plt.plot(range(15), times[3], 'y', label='MFGLA')
plt.plot(range(15), times[4], 'm', label='ADMM')
plt.legend(loc='upper left')
plt.show()
def grafic_vocoder():
time_list = list()
index_list = list()
for i in range(5, 100):
t = time.time()
data = synthesizer.tts(
'this is a test and you should not be worried about the results',
i)
time_list.append(time.time() - t)
index_list.append(i)
plt.plot(index_list, time_list, '-bo')
plt.xlabel('Numar iteratii Griffin-Lim')
plt.ylabel('Timp')
plt.show()
if __name__ == '__main__':
#griffin_lim_timer()
#global_timer()
data = synthesizer.tts(
'this is a test and you should not be worried about the results')
from flask import Flask, Response, request, render_template, send_file
parser = argparse.ArgumentParser()
parser.add_argument(
'-c', '--config_path', type=str, help='path to config file for training')
args = parser.parse_args()
config = load_config(args.config_path)
app = Flask(__name__)
synthesizer = Synthesizer()
synthesizer.load_model(config.model_path, config.model_name,
config.model_config, config.use_cuda)
@app.route('/')
def index():
return render_template('index.html')
@app.route('/api/tts', methods=['GET'])
def tts():
text = request.args.get('text')
text.encode("utf-8-sig")
print(" > Model input: {}".format(text))
data = synthesizer.tts(text)
return send_file(data, mimetype='audio/wav')
if __name__ == '__main__':
app.run(debug=True, host='0.0.0.0', port=config.port)
