task_categories:image-to-text language:ur license:cc-by-nc-4.0 arxiv:2306.15782 region:us ocr text recognition urdu-ocr utrnet
---
title: UrduDoc (UTRNet)
emoji: 📖
colorFrom: red
colorTo: green
license: cc-by-nc-4.0
task_categories:
- image-to-text
language:
- ur
tags:
- ocr
- text recognition
- urdu-ocr
- utrnet
pretty_name: UrduDoc
references:
  - https://github.com/abdur75648/UTRNet-High-Resolution-Urdu-Text-Recognition
  - https://abdur75648.github.io/UTRNet/
  - https://arxiv.org/abs/2306.15782
---

The **UrduDoc Dataset** is a benchmark dataset for Urdu text line detection in scanned documents. It is created as a byproduct of the **UTRSet-Real** dataset generation process. Comprising 478 diverse images collected from various sources such as books, documents, manuscripts, and newspapers, it offers a valuable resource for research in Urdu document analysis. It includes 358 pages for training and 120 pages for validation, featuring a wide range of styles, scales, and lighting conditions. It serves as a benchmark for evaluating printed Urdu text detection models, and the benchmark results of state-of-the-art models are provided. The Contour-Net model demonstrates the best performance in terms of h-mean.

The UrduDoc dataset is the first of its kind for printed Urdu text line detection and will advance research in the field. It will be made publicly available for non-commercial, academic, and research purposes upon request and execution of a no-cost license agreement. To request the dataset and for more information and details about the [UrduDoc ](https://paperswithcode.com/dataset/urdudoc), [UTRSet-Real](https://paperswithcode.com/dataset/utrset-real) & [UTRSet-Synth](https://paperswithcode.com/dataset/utrset-synth) datasets, please refer to the [Project Website](https://abdur75648.github.io/UTRNet/) of our paper ["UTRNet: High-Resolution Urdu Text Recognition In Printed Documents"](https://arxiv.org/abs/2306.15782)