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Overview

The Playing Cards dataset is a collection of synthetically generated cards blended into various types of backgrounds. You will be able to perform object detection to detect both number and suit of the cards.

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Training and Deployment

The playing cards model has been trained in Roboflow, available for inference on the Dataset tab.

One could also build a Card Counting model for either Black Jack or Poker using YOLOR. This is achieved using the Roboflow Platform which you can deploy the model for robust and real-time detections. You can learn more here: https://augmentedstartups.info/YOLOR-Get-Started

Video Demo using YOLOR for training- https://youtu.be/2lGTZuaH4ec

About Augmented Startups

We are at the forefront of Artificial Intelligence in computer vision. With over 90k subscribers on YouTube, we embark on fun and innovative projects in this field and create videos and courses so that everyone can be an expert in this field. Our vision is to create a world full of inventors that can turn their dreams into reality.

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.

YOLOv8

This project has a YOLOv8 model checkpoint available for inference with Roboflow Deploy. YOLOv8 is a new state-of-the-art real-time object detection model.

Cite This Project

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

@misc{
                            playing-cards-ow27d_dataset,
                            title = { Playing Cards Dataset },
                            type = { Open Source Dataset },
                            author = { Augmented Startups },
                            howpublished = { \url{ https://universe.roboflow.com/augmented-startups/playing-cards-ow27d } },
                            url = { https://universe.roboflow.com/augmented-startups/playing-cards-ow27d },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { aug },
                            note = { visited on 2024-04-19 },
                            }