', dot_graph=False) pool = essentia.Pool() loader = AudioLoader(filename=args[0]) panExtractor = PanningExtractor() loader.audio >> panExtractor.signal loader.numberChannels >> None loader.sampleRate >> None panExtractor.panning_coefficients >> (pool, namespace + '.panning_coefficients') essentia.run(loader) essentia.standard.YamlOutput(filename=args[1])(pool)
return options, args if __name__ == '__main__': opts, args = parse_args() if len(args) != 2: cmd = './' + os.path.basename(sys.argv[0]) + ' -h' os.system(cmd) sys.exit(1) if opts.generate_dot: essentia.translate(SfxExtractor, 'streaming_extractorsfx', dot_graph=True) elif opts.generate_cpp: essentia.translate(SfxExtractor, 'streaming_extractorsfx', dot_graph=False) pool = essentia.Pool() loader = MonoLoader(filename=args[0]) sfx = SfxExtractor() loader.audio >> sfx.signal for desc, output in sfx.outputs.items(): output >> (pool, namespace + '.' + desc) essentia.run(loader)
(options, args) = parser.parse_args() return options, args if __name__ == '__main__': opts, args = parse_args() if len(args) != 2: cmd = './'+os.path.basename(sys.argv[0])+ ' -h' os.system(cmd) sys.exit(1) if opts.generate_dot: essentia.translate(TuningFrequencyExtractor, 'streaming_extractortuningfrequency', dot_graph=True) elif opts.generate_cpp: essentia.translate(TuningFrequencyExtractor, 'streaming_extractortuningfrequency', dot_graph=False) pool = essentia.Pool() loader = essentia.streaming.MonoLoader(filename=args[0]) tuning = TuningFrequencyExtractor() loader.audio >> tuning.signal tuning.tuningFrequency >> (pool, 'tuning_frequency') essentia.run(loader) stats = ['mean', 'var', 'min', 'max', 'dmean', 'dmean2', 'dvar', 'dvar2'] poolStats = essentia.standard.PoolAggregator(defaultStats=stats)(pool) essentia.standard.YamlOutput(filename=args[1])(poolStats)
self.outputs['mfcc'] = mfcc.mfcc if __name__ == '__main__': # Make sure the command was well-formed. if len(sys.argv) < 3: print 'Usage: extractor_mfcc.py <input audio filename> <output yaml filename>' sys.exit(1) # Loaders must be specified outside your composite algorithm. loader = essentia.streaming.MonoLoader(filename=sys.argv[1]) # We are using the default values of our parameters so we don't specify any keyword arguments. mfccex = ExtractorMfcc() p = essentia.Pool() # When connecting to/from your composite algorithm, use the names you declared in the # self.inputs and self.outputs dictionaries, respectively. loader.audio >> mfccex.audio mfccex.mfcc >> (p, 'mfcc') essentia.run(loader) # CompoxiteBase algorithms can be translated into c++ code and dot graphs # can also be generated: essentia.translate(ExtractorMfcc, # algorithm to be translated 'myExtractorMfcc', # output name for the c++ and dot generated files dot_graph=True) # whether dot file should be generated essentia.standard.YamlOutput(filename=sys.argv[2])(p)
(options, args) = parser.parse_args() return options, args if __name__ == '__main__': opts, args = parse_args() if len(args) != 2: cmd = './'+os.path.basename(sys.argv[0])+ ' -h' os.system(cmd) sys.exit(1) if opts.generate_dot: essentia.translate(LowLevelSpectralEqloudExtractor, 'streaming_extractorlowlevelspectraleqloud', dot_graph=True) elif opts.generate_cpp: essentia.translate(LowLevelSpectralEqloudExtractor, 'streaming_extractorlowlevelspectraleqloud', dot_graph=False) loader = EqloudLoader(filename=args[0], replayGain=-6) lowlevelExtractor = LowLevelSpectralEqloudExtractor() pool = essentia.Pool() loader.audio >> lowlevelExtractor.signal for desc, output in lowlevelExtractor.outputs.items(): output >> (pool, namespace + '.' + desc) essentia.run(loader) # compute aggregation on values:
