def word_parser(final_callback=None): global model global datahandler model = Model() datahandler = DataHandler(noActualLoad=True) for i, word in enumerate(datahandler.getClasses()): current_word_prob[word] = 0 capture_audio(callback_word, final_callback)
def main(): config = Config() parser = argparse.ArgumentParser() parser.add_argument('-td', '--test-dataset', help='Walk through dataset \ and test while preprocessing', action='store_true') parser.add_argument('-e', '--execute', help='Execute', action='store_true') parser.add_argument('-t', '--train', help='Train Model', action='store_true') parser.add_argument('-wp', '--word-parser', help='Listen to microphone parse the word', action='store_true') parser.add_argument('-p', '--predict', help='Predict Audiofile', nargs='+') args = parser.parse_args() if args.test_dataset: datahandler = DataHandler() print("Test Passed") return if args.execute: from event_handler import EventHandler eh = EventHandler() word_parser(eh) if args.train: model = Model() model.train() if args.predict: model = Model() datahandler = DataHandler(noActualLoad=True) result_prob = model.predict(args.predict, datahandler.getClasses()) for fname, rp in zip(args.predict, result_prob): print("%s\t%s\twith Probabity %f" % (fname, rp[0], rp[1])) if args.word_parser: word_parser()