-**Data introduction**: XFUND is a multilingual form comprehension dataset, which contains form data in 7 different languages, and all are manually annotated in the form of key-value pairs. The data for each language contains 199 form data, which are divided into 149 training sets and 50 test sets. Part of the image and the annotation box visualization are shown below:
-**Data introduction**: XFUND is a multilingual form comprehension dataset, which contains form data in 7 different languages, and all are manually annotated in the form of key-value pairs. The data for each language contains 199 form data, which are divided into 149 training sets and 50 test sets. Part of the image and the annotation box visualization are shown below.
Here are the common datasets of layout anlysis, which are being updated continuously. Welcome to contribute datasets.
-[PubLayNet dataset](#publaynet)
-[CDLA dataset](#CDLA)
-[TableBank dataset](#TableBank)
Most of the layout analysis datasets are object detection datasets. In addition to open source datasets, you can also label or synthesize datasets using tools such as [labelme](https://github.com/wkentaro/labelme) and so on.
-**Data introduction**: The PubLayNet dataset contains 350000 training images and 11000 validation images. There are 5 categories in total, namely: `text, title, list, table, figure`. Some images and their annotations as shown below.
-**Data introduction**: CDLA dataset contains 5000 training images and 1000 validation images with 10 categories, which are `Text, Title, Figure, Figure caption, Table, Table caption, Header, Footer, Reference, Equation`. Some images and their annotations as shown below.
-**Note**: When you train detection model on CDLA dataset using [PaddleDetection](https://github.com/PaddlePaddle/PaddleDetection/tree/develop), you need to remove the label `__ignore__` and `_background_`.
-**Data introduction**: TableBank dataset contains 2 types of document: Latex (187199 training images, 7265 validation images and 5719 testing images) and Word (73383 training images 2735 validation images and 2281 testing images). Some images and their annotations as shown below.
