Empty slots in shelves 2 Computer Vision Project
Here are a few use cases for this project:
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Inventory Management: Retailers or supermarkets can use this model to instantly detect empty slots on their shelves and restock efficiently.
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Warehouse Optimization: Warehouses can implement the model to identify empty sections in their arrangements, giving them a better understanding of space usage and potential optimization.
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Automated Retail: Vending machine operators could benefit from the model by having it automatically recognize low stock or empty slots and send alerts for needed restocking.
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Library Management: Libraries might utilize this model to recognize empty slots in bookshelf organization to plan for ordering or repositioning of books.
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Smart Home Organization: Homeowners can use this model in smart home applications to keep track of empty slots in their pantry or refrigerator, and create shopping lists accordingly.
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.
YOLOv8
This project has a YOLOv8 model checkpoint available for inference with Roboflow Deploy. YOLOv8 is a new state-of-the-art real-time object detection model.
Cite this Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{ empty-slots-in-shelves-2_dataset,
title = { Empty slots in shelves 2 Dataset },
type = { Open Source Dataset },
author = { FYP },
howpublished = { \url{ https://universe.roboflow.com/fyp-qtd0e/empty-slots-in-shelves-2 } },
url = { https://universe.roboflow.com/fyp-qtd0e/empty-slots-in-shelves-2 },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { oct },
note = { visited on 2023-12-04 },
}Find utilities and guides to help you start using the Empty slots in shelves 2 project in your project.
