Dataset For Icdar2017 Competition On Handwritten Text Recognition On The Read Dataset (Icdar2017 Htr)

<strong>Train-A:</strong> Dataset of pages with manually revised baselines and the corresponding transcripts associated to them. This batch is small, 50 pages. Please, keep in mind that only the baselines have been manually corrected, The polygons associated to each line have not been manually reviewed.

<strong>Train-B:</strong> Dataset of pages without any layout or text line information. The corresponding transcripts are provided at page level with line breaks. It has 10k pages, though for convenience it is divided into two 5k page batches. This information is provided in PAGE format.

<strong>Test A:</strong> Dataset of pages with manually revised baselines. This batch has 65 pages. The polygons associated to each line have not been manually reviewed.

<strong>Test-B1:</strong> The same dataset of pages of the Test A, but annotated only with the geometry of regions. Text line information is not provided.

<strong>Test-B2:</strong> Dataset of page images annotated with the geometry of regions where to detect text line and recognize. It has 57 pages.

<strong>Baseline.tgz:</strong> Baseline system trained using the first 40 pages of Train-A. The system is based on the deep learning toolkit to transcribe handwritten text images called Laia.

More information at:

https://scriptnet.iit.demokritos.gr/competitions/~icdar2017htr/

<strong>训练集A（Train-A）:</strong> 包含已完成人工校正基线（baseline）的页面数据集，以及与之对应的转录文本。该批次体量较小，仅含50页。请注意，仅基线完成了人工校正，与每一行文本关联的多边形未经过人工审核。
<strong>训练集B（Train-B）:</strong> 不含任何版面布局或文本行信息的页面数据集，配套转录文本以页面级粒度提供并保留原始换行符。该数据集总计10000页，为便于使用分为两个各含5000页的子批次，相关信息以PAGE格式存储。
<strong>测试集A（Test A）:</strong> 包含已人工校正基线的页面数据集，该批次共计65页。与每一行文本关联的多边形未经过人工审核。
<strong>测试集B1（Test-B1）:</strong> 与测试集A使用的页面数据集完全一致，但仅标注了区域几何信息，未提供文本行相关内容。
<strong>测试集B2（Test-B2）:</strong> 标注有文本行检测与识别所需区域几何信息的页面图像数据集，总计57页。
<strong>基线模型包（Baseline.tgz）:</strong> 基于Laia（一款专为手写文本图像转录开发的深度学习工具包）开发，使用训练集A的前40页训练的基线系统。

更多信息请访问：
https://scriptnet.iit.demokritos.gr/competitions/~icdar2017htr/