Trolley_Detection Object Detection Dataset and Pre-Trained Model by Trolleys

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Here are a few use cases for this project:

Retail Intelligence: The "Trolley_Detection" model could be deployed in stores and supermarkets to analyze customer behaviors, like how often a trolley or wagon is used, how long it stays in specific aisles, or when it's abandoned.
Inventory Management: It can help in monitoring the availability and usage of trolleys in various sections of a store, aiding planning, and distribution efforts.
Shopping Experience Improvement: Stores could analyze the data to improve layout and flow to prevent congestion and improve customer experience, perhaps by providing more trolleys in high-demand areas.
Security and Lost Trolley Recovery: Malls or supermarkets can use it to track abandoned trolleys to ensure they are not used inappropriately or left in areas where they can cause inconvenience or potential security risks.
Accessibility Assistance in Smart Cities: With the help of this model, smart cities could detect and track available trolleys or wagons in public areas, providing real-time information for those requiring mobility assistance.

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{
                            trolley_detection_dataset,
                            title = { Trolley_Detection Dataset },
                            type = { Open Source Dataset },
                            author = { Trolleys },
                            howpublished = { \url{ https://universe.roboflow.com/trolleys/trolley_detection } },
                            url = { https://universe.roboflow.com/trolleys/trolley_detection },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { mar },
                            note = { visited on 2024-05-06 },
                            }