Group 6 Major Project

Card Grader

Object Detection


Card Grader Computer Vision Project

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Here are a few use cases for this project:

  1. Trading Card Quality Assessment: The "Card Grader" computer vision model can be used by collectors and enthusiasts to grade trading cards such as sports cards, Pokemon cards, or Magic: The Gathering cards. This helps determine the overall condition and value of the cards based on factors like Edge Wear, Scratch, and Corner Wear, assisting users in the buying, selling, or trading process.

  2. Playing Card Condition Analysis: The model can be employed in casinos or professional card game settings to ensure that the cards used are in good condition and free from any significant wear or damage that could impact gameplay or fairness. The system can automatically replace or rotate cards with detected issues.

  3. E-commerce Catalog Enhancement: Online retailers selling collectible or rare cards can use the "Card Grader" model to provide detailed card condition information to potential buyers. This feature can improve customer trust and satisfaction, and minimize potential disputes and return requests.

  4. Card Authentication and Anti-Counterfeiting: The "Card Grader" model can be integrated into card authentication services to identify signs of tampering or counterfeiting, such as inappropriate edge wear or inconsistent card characteristics. This ensures that only genuine and accurately graded cards are sold or exchanged in the market.

  5. Digital Archiving and Preservation: Libraries, archives, or museums with collections of rare or historic cards can use the "Card Grader" computer vision model to monitor and document the condition of their card items over time. The model can help prioritize conservation efforts, ensuring the long-term preservation and accessibility of these cultural artifacts.

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

Cite this Project

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{ card-grader_dataset,
    title = { Card Grader Dataset },
    type = { Open Source Dataset },
    author = { Group 6 Major Project },
    howpublished = { \url{ } },
    url = { },
    journal = { Roboflow Universe },
    publisher = { Roboflow },
    year = { 2022 },
    month = { may },
    note = { visited on 2023-11-30 },

Find utilities and guides to help you start using the Card Grader project in your project.

Last Updated

2 years ago

Project Type

Object Detection




Card, Corner Wear, Edge Wear, Scratch

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CC BY 4.0