def split_train_val():    
    tmp_dir = os.path.join(ROOT_DIR, "tmp")
    
    os.makedirs(os.path.join(ROOT_DIR, "train"))
    train_dir = os.path.join(ROOT_DIR, "train")
    os.makedirs(os.path.join(train_dir, "images"))
    
    os.makedirs(os.path.join(ROOT_DIR, "val"))
    val_dir = os.path.join(ROOT_DIR, "val")
    os.makedirs(os.path.join(val_dir, "images"))

    # Opening JSON file
    with open(os.path.join(tmp_dir, 'annotations.json')) as json_file:
        data = json.load(json_file)

        # 0.1765 is 15% van 100% omdat test al 20 % is (niet helemaal)
        val_keys = random.sample(list(data), round(len(data) * 0.1765))

        validation = {k: v for k, v in data.items() if k in val_keys}
        train = {k: v for k, v in data.items() if k not in val_keys}

    with open(os.path.join(val_dir, SAVE_FILE), 'w') as output_json_file:
        json.dump(validation, output_json_file)

    with open(os.path.join(train_dir, SAVE_FILE), 'w') as output_json_file:
        json.dump(train, output_json_file)
        
    for key, _ in validation.items():
        shutil.move(os.path.join(tmp_dir, "images", key), os.path.join(val_dir, "images", key))

    for key, _ in train.items():
        shutil.move(os.path.join(tmp_dir, "images", key), os.path.join(train_dir, "images"))

    shutil.rmtree(tmp_dir)