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**WARNING! This tool is currently** ![under_construction](http://www.textfiles.com/underconstruction/HeHeartlandPark2601underconstructionbar9.gif)
**For any planned changes, please have a look at the [Pull Requests](https://github.com/qurator-spk/eynollah/pulls).**
# Eynollah
> Document Layout Analysis
![](https://user-images.githubusercontent.com/952378/102350683-8a74db80-3fa5-11eb-8c7e-f743f7d6eae2.jpg)
## Introduction
This tool performs document layout analysis (segmentation) from image data and returns the results as [PAGE-XML](https://github.com/PRImA-Research-Lab/PAGE-XML).
It can currently detect the following layout classes/elements:
* Border
* Textregion
* Image
* Textline
* Separator
* Marginalia
* Initial (Drop Capital)
* [Border](https://ocr-d.de/en/gt-guidelines/pagexml/pagecontent_xsd_Complex_Type_pc_BorderType.html)
* [Textregion](https://ocr-d.de/en/gt-guidelines/pagexml/pagecontent_xsd_Complex_Type_pc_TextRegionType.html)
* [Textline](https://ocr-d.de/en/gt-guidelines/pagexml/pagecontent_xsd_Complex_Type_pc_TextLineType.html)
* [Image](https://ocr-d.de/en/gt-guidelines/pagexml/pagecontent_xsd_Complex_Type_pc_ImageRegionType.html)
* [Separator](https://ocr-d.de/en/gt-guidelines/pagexml/pagecontent_xsd_Complex_Type_pc_SeparatorRegionType.html)
* [Marginalia](https://ocr-d.de/en/gt-guidelines/trans/lyMarginalie.html)
* [Initial (Drop Capital)](https://ocr-d.de/en/gt-guidelines/trans/lyInitiale.html)
In addition, the tool can be used to detect the _Reading Order_ of regions. The final goal is to feed the output to an OCR model.
In addition, the tool can be used to detect the _[ReadingOrder](https://ocr-d.de/en/gt-guidelines/trans/lyLeserichtung.html)_ of regions. The final goal is to feed the output to an OCR model.
The tool uses a combination of various models and heuristics (see flowchart below for the different stages and how they interact):
* [Border detection](https://github.com/qurator-spk/eynollah#border-detection)
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* Finally, using the derived coordinates, bounding boxes are determined for each textline.
## Installation
`pip install .`
`pip install .` or
`pip install . -e` for editable installation
Alternatively, you can also use `make` with these targets:
`make install` or
`make install-dev` for editable installation
### Models
In order to run this tool you also need trained models. You can download our pretrained models from [qurator-data.de](https://qurator-data.de/eynollah/).
Alternatively, running `make models` will download and extract models to `$(PWD)/models_eynollah`.
## Usage
The basic command-line interface can be called like this:
eynollah \
-i <image file name> \
-o <directory to write output xml or enhanced image> \
-m <directory of models> \
-fl <if true, the tool will perform full layout analysis> \
-ae <if true, the tool will resize and enhance the image and produce the resulting image as output> \
-as <if true, the tool will check whether the document needs rescaling or not> \
-cl <if true, the tool will try to extract the contours of texlines instead of rectangle bounding boxes> \
-si <if a directory is given here, the tool will output image regions inside documents there>
```sh
eynollah \
-i <image file name> \
-o <directory to write output xml or enhanced image> \
-m <directory of models> \
-fl <if true, the tool will perform full layout analysis> \
-ae <if true, the tool will resize and enhance the image and produce the resulting image as output> \
-as <if true, the tool will check whether the document needs rescaling or not> \
-cl <if true, the tool will extract the contours of curved textlines instead of rectangle bounding boxes> \
-si <if a directory is given here, the tool will output image regions inside documents there>
```
The tool does accept and works better on original images (RGB format) than binarized images.
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* For some documents, while the quality is good, their scale is extremly large and the performance of tool decreases. In such cases you can set `-as` (**a**llow **s**caling) to `true`. With this option enabled, the tool will try to rescale the image and only then the layout detection process will begin.
* If you care about drop capitals (initials) and headings, you can set `-fl` (**f**ull **l**ayout) to `true`. As we can see in the case of full layout, we can currently distinguish 7 document layout classes/elements.
* If you care about drop capitals (initials) and headings, you can set `-fl` (**f**ull **l**ayout) to `true`. With this setting, the tool can currently distinguish 7 document layout classes/elements.
* In cases where the documents include curved headers or curved lines it is obvious that rectangular bounding boxes for textlines will not be a great option. For this, we have developed an option which tries to find contours of the curvy textlines. You can set `-cl` (**c**urved **l**ines) to `true` to enable this option. Be advised that this will increase the time needed for the tool to process the document.
* In cases where the document includes curved headers or curved lines, rectangular bounding boxes for textlines will not be a great option. In such cases it is strongly recommended to set the flag `-cl` (**c**urved **l**ines) to `true` to find countours of curved lines instead of rectangular boundinx boxes. Be advised that enabling this option increases the processing time of the tool.
* If you want to crop and save image regions inside the document, just provide a directory with the parameter, `-si` (**s**ave **i**mages).
* To crop and save image regions inside the document, set the parameter `-si` (**s**ave **i**mages) to true and provide a directory path to store the extracted images.
* This tool is actively being developed. If any problems occur or the performance does not meet your expectations, we welcome your feedback.
* This tool is actively being developed. If problems occur or the performance does not meet your expectations, we welcome your feedback via [issues](https://github.com/qurator-spk/eynollah/issues).