Marico Object Detection Dataset and Pre-Trained Model by Marico

Images

5897 images

Explore Dataset

Here are a few use cases for this project:

Intelligent Retail Inventory Management: The model can be used to automate tracking of inventory in real-time on retail shelves. It can identify low stock and trigger re-stocking procedures ensuring adequate supply of products.
Retail Checkout Automation: The model can be integrated into self-checkout systems. It can identify items in shopping carts/baskets, preventing the need for manual scanning, and thus speeding up the checkout process.
Market Analysis and Research: The visibility and popularity of brands on commercial shelves can be analyzed using this model, informing data-driven decisions for businesses in the retail sector.
Price Comparison Applications: Applications that aid shoppers by providing price comparison across stores can use this model to gather data by identifying products from images captured in different stores.
Consumer Trend Analysis: By consistently capturing and analyzing images from retail stores, the model can help track consumer buying trends by identifying the frequency and quantity of particular products being sold.

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{
                            marico-tg0wc_dataset,
                            title = { Marico Dataset },
                            type = { Open Source Dataset },
                            author = { Marico },
                            howpublished = { \url{ https://universe.roboflow.com/marico/marico-tg0wc } },
                            url = { https://universe.roboflow.com/marico/marico-tg0wc },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { nov },
                            note = { visited on 2024-04-20 },
                            }