pakaianfix Object Detection Dataset and Pre-Trained Model by identifikasiterong

Images

1693 images

Explore Dataset

Here are a few use cases for this project:

Online Retail: The "pakaianfix" model could be used by e-commerce platforms to categorize images of shirts into 'neat' (rapi) or 'not neat' (tidak rapi). This could help customers streamline their shopping experience by searching and sorting garments according to their preferences.
AI Personal Stylist: This model could be integrated into a virtual styling application. The application could provide outfit recommendations based on a user's preference for neat or not neat shirts which could then be paired with appropriate pants, jackets, or accessories.
Laundry Sorting Applications: Laundromats or laundry service providers could use the model to automatically sort clothes into neat and not neat piles for more precise cleaning processes. For instance, 'not neat' shirts may require additional attention or different cleaning methods.
Online Auctions & Second-hand Stores: These platforms could use the "pakaianfix" model to classify and categorize images of shirts by their condition (neat or not neat). This would allow users to filter and search items based on the status of their neatness, aiding in their buying decisions.
Automated Quality Control: In the textile or fashion industry, the model can be used in the quality control process to quickly identify neatly finished products and separate them from those not meeting the standards. This automation can help save time and increase production efficiency.

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{
                            pakaianfix_dataset,
                            title = { pakaianfix Dataset },
                            type = { Open Source Dataset },
                            author = { identifikasiterong },
                            howpublished = { \url{ https://universe.roboflow.com/identifikasiterong/pakaianfix } },
                            url = { https://universe.roboflow.com/identifikasiterong/pakaianfix },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { aug },
                            note = { visited on 2024-07-27 },
                            }