def compute(self, *args):
key = args[2]
outs = pyloudness.get_loudness(args[0].routes[key])
integratedLoudness = outs['Integrated Loudness']['I']
loudnessRange = outs['Loudness Range']['LRA']
return esarr([integratedLoudness, loudnessRange])
def compute(self, *args):
key = args[2]
outs = pyloudness.get_loudness(args[0].routes[key])
integratedLoudness = outs['Integrated Loudness']['I']
loudnessRange = outs['Loudness Range']['LRA']
return esarr([integratedLoudness, loudnessRange])
def stats(file):
'''Takes a file path and outputs Loudness and Peak to terminal'''
loudness_stats = pyloudness.get_loudness(file)
print("File : " + os.path.basename(file))
print("_________________")
print("Loudness : " + str(loudness_stats["Integrated Loudness"]["I"]))
print("Peak : " + str(loudness_stats["True Peak"]["Peak"]))
print("_________________")
print(" ")
def _work(self):
tts.say("Time to work! The LED lights will turn off as time elapses.")
self._board.led.state = Led.PULSE_SLOW
record_file(
AudioFormat.CD, filename=self._file, wait=self._wait, filetype="wav",
)
self._done.clear()
session_score = pyloudness.get_loudness(self._file)["Loudness Range"]["LRA"]
tts.say("Session score: {:.2}".format(session_score))
if session_score > 5:
tts.say("Try to be a little more quiet next round")
self._score += session_score
def _work(self):
tts.say("Time to work!")
self._board.led.state = Led.PULSE_SLOW
record_file(
AudioFormat.CD,
filename=self._file,
wait=self._wait,
filetype="wav",
)
tts.say("Session ended")
self._done.clear()
session_score = pyloudness.get_loudness(
self._file)["Loudness Range"]["LRA"]
if session_score > 40:
tts.say("Try to be a little more quiet next round")
self._score += session_score
model = model_from_json(model_json)
model.load_weights("{}.h5".format(args.model))
print("Using model: {}".format(args.model))
print("Architecture:")
print(model.summary())
records = []
for input_file in tqdm.tqdm(filenames):
# For duration extraction (using librosa and essentia at the same time seems)
# overkill however we need to deal with it at the current version
audio = essentia.standard.MonoLoader(filename=input_file,
sampleRate=22050)()
# Loudness extractors
loudness_dict = ld.get_loudness(input_file)
true_peak = loudness_dict['True Peak']['Peak']
integrated_loudness = loudness_dict['Integrated Loudness']['I']
# Music/Speech/Sfx discrimination
frameGenerator = essentia.standard.FrameGenerator(audio,
frameSize=frameSize,
hopSize=hopSize,
startFromZero=True)
w = essentia.standard.Windowing(size=frameSize)
rmsx = essentia.standard.RMS()
rms = []
for frame in frameGenerator:
rms.append(rmsx(frame))