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Added tesseract ocr layoutparsing example #207

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Added tesseract ocr layoutparsing example #207

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7 changes: 6 additions & 1 deletion README.md
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Expand Up @@ -111,7 +111,12 @@ Extra steps are needed if you want to use Detectron2-based models. Please check

We provide a series of examples for to help you start using the layout parser library:

1. [Table OCR and Results Parsing](https://github.com/Layout-Parser/layout-parser/blob/main/examples/OCR%20Tables%20and%20Parse%20the%20Output.ipynb): `layoutparser` can be used for conveniently OCR documents and convert the output in to structured data.
1. Table OCR and Results Parsing: `layoutparser` can be used for conveniently OCR documents and convert the output in to structured data. Currently, `layoutparser` supports two types of OCR engines: Google Cloud Vision and Tesseract OCR engine. And we are going to provide more support in the future.

The tutorials are as follows :
1. [Google Cloud Vision](https://github.com/Layout-Parser/layout-parser/blob/main/examples/OCR%20Tables%20and%20Parse%20the%20Output.ipynb)
2. [Tesseract OCR](./examples/OCR_tesserocr_example.ipynb)


2. [Deep Layout Parsing Example](https://github.com/Layout-Parser/layout-parser/blob/main/examples/Deep%20Layout%20Parsing.ipynb): With the help of Deep Learning, `layoutparser` supports the analysis very complex documents and processing of the hierarchical structure in the layouts.

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16 changes: 8 additions & 8 deletions examples/OCR Tables and Parse the Output.ipynb
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672 changes: 672 additions & 0 deletions examples/OCR_tesserocr_example.ipynb
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