CartLens

shelf_data

Object Detection

shelf_data Computer Vision Project

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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{ shelf_data_dataset,
    title = { shelf_data Dataset },
    type = { Open Source Dataset },
    author = { CartLens },
    howpublished = { \url{ https://universe.roboflow.com/cartlens/shelf_data } },
    url = { https://universe.roboflow.com/cartlens/shelf_data },
    journal = { Roboflow Universe },
    publisher = { Roboflow },
    year = { 2023 },
    month = { oct },
    note = { visited on 2023-12-03 },
}

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

Source

CartLens

Last Updated

a month ago

Project Type

Object Detection

Subject

products

Classes

50 50 Biscuit, Biscafe, Bounce, Bourbon, Bourbon Dark fantasy, Bourn Vita Biscuit, Chocobakes, Coffee Joy, Creme, Dark Fantasy, Digestive, Elite, Ginger, Good Day, Happy Happy, Hide & Seek, Jim Jam, KrackJack, Malkist, Marie Gold, Marie Light, Milk Bikis, Milk Short Cake, Mom Magic, Monaco, Nice, Nutri Choice, Nutri Choice(Crackers), Nutri Choice(Herbs), Nutri Choice(Sugar Free), Oreo, Parle G, Potazo, Sunfeast green, Super Millets, Supermilk, Tninz, Treat, Unibic, Unibic-box, all rounder

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License

CC BY 4.0