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PP-Structure is an intelligent document analysis system developed by the PaddleOCR team, which aims to help developers better complete tasks related to document understanding such as layout analysis and table recognition.
The pipeline of PP-StructureV2 system is shown below. The document image first passes through the image direction correction module to identify the direction of the entire image and complete the direction correction. Then, two tasks of layout information analysis and key information extraction can be completed.
More technical details: 👉 PP-StructureV2 Technical Report
PP-StructureV2 supports independent use or flexible collocation of each module. For example, you can use layout analysis alone or table recognition alone. Click the corresponding link below to get the tutorial for each independent module:
The main features of PP-StructureV2 are as follows:
PP-StructureV2 supports the independent use or flexible collocation of each module. For example, layout analysis can be used alone, or table recognition can be used alone. Only the visualization effects of several representative usage methods are shown here.
The figure shows the pipeline of layout analysis + table recognition. The image is first divided into four areas of image, text, title and table by layout analysis, and then OCR detection and recognition is performed on the three areas of image, text and title, and the table is performed table recognition, where the image will also be stored for use.
The following figure shows the result of layout analysis on single word, please refer to the doc。
The following figure shows the effect of layout recovery based on the results of layout analysis and table recognition in the previous section.
Different colored boxes in the figure represent different categories.
In the figure, the red box represents Question
, the blue box represents Answer
, and Question
and Answer
are connected by green lines.
Start from Quick Start.
Some tasks need to use both the structured analysis models and the OCR models. For example, the table recognition task needs to use the table recognition model for structured analysis, and the OCR model to recognize the text in the table. Please select the appropriate models according to your specific needs.
For structural analysis related model downloads, please refer to:
For OCR related model downloads, please refer to:
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