Glico V3 Computer Vision Project

Adi Krena

Updated a year ago

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Classes (14)
Pejoy Chocolate 37g
Pejoy Cookies and Cream 37g
Pocky Almond 36g
Pocky Brown Sugar 37g
Pocky Choco Banana 42g
Pocky Chocolate 47g
Pocky Cookies and Cream 40g
Pocky Double Choco 47g
Pocky Matcha 33g
Pocky Strawberry 45g
Pocky Yuzu 33g
Pretz Ayam BBQ 31g
Pretz Original 31g
Pretz Pizza 31g

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Description

Here are a few use cases for this project:

  1. Grocery Store Inventory Management: The model can be used in grocery stores or supermarkets to monitor their inventory levels of different varieties of Pocky. By recognizing which variant of Pocky is on the shelf, the model could provide data for automatic restocking and inventory management systems.

  2. Online Retail Services: E-commerce platforms selling snacks can utilize the model to classify and catalogue their inventory based on product images. This can make the search and listing process more efficient and accurate.

  3. Consumer Behavior Study: Market research companies can use this model to study consumer behavior in stores or at home by recognizing which variant of Pocky is more popular, frequently bought, or left untouched in a group of Pocky snacks.

  4. Quality Control: Manufacturers of Pocky can use this model in their production lines to identify and segregate Pocky snacks as per their types for quality control checks and accurate packaging.

  5. Interactive Retail Experiences: The model can be incorporated in AR-based applications. When customers scan a Pocky product using their smartphone, the application identifies the type of Pocky and provides product information, nutritional facts, and even suggests pairing drinks or recipes.

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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{
                            glico-v3_dataset,
                            title = { Glico V3 Dataset },
                            type = { Open Source Dataset },
                            author = { Adi Krena },
                            howpublished = { \url{ https://universe.roboflow.com/adi-krena-zpiio/glico-v3 } },
                            url = { https://universe.roboflow.com/adi-krena-zpiio/glico-v3 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { dec },
                            note = { visited on 2024-12-03 },
                            }
                        
                    

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