def testGetFeaturesForWav(self):
tmp_dir = self.get_temp_dir()
wav_dir = os.path.join(tmp_dir, "wavs")
os.mkdir(wav_dir)
self._SaveWavFolders(wav_dir, ["a", "b", "c"], 1)
flags = self._GetDefaultFlags()
flags.preprocess = "average"
flags.desired_samples = 1600
flags.train_dir = tmp_dir
flags.summaries_dir = tmp_dir
flags.data_dir = wav_dir
with self.cached_session() as sess:
audio_processor = input_data.AudioProcessor(flags)
sample_data = np.zeros([flags.desired_samples, 1])
for i in range(flags.desired_samples):
phase = i % 4
if phase == 0:
sample_data[i, 0] = 0
elif phase == 1:
sample_data[i, 0] = -1
elif phase == 2:
sample_data[i, 0] = 0
elif phase == 3:
sample_data[i, 0] = 1
test_wav_path = os.path.join(tmp_dir, "test_wav.wav")
input_data.save_wav_file(test_wav_path, sample_data, 16000)
results = audio_processor.get_features_for_wav(
test_wav_path, flags, sess)
spectrogram = results[0]
self.assertEqual(1, spectrogram.shape[0])
self.assertEqual(16, spectrogram.shape[1])
self.assertEqual(11, spectrogram.shape[2])
self.assertNear(0, spectrogram[0, 0, 0], 0.1)
self.assertNear(200, spectrogram[0, 0, 5], 0.1)
def testSaveWavFile(self):
tmp_dir = self.get_temp_dir()
file_path = os.path.join(tmp_dir, "load_test.wav")
save_data = np.zeros([16000, 1])
input_data.save_wav_file(file_path, save_data, 16000)
loaded_data = input_data.load_wav_file(file_path)
self.assertIsNotNone(loaded_data)
self.assertLen(loaded_data, 16000)
