def create_audio_and_convert(output_dir, captcha_text):
pwd = os.getcwd()
work_dir = pwd + '\\symbols\\'
#combined_sounds = None
#for symbol in captcha_text:
#tts_service = random.choice(tts_list)
#raw_path = work_dir + tts_service + '\\' + symbol
#sound = AudioSegment.from_wav(raw_path + ".wav")
#if combined_sounds is None:
# combined_sounds = sound
#else:
# combined_sounds = combined_sounds + sound
audio = AudioCaptcha()
audio.write(captcha_text, output_dir)
if not os.path.exists(pwd + '\\' + tempDir):
print("Creating temp directory " + tempDir)
os.makedirs(pwd + '\\' + tempDir)
output_dir_tts = pwd + '\\' + tempDir + '\\'
wav_audio_path = output_dir_tts + captcha_text + '.wav'
audio.export(wav_audio_path, format="wav")
plt.interactive(False)
clip, sample_rate = librosa.load(wav_audio_path, sr=None)
fig = plt.figure(figsize=[0.415, 0.210])
ax = fig.add_subplot(111)
ax.axes.get_xaxis().set_visible(False)
ax.axes.get_yaxis().set_visible(False)
ax.set_frame_on(False)
S = librosa.feature.melspectrogram(y=clip, sr=sample_rate)
librosa.display.specshow(librosa.power_to_db(S, ref=np.max))
filename = os.path.join(output_dir, captcha_text + '.jpg')
plt.savefig(filename, dpi=400, bbox_inches='tight', pad_inches=0)
plt.close()
fig.clf()
plt.close(fig)
plt.close('all')
del clip, sample_rate, fig, ax, S
