def _generate_data():
"""Generate data examples."""
wav_file = fake_data_utils.get_random_wav_c1(duration=1, sample=22050)
filepath = os.path.join(_output_dir(), "music_speech", "speech_wav",
"{}.wav".format("test"))
dirname = os.path.dirname(filepath)
if not tf.io.gfile.exists(dirname):
tf.io.gfile.makedirs(dirname)
tf.io.gfile.copy(wav_file, filepath, overwrite=True)
def _generate_data():
"""Generate data examples."""
for _ in range(NUMBER_OF_EXAMPLES):
wav_file = fake_data_utils.get_random_wav_c1(duration=6, sample=8000)
filename = _get_file_name()
filepath = os.path.join(_output_dir(), "waves_yesno",
"{}.wav".format(filename))
dirname = os.path.dirname(filepath)
if not tf.io.gfile.exists(dirname):
tf.io.gfile.makedirs(dirname)
tf.io.gfile.copy(wav_file, filepath, overwrite=True)
def _generate_data():
"""Generate data examples."""
# pylint: disable=protected-access
labels = tfds.features.ClassLabel(names=gtzan._CLASS_LABELS).names # pytype: disable=module-attr
# pylint: enable=protected-access
wav_file = fake_data_utils.get_random_wav_c1(duration=30, sample=22050)
# .wav file has name in the format of <genre>.<number>.wav
label = random.choice(labels)
random_number_for_filename = random.randint(0, 99)
filename = "{}.{:05d}".format(label, random_number_for_filename)
filepath = os.path.join(_output_dir(), "genres", label,
"{}.wav".format(filename))
dirname = os.path.dirname(filepath)
if not tf.io.gfile.exists(dirname):
tf.io.gfile.makedirs(dirname)
tf.io.gfile.copy(wav_file, filepath, overwrite=True)
def _make_wav_file(filepath: str):
wav_file = fake_data_utils.get_random_wav_c1(duration=2, sample=16000)
dirname = os.path.dirname(filepath)
if not tf.io.gfile.exists(dirname):
tf.io.gfile.makedirs(dirname)
tf.io.gfile.copy(wav_file, filepath, overwrite=True)