return options, args if __name__ == '__main__': opts, args = parse_args() if len(args) != 2: cmd = './' + os.path.basename(sys.argv[0]) + ' -h' os.system(cmd) sys.exit(1) if opts.generate_dot: essentia.translate(LevelExtractor, 'streaming_extractorlevel', dot_graph=True) elif opts.generate_cpp: essentia.translate(LevelExtractor, 'streaming_extractorlevel', dot_graph=False) # find out replay gain: loader = EqloudLoader(filename=args[0], sampleRate=analysisSampleRate, downmix='mix') rgain = ReplayGain(applyEqloud=False) pool = essentia.Pool() loader.audio >> rgain.signal
return options, args if __name__ == '__main__': opts, args = parse_args() if len(args) != 2: cmd = './' + os.path.basename(sys.argv[0]) + ' -h' os.system(cmd) sys.exit(1) if opts.generate_dot: essentia.translate(LowLevelSpectralExtractor, 'streaming_extractorlowlevelspectral', dot_graph=True) elif opts.generate_cpp: essentia.translate(LowLevelSpectralExtractor, 'streaming_extractorlowlevelspectral', dot_graph=False) loader = MonoLoader(filename=args[0]) lowlevelExtractor = LowLevelSpectralExtractor() pool = essentia.Pool() loader.audio >> lowlevelExtractor.signal for desc, output in lowlevelExtractor.outputs.items(): output >> (pool, namespace + '.' + desc)
return options, args if __name__ == '__main__': opts, args = parse_args() if len(args) != 2: cmd = './'+os.path.basename(sys.argv[0])+ ' -h' os.system(cmd) sys.exit(1) if opts.generate_dot: essentia.translate(LevelExtractor, 'streaming_extractorlevel', dot_graph=True) elif opts.generate_cpp: essentia.translate(LevelExtractor, 'streaming_extractorlevel', dot_graph=False) # find out replay gain: loader = EqloudLoader(filename=args[0], sampleRate=analysisSampleRate, downmix='mix') rgain = ReplayGain(applyEqloud=False) pool = essentia.Pool() loader.audio >> rgain.signal rgain.replayGain >> (pool, 'replay_gain') essentia.run(loader)
return options, args if __name__ == '__main__': opts, args = parse_args() if len(args) != 2: cmd = './'+os.path.basename(sys.argv[0])+ ' -h' os.system(cmd) sys.exit(1) if opts.generate_dot: essentia.translate(TonalDescriptorsExtractor, 'streaming_extractortonaldescriptors', dot_graph=True) elif opts.generate_cpp: essentia.translate(TonalDescriptorsExtractor, 'streaming_extractortonaldescriptors', dot_graph=False) pool = essentia.Pool() loader = essentia.streaming.MonoLoader(filename=args[0]) tonalExtractor = TonalDescriptorsExtractor() loader.audio >> tonalExtractor.signal for desc, output in tonalExtractor.outputs.items(): output >> (pool, desc) essentia.run(loader) stats = ['mean', 'var', 'min', 'max', 'dmean', 'dmean2', 'dvar', 'dvar2'] poolStats = essentia.standard.PoolAggregator(defaultStats=stats)(pool) essentia.standard.YamlOutput(filename=args[1])(poolStats)
return options, args if __name__ == '__main__': opts, args = parse_args() if len(args) != 2: cmd = './'+os.path.basename(sys.argv[0])+ ' -h' os.system(cmd) sys.exit(1) if opts.generate_dot: essentia.translate(SfxExtractor, 'streaming_extractorsfx', dot_graph=True) elif opts.generate_cpp: essentia.translate(SfxExtractor, 'streaming_extractorsfx', dot_graph=False) pool = essentia.Pool() loader = MonoLoader(filename=args[0]) sfx = SfxExtractor() loader.audio >> sfx.signal for desc, output in sfx.outputs.items(): output >> (pool, namespace + '.' + desc) essentia.run(loader) # compute aggregation on values: stats = ['mean', 'var', 'min', 'max', 'dmean', 'dmean2', 'dvar', 'dvar2'] exceptions = {'lowlevel.mfcc' : ['mean', 'cov', 'icov']}
