def regressionFolderWrapper(inputFolder, model_type, model_name):
files = "*.wav"
if os.path.isdir(inputFolder):
strFilePattern = os.path.join(inputFolder, files)
else:
strFilePattern = inputFolder + files
wavFilesList = []
wavFilesList.extend(glob.glob(strFilePattern))
wavFilesList = sorted(wavFilesList)
if len(wavFilesList) == 0:
print("No WAV files found!")
return
Results = []
for wavFile in wavFilesList:
R, regressionNames = aT.file_regression(wavFile, model_name, model_type)
Results.append(R)
Results = numpy.array(Results)
for i, r in enumerate(regressionNames):
[Histogram, bins] = numpy.histogram(Results[:, i])
centers = (bins[0:-1] + bins[1::]) / 2.0
plt.subplot(len(regressionNames), 1, i + 1)
plt.plot(centers, Histogram)
plt.title(r)
plt.show()
def regressionFileWrapper(inputFile, model_type, model_name):
if not os.path.isfile(inputFile):
raise Exception("Input audio file not found!")
R, regressionNames = aT.file_regression(inputFile, model_name, model_type)
for i in range(len(R)):
print("{0:s}\t{1:.3f}".format(regressionNames[i], R[i]))