def process(fileName):
client = MongoClient()
db = client.audiograins
grainEntries = db.grains
song = AudioSegment.empty()
songFile = open(fileName)
print("converting to mono")
monoFilename = "mono" + fileName
subprocess.check_call(["ffmpeg -i " + fileName + " -ac 1 -threads 2 " + monoFilename], close_fds=True, shell=True)
grains = granulizer.chopSound(monoFilename, 20, "inputGrains", "sample")
labels = ["chorus", "hip-hop", "latin", "orchestra", "pop", "rock", "country", "jazz", "opera", "piano", "reggae", "techno"]
classifications = [0] * 12;
totalGrains = 0
normalizer = pickle.load(open("normalizer.pickle"))
classifier = pickle.load(open("classifier.pickle"))
indexToIds = pickle.load(open("indexToIds.pickle"))
for grain in tqdm(grains):
#Analyze all stats for grain
totalGrains += 1
dataPoint = np.empty([1, 16])
mfccs = analyzer.analyzeMFCC(grain)
dataPoint[0][0] = mfccs[0]
dataPoint[0][1] = mfccs[1]
dataPoint[0][2] = mfccs[2]
dataPoint[0][3] = mfccs[3]
dataPoint[0][4] = mfccs[4]
dataPoint[0][5] = mfccs[5]
dataPoint[0][6] = mfccs[6]
dataPoint[0][7] = mfccs[7]
dataPoint[0][8] = mfccs[8]
dataPoint[0][9] = mfccs[9]
dataPoint[0][10] = mfccs[10]
dataPoint[0][11] = mfccs[11]
dataPoint[0][12] = mfccs[12]
dataPoint[0][13] = analyzer.analyzePitch(grain)
dataPoint[0][14] = analyzer.analyzeEnergy(grain)
#dataPoint[15] = kurtosis
#dataPoint[16] = skewness
#dataPoint[17] = spread
#dataPoint[18] = centroid
dataPoint[0][15] = analyzer.analyzeZeroCrossingRate(grain)
classifications[int(classifier.predict(normalizer.transform(dataPoint))[0])] += 1
#print("Prediction: " + str(classifier.predict(normalizer.transform(dataPoint))[0]))
print("Genre:")
for i in range(0, 12):
print("\t" + labels[i] + ": " + str(((float(classifications[i]) / float(totalGrains)) * 100.0)) + "%")
print("downloading " + toDownload)
try:
urllib.urlretrieve(url=toDownload, filename=filename)
songFile = open(filename)
print("done downloading file")
print("converting to " + monoFilename)
subprocess.check_call(["ffmpeg -i " + filename +" -ac 1 -threads 2 " + monoFilename], close_fds=True, shell=True)
except Exception:
print("Error in ffmpeg or download")
print("cleaning up..")
subprocess.call(["rm " + filename], shell=True)
open(downloadsPath + downloadFile, 'w').writelines(lines[1:])
subprocess.call(["rm " + monoFilename], shell=True)
sys.exit()
grainMongoObjects = chopSound(monoFilename, 20, grainsFolder, downloadFile[:-4])
if grainMongoObjects is None:
print("Problem chopping sound, skipping " + monoFilename)
subprocess.call(["rm " + filename], shell=True)
open(downloadsPath + downloadFile, 'w').writelines(lines[1:])
subprocess.call(["rm " + monoFilename], shell=True)
songFile.close()
sys.exit()
else:
try:
storeGrains(grainMongoObjects)
analyzeMFCCSubset(grainMongoObjects)
logging.debug("done with mfcc for " + toDownload)
analyzePitchSubset(grainMongoObjects)
logging.debug("done with pitch for " + toDownload)
analyzeEnergySubset(grainMongoObjects)