Automated Book Inventory using Computer Vision

Timothy M's blog post, published on July 19, 2024, outlines the development of an automated library management system utilizing computer vision and large language models to streamline the process of book inventory. The system employs a combination of technologies, including an object detection model trained with Roboflow to recognize book covers, Microsoft's Florence-2 vision foundation model to extract text from images, and the GPT-4o model API to analyze and structure this data into a library's digital inventory. This automation not only enhances the efficiency and accuracy of cataloging and inventory management but also eliminates the need for manual data entry by automatically extracting book details such as titles, authors, and genres. The application is built with a Gradio interface, allowing users to upload book cover images for processing, and is capable of handling large volumes of data, thus significantly improving the scalability of library operations.