Yolov7 Computer Vision Project
Here are a few use cases for this project:
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Grocery Store Inventory Management: The Yolov7 model can automatically recognize and track product levels on the shelves in real-time, alerting employees when restocking is needed for specific items such as Milk, Milk-Chocolate, Juice, Juice-Pure, Cereal-Chocolate, and Cereal.
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Smart Retail Experiences: In stores equipped with smart carts, the model can be used to automatically identify and add items to the customers' digital checkout list as they place them into their cart, speeding up the checkout process.
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Automated Checkout Systems: The model can be integrated into self-checkout systems to identify and confirm the products customers are buying, reducing reliance on manual input of product codes.
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Online Grocery Services: The AI can be used for quality control, ensuring the correctness of orders in warehouses before delivery to the customers, reducing the error rate in fulfilling online orders.
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Diet Monitoring Application: The model can be incorporated into a diet tracking app, allowing users to simply point their phone's camera towards their food items to automatically log their nutritional intake based on the identified product classes.
Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
yolov7-r2pka_dataset,
title = { Yolov7 Dataset },
type = { Open Source Dataset },
author = { custom yolov7 },
howpublished = { \url{ https://universe.roboflow.com/custom-yolov7/yolov7-r2pka } },
url = { https://universe.roboflow.com/custom-yolov7/yolov7-r2pka },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { may },
note = { visited on 2024-04-29 },
}
Connect Your Model With Program Logic
Find utilities and guides to help you start using the Yolov7 project in your project.
Source
Last Updated
a year ago
Project Type
Object Detection
Subject
Products
Views: 61
Downloads: 3