return options, args if __name__ == '__main__': opts, args = parse_args() if len(args) != 2: cmd = './' + os.path.basename(sys.argv[0]) + ' -h' os.system(cmd) sys.exit(1) if opts.generate_dot: essentia.translate(PanningExtractor, 'streaming_extractorpanning', dot_graph=True) elif opts.generate_cpp: essentia.translate(PanningExtractor, 'streaming_extractorpanning', dot_graph=False) pool = essentia.Pool() loader = AudioLoader(filename=args[0]) panExtractor = PanningExtractor() loader.audio >> panExtractor.signal loader.numberChannels >> None loader.sampleRate >> None panExtractor.panning_coefficients >> (pool, namespace + '.panning_coefficients')
if __name__ == '__main__': # Make sure the command was well-formed. if len(sys.argv) < 3: print 'Usage: extractor_mfcc.py <input audio filename> <output yaml filename>' sys.exit(1) # Loaders must be specified outside your composite algorithm. loader = essentia.streaming.MonoLoader(filename=sys.argv[1]) # We are using the default values of our parameters so we don't specify any keyword arguments. mfccex = ExtractorMfcc() p = essentia.Pool() # When connecting to/from your composite algorithm, use the names you declared in the # self.inputs and self.outputs dictionaries, respectively. loader.audio >> mfccex.audio mfccex.mfcc >> (p, 'mfcc') essentia.run(loader) # CompoxiteBase algorithms can be translated into c++ code and dot graphs # can also be generated: essentia.translate( ExtractorMfcc, # algorithm to be translated 'myExtractorMfcc', # output name for the c++ and dot generated files dot_graph=True) # whether dot file should be generated essentia.standard.YamlOutput(filename=sys.argv[2])(p)
return options, args if __name__ == '__main__': opts, args = parse_args() if len(args) != 2: cmd = './' + os.path.basename(sys.argv[0]) + ' -h' os.system(cmd) sys.exit(1) if opts.generate_dot: essentia.translate(RhythmDescriptorsExtractor, "streaming_extractorrhythmdescriptors", dot_graph=True) elif opts.generate_cpp: essentia.translate(RhythmDescriptorsExtractor, "streaming_extractorrhythmdescriptors", dot_graph=False) pool = essentia.Pool() loader = essentia.streaming.MonoLoader(filename=args[0]) rhythm = RhythmDescriptorsExtractor() loader.audio >> rhythm.signal for desc, output in rhythm.outputs.items(): output >> (pool, desc) essentia.run(loader) stats = ['mean', 'var', 'min', 'max', 'dmean', 'dmean2', 'dvar', 'dvar2']
return options, args if __name__ == '__main__': opts, args = parse_args() if len(args) != 2: cmd = './' + os.path.basename(sys.argv[0]) + ' -h' os.system(cmd) sys.exit(1) if opts.generate_dot: essentia.translate(TonalDescriptorsExtractor, 'streaming_extractortonaldescriptors', dot_graph=True) elif opts.generate_cpp: essentia.translate(TonalDescriptorsExtractor, 'streaming_extractortonaldescriptors', dot_graph=False) pool = essentia.Pool() loader = essentia.streaming.MonoLoader(filename=args[0]) tonalExtractor = TonalDescriptorsExtractor() loader.audio >> tonalExtractor.signal for desc, output in tonalExtractor.outputs.items(): output >> (pool, desc) essentia.run(loader) stats = ['mean', 'var', 'min', 'max', 'dmean', 'dmean2', 'dvar', 'dvar2']
return options, args if __name__ == '__main__': opts, args = parse_args() if len(args) != 2: cmd = './'+os.path.basename(sys.argv[0])+ ' -h' os.system(cmd) sys.exit(1) if opts.generate_dot: essentia.translate(PitchExtractor, 'streaming_extractorpitch', dot_graph=True) elif opts.generate_cpp: essentia.translate(PitchExtractor, 'streaming_extractorpitch', dot_graph=False) # find out replay gain loader = EqloudLoader(filename=args[0], sampleRate=analysisSampleRate, downmix='mix') rgain = ReplayGain(applyEqloud=False) pool = essentia.Pool() loader.audio >> rgain.signal rgain.replayGain >> (pool, 'replay_gain') essentia.run(loader)