retraining Computer Vision Project

Fieldlytics

Updated a year ago

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Classes (21)
Maggi Chicken Noodles 284g
Maggi Chicken Noodles 71g
Maggi Chill Chow Cup Noodles 70g
Maggi Masala Cup Noodles 70g
Maggi Masala N560g -Family Pack-
Maggi Masala N560g -Mega pack-
Maggi Masala Noodles 140g
Maggi Masala Noodles 280g
Maggi Masala Noodles 420g
Maggi Masala Noodles 560g
Maggi Masala Noodles 71g
Maggi Oats Noodles 292g
Maggi Oats Noodles 73g
Maggi Special Noodles 280g
Maggi Special Noodles 71g
Maggi SpinachVegatta 290g
Maggi SpinachVegatta Noodles 70g
Maggi Vegatta 290g
Maggi Vegatta Noodles 70g
Maggi Veggie Masala Noodles 280g
Maggi Veggie Masala Noodles 70g
Description

Here are a few use cases for this project:

  1. Grocery Store Inventory Management: The "retraining" computer vision model can be used to help employees track inventory levels, identify when restocking is needed or even automatize the restocking process by analyzing shelf images from a store.

  2. Supermarket Checkout: This model can be implemented in automated checkout systems in supermarkets, identifying and scanning different packs and sizes of Maggi products for accurate billing.

  3. Retail Analytics: Retailers can use the "retraining" model to analyze which Maggi products are more popular by monitoring the rate of product disappearance from the shelves, facilitating better decision-making for optimizing product assortment and space allocation.

  4. Smart Shopping Assistants: Customers can use a shopping app that implements the "retraining" model to quickly find out where the desired Maggi product is located in a store using a store's camera feeds, improving their overall shopping experience.

  5. Visual Quality Control: The model can be employed in the manufacturing process, verifying that the appropriate packaging design and content are being used for different Maggi products, allowing the identification of any discrepancies in real-time.

Supervision

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Cite This Project

LICENSE
CC BY 4.0

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

                        @misc{
                            retraining-n7lbv_dataset,
                            title = { retraining Dataset },
                            type = { Open Source Dataset },
                            author = { Fieldlytics },
                            howpublished = { \url{ https://universe.roboflow.com/fieldlytics-sn6h2/retraining-n7lbv } },
                            url = { https://universe.roboflow.com/fieldlytics-sn6h2/retraining-n7lbv },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { jul },
                            note = { visited on 2024-11-21 },
                            }
                        
                    

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