def METHOD_NAME(self, image_list):
    inputs = []
    batch_loop_cnt = math.ceil(float(len(image_list)) / self.batch_size)
    results = []
    for i in range(batch_loop_cnt):
        start_index = i * self.batch_size
        end_index = min((i + 1) * self.batch_size, len(image_list))
        batch_image_list = image_list[start_index:end_index]
        # preprocess
        # model inference
        result = self.nlp(batch_image_list)
        # postprocess
        result = self.postprocess(inputs, result)
        results.extend(result)
    # results = self.merge_batch_result(results)
    return results