def load_backgrounds(data):
backgrounds = []
background_paths = data['backgroundSlices']
logger.info("input: %s", background_paths)
for background_path in background_paths:
backgrounds.append(open_audio(background_path))
return backgrounds
def load_all_waves(root):
audios = []
for path, dirs, filenames in os.walk(root):
for filename in filenames:
if filename.endswith("mp3"):
full_path = path + "/" + filename
audio = open_audio(full_path)
audios.append((full_path, audio))
return audios
def slice_sound(path, duration_sec=MIN_BACK_DURATION_SEC):
res = []
try:
sound = open_audio(path).split_to_mono()[0]
total_duration = len(sound)
duration_millis = duration_sec * 1000
for i in range(0, total_duration, duration_millis):
target = "1-" + str(i) + ".wav"
end = i+duration_millis-1 if i+duration_millis-1 < total_duration else total_duration
buf = sound[i:end]
buf.export(out_f=target, format="wav").close()
res.append(target)
except FileNotFoundError as e:
logger.error("file:{path} not found".format(path=path))
except Exception as e:
logger.error("exception occurs : {e}".format(e=e))
return res
def setUp(self):
self.background: AudioSegment = open_audio(
'test-asset/raw-data/backgrounds/1.mp3')
self.activate: AudioSegment = open_audio(
'test-asset/raw-data/activates/1_2.wav')
def process(data):
segment = open_audio(data['filePath'])
x = fit_audio(segment)
predictions = predict(x)
return make_output(segment, predictions)