#!/usr/bin/env python

from keras.models import load_model
import numpy as np

from train import load_data

if __name__ == '__main__':
    # Load trained keras model
    model = load_model('model.hd5')

    # Load test data
    images, labels = load_data('test_images.bin', 'test_labels.bin')

    # Predict written numbers in images
    labels_predicted = model.predict(images)

    # Decode the one-hot vectors to labels
    labels_decoded = np.argmax(labels_predicted, axis=1)

    # Calculate accuracy of prediction
    num_correct = np.sum(labels_decoded == labels)
    print('Accuracy on test dataset: {}'.format(float(num_correct)/len(labels)))