medium_tensorflow_grf_data_predict.py

def predict(model, path):
    img = load_image(path)
    predictions = model.predict(img)
    certainties = []
    labels = ['01', '02', '03', '04', '04b', '05', '06', '07', '08', '09', '10', '11', '12']
    page_to_scene_mapping = {
        '01': '1',
        '02': '2',
        '03': '2',
        '04': '3',
        '04b': '4b',
        '05': '4',
        '06': '8',
        '07': '8',
        '08': '10',
        '09': '11',
        '10': '14',
        '11': '15',
        '12': '16',
    }
    for idx, prediction in enumerate(predictions[0]):
        certainties.append(float(prediction))
        print("Certainty of page %s: %s" % (labels[idx], prediction))

    predicted_page = labels[predictions[0].argmax()]
    predicted_scene = page_to_scene_mapping[predicted_page]
    certainty = predictions[0][predictions[0].argmax()]
    print("Highest probable scene is %s" % predicted_scene)
    return str(predicted_scene), float(certainty), certainties