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@ -9,6 +9,12 @@ The goal of this project is to extract textlines of a document to feed an ocr mo
* Layout analysis
* Textline detection
* Heuristic methods
First three stages are done by using a pixel-wise segmentation. You can train your own model using this tool (https://github.com/qurator-spk/sbb_pixelwise_segmentation).
## Printspace or border extraction
From ocr point of view and in order to avoid texts outside printspace region, you need to detect and extract printspace region. As mentioned briefly earlier this is done by a binary pixelwise-segmentation. We have trained our model by a dataset of 2000 documents where about 1200 of them was from dhsegment project (you can download the dataset from here https://github.com/dhlab-epfl/dhSegment/releases/download/v0.2/pages.zip) and the rest was annotated by myself using our dataset in SBB.
This is worthy to mention that for page (printspace or border) extractation you have to feed model whole image at once and not in patches.
## Installation
`pip install .`

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