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        "author": "Konstantin Baierer, Mike Gerber",
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        "description": "# ocrd_calamari\n\n> Recognize text using [Calamari OCR](https://github.com/Calamari-OCR/calamari).\n\n[![image](https://circleci.com/gh/OCR-D/ocrd_calamari.svg?style=svg)](https://circleci.com/gh/OCR-D/ocrd_calamari)\n[![image](https://img.shields.io/pypi/v/ocrd_calamari.svg)](https://pypi.org/project/ocrd_calamari/)\n[![image](https://codecov.io/gh/OCR-D/ocrd_calamari/branch/master/graph/badge.svg)](https://codecov.io/gh/OCR-D/ocrd_calamari)\n\n## Introduction\n\n**ocrd_calamari** offers a [OCR-D](https://ocr-d.de) compliant workspace processor for the functionality of Calamari OCR. It uses OCR-D workspaces (METS) with [PAGE XML](https://github.com/PRImA-Research-Lab/PAGE-XML) documents as input and output.\n\nThis processor only operates on the text line level and so needs a line segmentation (and by extension a binarized \nimage) as its input.\n\nIn addition to the line text it may also output word and glyph segmentation\nincluding per-glyph confidence values and per-glyph alternative predictions as\nprovided by the Calamari OCR engine, using a `textequiv_level` of `word` or\n`glyph`. Note that while Calamari does not provide word segmentation, this\nprocessor produces word segmentation inferred from text\nsegmentation and the glyph positions. The provided glyph and word segmentation\ncan be used for text extraction and highlighting, but is probably not useful for\nfurther image-based processing.\n\n![Example output as viewed in PAGE Viewer](https://github.com/OCR-D/ocrd_calamari/raw/screenshots/output-in-page-viewer.jpg)\n\n## Installation\n\n### From PyPI\n\n```\npip install ocrd_calamari\n```\n\n### From Repo\n\n```sh\npip install .\n```\n\n## Install models\n\nDownload models trained on GT4HistOCR data:\n\n```\nmake gt4histocr-calamari1\nls gt4histocr-calamari1\n```\n\nManual download: [model.tar.xz](https://qurator-data.de/calamari-models/GT4HistOCR/2019-12-11T11_10+0100/model.tar.xz)\n\n## Example Usage\nBefore using `ocrd-calamari-recognize` get some example data and model, and\nprepare the document for OCR:\n```\n# Download model and example data\nmake gt4histocr-calamari1\nmake actevedef_718448162\n\n# Create binarized images and line segmentation using other OCR-D projects\ncd actevedef_718448162\nocrd-olena-binarize -P impl sauvola-ms-split -I OCR-D-IMG -O OCR-D-IMG-BIN\nocrd-tesserocr-segment-region -I OCR-D-IMG-BIN -O OCR-D-SEG-REGION\nocrd-tesserocr-segment-line -I OCR-D-SEG-REGION -O OCR-D-SEG-LINE\n```\n\nFinally recognize the text using ocrd_calamari and the downloaded model:\n```\nocrd-calamari-recognize -P checkpoint \"../gt4histocr-calamari1/*.ckpt.json\" -I OCR-D-SEG-LINE -O OCR-D-OCR-CALAMARI\n```\n\nor\n\n```\nocrd-calamari-recognize -P checkpoint_dir \"../gt4histocr-calamari1\" -I OCR-D-SEG-LINE -O OCR-D-OCR-CALAMARI\n```\n\n\nYou may want to have a look at the [ocrd-tool.json](ocrd_calamari/ocrd-tool.json) descriptions\nfor additional parameters and default values.\n\n## Development & Testing\nFor information regarding development and testing, please see\n[README-DEV.md](README-DEV.md).\n\n\n",
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