Retail Product Checkout Object Detection Dataset and Pre-Trained Model by CDIO

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Explore Dataset

Here are a few use cases for this project:

Smart Recycling and Waste Management: Use the "Có Gì Dùng Nấy" computer vision model to identify and sort various types of bottles and containers at recycling centers or waste management facilities, ensuring that materials are properly separated and recycled.
Smart Inventory Management: Implement the model in retail stores, warehouses, or supermarkets to automatically monitor and track the stock levels of different products (bocalex, oil bottle, vinamilk, chinsu, strongbow, traxanhkhongdo, aquafina, hanhnhan, life-buoy, X-men, 4D_medical_face-mask), helping businesses maintain optimal inventory levels and reduce the need for manual counting.
Automated Checkout Systems: Integrate the "Có Gì Dùng Nấy" model into self-checkout systems at grocery stores, allowing customers to easily scan and pay for their items without manually entering product information. This can reduce wait times and improve the shopping experience.
eCommerce Product Recognition: Use the model to enhance product search and recommendation features on eCommerce platforms. When users upload images of products they are interested in, the platform can accurately identify the product and suggest similar items or related product categories.
Accessible Product Information for Visually Impaired Users: Leverage the "Có Gì Dùng Nấy" model to create accessible product information for visually impaired users through a mobile app or smart device. By recognizing product labels and containers, the app can provide users with detailed information about the item, such as ingredients, usage instructions, and safety warnings.

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{
                            retail-product-checkout_dataset,
                            title = { Retail Product Checkout Dataset },
                            type = { Open Source Dataset },
                            author = { CDIO },
                            howpublished = { \url{ https://universe.roboflow.com/cdio-zmfmj/retail-product-checkout } },
                            url = { https://universe.roboflow.com/cdio-zmfmj/retail-product-checkout },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2024 },
                            month = { feb },
                            note = { visited on 2024-05-06 },
                            }