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)
