Building Visual Questioning Answering System Using Hugging Face Open-Source Models

Author(s): Youssef Hosni

Originally published on Towards AI.

Visual Question Answering (VQA) is a complex task that combines computer vision and natural language processing to enable systems to answer questions about images.

In this technical blog, we explore the creation of a VQA system using Hugging Face’s open-source models. The article begins with an introduction to multimodal models and the VQA task, providing foundational knowledge for understanding how these systems operate.

We then guide you through setting up the working environment and loading the necessary models and processors. By preparing both image and text inputs, we illustrate how to perform visual question answering.

This step-by-step tutorial demonstrates how to leverage Hugging Face’s powerful tools to build sophisticated VQA systems, enhancing readers’ understanding of multimodal AI applications.

Introduction to Multimodal ModelsIntroduction to Visual Questioning Answering TaskSetting Up Working EnvironmentLoading the Model and ProcessorPreparing the Image and TextPerforming Visual Questioning-Answering

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Published via Towards AI