# Eynollah > Perform document layout analysis (segmentation) from image data and return the results as [PAGE-XML](https://github.com/PRImA-Research-Lab/PAGE-XML). ![](https://user-images.githubusercontent.com/952378/102350683-8a74db80-3fa5-11eb-8c7e-f743f7d6eae2.jpg) ## Installation `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 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`. ### Training 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 The command-line interface can be called like this: ```sh eynollah \ -i \ -o \ -m \ -fl \ -ae \ -as \ -cl \ -si \ -sd \ -sa \ -tab \ -ib \ -ho \ -sl \ -ep ``` The tool performs better with RGB images than greyscale/binarized images. Additional documentation can be found in the [wiki](https://github.com/qurator-spk/eynollah/wiki).