Datasets:
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Update README.md
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README.md
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path: data/dev-*
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- split: test
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path: data/test-*
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---
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task_categories:
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- image-to-text
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language:
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- TAL
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pretty_name: Split ICDAR2017 dataset
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---
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This dataset is a filtered version of the ICDAR2017 Competition on Handwritten Text Recognition, focusing on monograph texts written between 1800 and 1900. It consists of a total of **957 documents**, divided into training, validation, and testing sets, and is designed for post-correction of OCR (Optical Character Recognition) text.
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- **Total Documents**: 957
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- **Training Set**: 765
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- **Test Set**: 97
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## Purpose
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The dataset aims to improve the accuracy of digitized texts by providing a reliable
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## Structure
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The dataset is organized as follows:
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For more information, visit the original dataset source: [ICDAR2017 Competition on Post-OCR Text Correction](http://l3i.univ-larochelle.fr/ICDAR2017PostOCR).
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## Copyright
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The original corpus is publicly accessible, and I do not hold any rights to this deployment of the corpus.
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path: data/dev-*
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- split: test
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path: data/test-*
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task_categories:
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- image-to-text
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language:
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- TAL
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pretty_name: Split ICDAR2017 dataset
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---
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This dataset is a filtered version of the *ICDAR2017* Competition on Handwritten Text Recognition, focusing on monograph texts written between 1800 and 1900. It consists of a total of **957 documents**, divided into training, validation, and testing sets, and is designed for post-correction of OCR (Optical Character Recognition) text.
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- **Total Documents**: 957
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- **Training Set**: 765
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- **Test Set**: 97
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## Purpose
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The dataset aims to improve the accuracy of digitized texts by providing a reliable Ground Truth for comparison and correction, specifically addressing the challenges of French text of 19th century.
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## Structure
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The dataset is organized as follows:
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For more information, visit the original dataset source: [ICDAR2017 Competition on Post-OCR Text Correction](http://l3i.univ-larochelle.fr/ICDAR2017PostOCR).
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## Copyright
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The original corpus is publicly accessible, and I do not hold any rights to this deployment of the corpus.
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