sabad-10-classes Object Detection Dataset and Pre-Trained Model by balance16class

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Explore Dataset

Here are a few use cases for this project:

Supermarket Inventory Management: The model can be used to track and manage inventory by constantly monitoring and identifying supermarket products on the shelves through security camera footage.
Automated Checkout Systems: This model can be integrated into self-checkout systems, where it identifies items as customers scan them. This adds an additional layer of verification, reducing errors and potential losses due to mis-scanned items.
Online Shopping Experience: Enhance the online shopping experience by integrating the model with apps, allowing users to scan their preferred product at home and find it or its alternatives in the online store.
Smart Shopping Assistants: Use in developing smart shopping apps that help users identify and locate items in the supermarket. Users can input a shopping list and the model, through an in-store camera system, could guide customers to the items.
Waste Management: Companies that handle supermarket waste can use the model to better sort waste products by distinguishing between different types of products and their packaging materials, important for recycling processes.

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{
                            sabad-10-classes_dataset,
                            title = { sabad-10-classes Dataset },
                            type = { Open Source Dataset },
                            author = { balance16class },
                            howpublished = { \url{ https://universe.roboflow.com/balance16class/sabad-10-classes } },
                            url = { https://universe.roboflow.com/balance16class/sabad-10-classes },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { jun },
                            note = { visited on 2024-06-29 },
                            }