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