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# Eynollah # Eynollah
> Document Layout Analysis (segmentation) using pre-trained models and heuristics > Document Layout Analysis with Deep Learning and Heuristics
[![PyPI Version](https://img.shields.io/pypi/v/eynollah)](https://pypi.org/project/eynollah/) [![PyPI Version](https://img.shields.io/pypi/v/eynollah)](https://pypi.org/project/eynollah/)
[![CircleCI Build Status](https://circleci.com/gh/qurator-spk/eynollah.svg?style=shield)](https://circleci.com/gh/qurator-spk/eynollah) [![CircleCI Build Status](https://circleci.com/gh/qurator-spk/eynollah.svg?style=shield)](https://circleci.com/gh/qurator-spk/eynollah)
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* [OCR-D](https://github.com/qurator-spk/eynollah#use-as-ocr-d-processor) interface * [OCR-D](https://github.com/qurator-spk/eynollah#use-as-ocr-d-processor) interface
## Installation ## Installation
Python versions `3.8-3.11` with Tensorflow versions >=`2.12` on Linux are currently supported. Unfortunately we can not currently support Windows or MacOS. Python versions `3.8-3.11` with Tensorflow versions >=`2.12` on Linux are currently supported. While we can not provide support for Windows or MacOS, Windows users may be able to install and run the tool through Linux in [WSL](https://learn.microsoft.com/en-us/windows/wsl/).
Windows users may be able to successfully run the tool through [WSL](https://learn.microsoft.com/en-us/windows/wsl/).
For (limited) GPU support the CUDA toolkit needs to be installed. For (limited) GPU support the CUDA toolkit needs to be installed.
You can either install via You can either install from PyPI via
``` ```
pip install eynollah pip install eynollah
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cd eynollah; pip install -e . cd eynollah; pip install -e .
``` ```
Alternatively, you can run `make install` or `make install-dev` for editable installation. Alternatively, run `make install` or `make install-dev` for editable installation.
## Models ## Models
Pre-trained models can be downloaded from [qurator-data.de](https://qurator-data.de/eynollah/). Pre-trained models can be downloaded from [qurator-data.de](https://qurator-data.de/eynollah/). In case you want to train your own model with Eynollah, have a look at [`train`](https://github.com/qurator-spk/eynollah/tree/main/eynollah/eynollah/train).
In case you want to train your own model to use with Eynollah, have a look at [sbb_pixelwise_segmentation](https://github.com/qurator-spk/sbb_pixelwise_segmentation).
## Usage ## Usage
The command-line interface can be called like this: The command-line interface can be called like this:

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