def get_frrn_label(self):
params, _ = self.voc
filename, offset, _range = params
voc = get_offset_range_patch(filename, offset, _range)
# voc = (voc > FCN_VOC_THRESHOLD).astype('float')
voc = voc.reshape((voc.shape[0], voc.shape[1], 1))
return (voc > FCN_VOC_THRESHOLD).astype('int32')
def _safe_write(self, data):
# print(data)
if isinstance(data, MixWithVocalResult):
self.output_queue.put(
(data.desc(), data._slice(), *data.get_rnn_label()))
return
if isinstance(data, InstWithVocalResult):
self.output_queue.put(
(data.desc(), data.mix(), *data.get_rnn_label()))
return
params, label = data
filename, offset, _range = params
aud = get_offset_range_patch(filename, offset, _range)
if label == [1, 0]:
y1 = aud.reshape((aud.shape[0], aud.shape[1], 1))
y2 = np.zeros((aud.shape[0], aud.shape[1], 1))
# label = np.concatenate((others, voc), axis=2)
else:
# voc = (aud > FCN_VOC_THRESHOLD).astype('float')
y1 = np.zeros((aud.shape[0], aud.shape[1], 1))
y2 = aud.reshape((voc.shape[0], voc.shape[1], 1))
# label = np.concatenate((others, voc), axis=2)
# voc = (voc > FCN_VOC_THRESHOLD).astype('int32')
# label = voc
# if np.isnan(aud).any() or np.isinf(aud).any():
if np.isnan(aud).any():
raise HasNanException()
desc = str(params)
self.output_queue.put((desc, aud, y1, y2))
def _safe_write(self, data):
# print(data)
if isinstance(data, MixWithVocalResult):
self.output_queue.put(
(data.desc(), data._slice(), data.get_label()))
return
if isinstance(data, InstWithVocalResult):
self.output_queue.put((data.desc(), data.mix(), data.get_label()))
return
params, label = data
filename, offset, _range = params
aud = get_offset_range_patch(filename, offset, _range)
# if np.isnan(aud).any() or np.isinf(aud).any():
if np.isnan(aud).any():
raise HasNanException()
desc = str(params)
self.output_queue.put((desc, aud, label))
def _slice(self):
params, _ = self.voc
filename, offset, _range = params
ret = get_offset_range_patch(filename, offset, _range, self.mix)
return ret