def test_get():
signal = Signal(["test", "test2"], [[1, 2], [3, 4]])
audio = signal.get("test")
assert audio == [1, 2]
with pytest.raises(ValueError) as pe:
audio = signal.get("test3")
def test_overlay():
dummy_signal = Signal(["test"], [np.array(range(100), dtype=np.float32)])
augment = Augment()
augment.overlay((5, 10), 17, 1)
augment.augment(dummy_signal, "test")
audio = dummy_signal.get("test")
actual = np.array([11, 12, 13, 14, 15], dtype=np.float32)
assert np.allclose(audio[17: 22], actual)
def test_set():
signal = Signal(["test", "test2"], [[1, 2], [3, 4]])
signal.set("test", [1, 2.5])
with pytest.raises(ValueError) as pe:
signal.set("test3", [1, 2.5])
signal.set("tesT2", [3, 4.5])
with pytest.raises(ValueError) as pe:
signal.set("tesT2", [3, 4.5, 4])
def separate(self, audio: Union[str, np.ndarray], sample_rate=44_100):
"""Separate audio into specified stems.
Note: Spleeter uses tensorflow backend. Hence, corresponding
installed device will automatically be used (CPU/GPU).
Minimum VRAM/RAM requirement: 4GB (for small audio, <6 minutes).
Args:
audio_file (str, array): path to the original signal or the signal itself.
sample_rate (int): sampling rate of the file.
Returns:
signal (Signal): separated signals.
Raises:
tf.errors.ResourceExhaustedError: When memory gets exhausted.
"""
if isinstance(audio, np.ndarray):
waveform = audio
else:
waveform, _ = self._audio_adapter.load(audio,
sample_rate=sample_rate)
print(waveform.shape)
#predict in chunks
prediction = {}
for chunk in self._chunk(waveform, sample_rate):
chunk_prediction = self._separator.separate(chunk)
for chunk_key, chunk_value in chunk_prediction.items():
if chunk_key not in prediction:
prediction[chunk_key] = []
prediction.get(chunk_key).append(chunk_value)
#merge chunk prediction
prediction = {k: np.vstack(v) for k, v in prediction.items()}
print(list(v.shape for v in prediction.values()))
signal = Signal(prediction.keys(), prediction.values())
return signal
def test_create():
signal = Signal(["test"], [[1, 2]])
assert signal is not None
def test_len():
signal = Signal(["test", "test2"], [[1, 2, 3], [4, 5, 6]])
assert len(signal) == 2
assert signal.get_signal_length() == 3
def test_n_stem():
signal = Signal(["test", "test2"], [[1, 2], [3, 4]])
stem = signal.stems
assert stem == 2
def test_diff_len():
with pytest.raises(Exception) as pe:
signal = Signal(["test"], [[1], [2, 3]])
import pytest
import numpy as np
from separator.main import Signal
from separator.main.augment import Augment
dummy_signal = Signal(["test"], [np.array(range(100), dtype=np.float32)])
def test_command():
augment = Augment()
augment.amplitude((3, 10), 0, 1)
assert len(augment.command) == 1
augment.augment(dummy_signal, "test")
assert len(augment.command) == 1
augment.amplitude((3, 10), 0, 1)
assert len(augment.command) == 2
augment.clear()
assert len(augment.command) == 0
def test_amplitude():
augment = Augment()
augment.amplitude((3, 10), 0, 1)
augment.augment(dummy_signal, "test")
audio = dummy_signal.get("test")
assert not any(audio[3: 10])