test_predictions.py

labels = ["00-damage","01-whole"]

it = iter(testing_set)
batch = next(it) # Gets a batch of 16 test images

fig, axes = plt.subplots(3, 3, figsize=(10,10))
fig.tight_layout()
fig.subplots_adjust(hspace=.25)

for i in range(3):
    for j in range(3):
        ax = axes[i,j]
        image = batch[0][i*3+j]
        net_input = image.reshape((1, 64, 64, 3))
        truth = np.argmax(batch[1][i*3+j])
        prediction = np.argmax(model.predict(net_input))
        ax.set_title('Label: %s\nPrediction: %s' % (labels[truth].capitalize(), labels[prediction].capitalize()))
        ax.imshow(image)