computeFeature.py

Go to the documentation of this file.

# -*- coding: utf-8 -*-
 
import matplotlib.pyplot as plt
 
import pyACA
from pyACA.computeSpectrogram import computeSpectrogram
from pyACA.ToolPreprocAudio import ToolPreprocAudio
from pyACA.ToolComputeHann import ToolComputeHann
from pyACA.ToolReadAudio import ToolReadAudio
 
 
 
def computeFeature(cFeatureName, x, f_s, afWindow=None, iBlockLength=4096, iHopLength=2048):
 
    # mypackage = __import__(".Feature" + cFeatureName, package="pyACA")
    hFeatureFunc = getattr(pyACA, "Feature" + cFeatureName)
 
    # pre-processing
    x = ToolPreprocAudio(x)
 
    if isSpectral(cFeatureName):
        # compute window function for FFT
        if afWindow is None:
            afWindow = ToolComputeHann(iBlockLength)
 
        assert(afWindow.shape[0] == iBlockLength), "parameter error: invalid window dimension"
 
        # in the real world, we would do this block by block...
        [X, f, t] = computeSpectrogram(x, f_s, None, iBlockLength, iHopLength)
 
        # compute instantaneous feature
        v = hFeatureFunc(X, f_s)
 
    if isTemporal(cFeatureName):
        [v, t] = hFeatureFunc(x, iBlockLength, iHopLength, f_s)
 
    return v, t
 
 
 
def isSpectral(cName):
    bResult = False
    if "Spectral" in cName:
        bResult = True
 
    return bResult
 
 
def isTemporal(cName):
    bResult = False
    if "Time" in cName:
        bResult = True
 
    return bResult
 
 
 
def computeFeatureCl(cPath, cFeatureName, bPlotOutput=False):
 
    # read audio file
    [f_s, afAudioData] = ToolReadAudio(cPath)
    
    # for debugging
    iBlockLength = 4096
    iHopLength = 2048
 
    # compute feature
    [v, t] = computeFeature(cFeatureName, afAudioData, f_s, None, iBlockLength, iHopLength)
 
    # plot feature output
    if bPlotOutput:
        plt.plot(t, v)
 
    return v, t
 
 
if __name__ == "__main__":
    import argparse
 
    # add command line args and parse them
    parser = argparse.ArgumentParser(description='Compute feature from wav file')
    parser.add_argument('--infile', metavar='path', required=False,
                        help='path to input audio file')
    parser.add_argument('--featurename', metavar='string', required=False,
                        help='feature name in the format SpectralPitchChroma')
    parser.add_argument('--plotoutput', metavar='bool', required=False,
                        help='option to plot the output')
 
    # retrieve command line args
    args = parser.parse_args()
    cPath = args.infile
    cFeatureName = args.featurename
    bPlotOutput = args.plotoutput
 
    # only for debugging
    if __debug__:
        if not cPath:
            cPath = "../ACA-Plots/audio/sax_example.wav"
        if not cFeatureName:
            cFeatureName = "SpectralKurtosis"
        if not bPlotOutput:
            bPlotOutput = False
 
    # call the function
    computeFeatureCl(cPath, cFeatureName, bPlotOutput)