  Multi-modal visual understanding of images with prompts involves using
various visual and textual cues to enhance the semantic understanding of
images. This approach combines both vision and language processing to generate
more accurate predictions and recognition of images. By utilizing prompt-based
techniques, models can learn to focus on certain features of an image to
extract useful information for downstream tasks. Additionally, multi-modal
understanding can improve upon single modality models by providing more robust
representations of images. Overall, the combination of visual and textual
information is a promising area of research for advancing image recognition and
understanding. In this paper we will try an amount of prompt design methods and
propose a new method for better extraction of semantic information
