本论文介绍了基于BLIP(Bootstrapping Language Image Pre-training)模型的VQA(Visual Question Answering)智能问答系统的设计与实现.该系统通过将视觉和语言信息融合,实现了对图像提出问题并获取准确答案的功能.前端使用HTML、CSS和Javascript构建,后端采用Django框架进行开发,部署使用Docker容器.实验结果表明,所提出的系统在开放问答领域上取得了显著的成果.
Design and Implementation of VQA Intelligent Q&A System Based on BLIP
This thesis describes the design and implementation of VQA(Visual Question Answering)intelligent question and answer system based on BLIP(Bootstrapping Language Image Pre-training)model.The system realizes the function of asking questions about images and obtaining accurate answers by fusing visual and linguistic information.The front-end is built using HTML,CSS and Javascript,the back-end is developed using Django framework and deployed using Docker containers.The experimental results show that the proposed system achieves significant results on the open question and answer domain.
BLIPVQAintelligent question and answer systemdjangodocker
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