Assembled Object Detection Dataset and Pre-Trained Model by simon lee

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Explore Dataset

Here are a few use cases for this project:

Online Retail Store: The "Assembled" model could be used by an online fashion retailer to automatically categorize and sort incoming inventory by clothing type. This would significantly streamline the product listing process and ensure accurate search results for customers.
Fashion Trend Tracking: Firms involved in fashion market research might use the "Assembled" model to analyze and identify trends in street fashion, by scanning and interpreting public footage or photos shared on social media.
Personal Wardrobe Assistant: An application could use the "Assembled" model for managing users' wardrobes, suggesting outfits based on specific clothing items identified or sorting clothes by type for easier organization.
Dress Code Enforcement: In environments where specific attire is required or certain clothing is not allowed (such as schools or professional workplaces), the "Assembled" model could be employed to enforce these rules and identify transgressions.
Aid for Visually Impaired: Apps or wearable smart devices could employ the "Assembled" model to help visually impaired individuals identify their clothing, potentially offering them greater independence in their attire choices.

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{
                            assembled_dataset,
                            title = { Assembled Dataset },
                            type = { Open Source Dataset },
                            author = { simon lee },
                            howpublished = { \url{ https://universe.roboflow.com/simon-lee-ud1fw/assembled } },
                            url = { https://universe.roboflow.com/simon-lee-ud1fw/assembled },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { mar },
                            note = { visited on 2024-06-18 },
                            }