print 'Model Already Exist' print '--------------------' model = nn.load_model() else: print 'Model Does Not Exist' print '--------------------' model = nn.create_cnn_model() input = int(raw_input('Enter 0 to train:\nEnter 1 to predict:')) if input == 0: list = [] for i in xrange(65, 91): print 'Training: ' + str(chr(i)) print '-----------------------------------------------------' images = nn.fetch_data('../asl_alphabet_train/' + chr(i)) nn.prepare_data(images, letter=chr(i)) #Nothing images = nn.fetch_data('../asl_alphabet_train/' + 'nothing') nn.prepare_data(images, letter='nothing') #Space images = nn.fetch_data('../asl_alphabet_train/' + 'space') nn.prepare_data(images, letter='space') inputs, labels = nn.mix_data() nn.train_cnn_model(model, inputs, labels) elif input == 1: images = nn.fetch_data('../asl_alphabet_test') inputs, labels = nn.prepare_test_data(images) nn.predict_sample(model, inputs, labels)