Socks-number Object Detection Dataset and Pre-Trained Model by Socks

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Explore Dataset

Here are a few use cases for this project:

Document Annotation: The model can be applied in navigating and categorizing various documents, especially technical ones as it can identify symbols, figures, page numbers, etc. For example, it could be used to scan engineering schematics or architecture plans.
Educational Resources Management: The model can find specific diagrams or figures in textbooks or educational resources by identifying the "figure_name" or "in_box" classes. It's useful in digitized learning where content can be isolated and tagged, and then referred to during class sessions.
Navigational Assistance in Large Datasets: By identifying 'Page_numb', 'arrow_in', 'arrow_out', the model can assist in data navigation in large datasets or files, making tasks efficient for data scientists and researchers.
Automated Diagram Analysis: For those in the IT sector, the model could scan through computer network diagrams or system architectures, recognizing aspects like 'arrow_out' or 'underline' to analyze the flow of data or processes.
Content Filtering: In digital libraries or resources, this model can enhance search capabilities by recognizing the specific elements in documents or materials, thus improving user experience by filtering and providing more accurate results on search queries.

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{
                            socks-number_dataset,
                            title = { Socks-number Dataset },
                            type = { Open Source Dataset },
                            author = { Socks },
                            howpublished = { \url{ https://universe.roboflow.com/socks/socks-number } },
                            url = { https://universe.roboflow.com/socks/socks-number },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { oct },
                            note = { visited on 2024-04-26 },
                            }