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)