cup_layer_count Instance Segmentation Dataset and Pre-Trained Model by Kittitham Phadungviang

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Explore Dataset

Here are a few use cases for this project:

Recycling Assistance: This model could be utilized within smart recycling systems to accurately identify and sort different types of cups based on their structure and layer composition. This could improve waste management and contribute to better environmental stewardship.
Quality Control in Manufacturing: Manufacturers of cups could use the "cup_layer_count" model to automate quality control, ensuring that each cup is produced according to the desired specifications. This would help to maintain product consistency and detect any production errors early in the process.
Automatic Beverage Machine Interaction: Vending and beverage machines could incorporate this model to recognize different types of cups, enabling accurate dispensing of drinks according to the cup type.
Packaging Industry Analysis: Within the packaging industry, this model could assist in cataloging various types of cup products, offering deeper insight into the market structure and diversity of product design.
Accessibility Assistance: For visually impaired individuals, an AI assistant equipped with this model could provide information about a given cup's structure and design, enabling a more informed interaction with their environment.

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{ cup_layer_count_dataset,
    title = { cup_layer_count Dataset },
    type = { Open Source Dataset },
    author = { Kittitham Phadungviang },
    howpublished = { \url{ https://universe.roboflow.com/kittitham-phadungviang-5zcpq/cup_layer_count } },
    url = { https://universe.roboflow.com/kittitham-phadungviang-5zcpq/cup_layer_count },
    journal = { Roboflow Universe },
    publisher = { Roboflow },
    year = { 2023 },
    month = { jul },
    note = { visited on 2023-12-02 },
}