Abdelnasser Ahmed

ShelfCPlanogram

Object Detection

ShelfCPlanogram Computer Vision Project

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750 images
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Here are a few use cases for this project:

  1. Retail Inventory Management: ShelfCPlanogram can be used by store owners and managers to analyze inventory levels of different chocolate bar classes on store shelves. By identifying the type and quantity of chocolate bars, they can optimize inventory, restocking frequency, and detect possible issues such as out-of-stock products.

  2. Consumer Behavior Analysis: ShelfCPlanogram can be used for market research purposes by tracking sales trends and customer preferences for specific chocolate bar classes. Researchers can analyze data gathered from computer vision models to gain insights into consumer habits and preferences.

  3. Store Shelf Optimization: By identifying the presence and location of each chocolate bar class, ShelfCPlanogram can be used to optimize store shelf layout and product placement based on sales performance, customer preferences, and visual appeal.

  4. Automated Checkout Systems: ShelfCPlanogram can be integrated with advanced checkout systems, facilitating a seamless and accurate self-checkout process. By correctly identifying each chocolate bar class, customers can enjoy a faster and more convenient shopping experience, while retailers can reduce instances of mispricing and shrinkage.

  5. Advertising and Marketing Research: ShelfCPlanogram can be used to analyze the effectiveness of in-store marketing campaigns and promotions for different chocolate bar classes. By evaluating the impact of shelf displays, promotional materials, and pricing strategies, brands can fine-tune their advertising efforts and improve overall sales.

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{
                            shelfcplanogram_dataset,
                            title = { ShelfCPlanogram Dataset },
                            type = { Open Source Dataset },
                            author = { Abdelnasser Ahmed },
                            howpublished = { \url{ https://universe.roboflow.com/abdelnasser-ahmed/shelfcplanogram } },
                            url = { https://universe.roboflow.com/abdelnasser-ahmed/shelfcplanogram },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { may },
                            note = { visited on 2024-06-26 },
                            }
                        

Connect Your Model With Program Logic

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

Last Updated

a year ago

Project Type

Object Detection

Subject

Chocolate-bars

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Views in previous 30 days: 0

Downloads: 3

Downloads in previous 30 days: 0

License

MIT

Classes

0_0_crispello 0_32_flake 0_40_bubbly 0_40_bubbly_oreo 0_large_mandoline 0_twin_mandoline choco_0_oreo_enrobed choco_160_marv_creations choco_28_bubbly choco_34_dellight choco_38_marv_creations choco_38_oreo choco_dairy_milk choco_fruits_and_nuts choco_large_bubbly choco_large_dairy_milk choco_large_oreo moro_red moro_yellow nuts_dairy_milk nuts_large_daily_milk yellow_dairy_milk