Trading Card Inventory Management with AI

Managing a large trading card collection, especially in markets like Pokémon and Magic: The Gathering, involves balancing speed with precision, as errors can lead to financial losses. Traditionally, cataloging was done manually, but the advent of computer vision and AI has revolutionized this process. An AI-driven system can now automate the identification and logging of cards, utilizing a two-stage pipeline consisting of an RF-DETR model for card detection and a Gemini 2.5 Flash reasoning engine for data verification. This system is trained on high-quality datasets, ensuring accuracy and efficiency, and uses a series of preprocessing and augmentation steps to adapt to various conditions. The automated workflow involves a Roboflow interface to streamline decision-making, and the resulting data is integrated into Excel spreadsheets using Python scripts. This modern approach ensures data integrity, allowing for rapid, high-volume inventory scaling without sacrificing accuracy, and demonstrates a significant advancement in trading card inventory management through AI and computer vision.