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61 lines
2.1 KiB
Markdown
61 lines
2.1 KiB
Markdown
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# Table of Contents
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This python package contains modules to help with finding and extracting tabular
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data from a PDF or image into a CSV format.
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Given an image that contains a table…
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![img](resources/examples/example-page.png)
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Extract the the text into a CSV format…
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PRIZE,ODDS 1 IN:,# OF WINNERS*
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$3,9.09,"282,447"
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$5,16.66,"154,097"
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$7,40.01,"64,169"
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$10,26.67,"96,283"
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$20,100.00,"25,677"
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$30,290.83,"8,829"
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$50,239.66,"10,714"
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$100,919.66,"2,792"
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$500,"6,652.07",386
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"$40,000","855,899.99",3
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1,i223,
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Toa,,
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,,
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,,"* Based upon 2,567,700"
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The package is split into modules with narrow focuses.
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- `pdf_to_images` uses Poppler and ImageMagick to extract images from a PDF.
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- `extract_tables` finds and extracts table-looking things from an image.
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- `extract_cells` extracts and orders cells from a table.
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- `ocr_image` uses Tesseract to OCR the text from an image of a cell.
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- `ocr_to_csv` converts into a CSV the directory structure that `ocr_image` outputs.
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The outputs of a previous module can be used by a subsequent module so that they
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can be chained together to create the entire workflow, as demonstrated by the
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following shell script.
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#!/bin/sh
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PDF=$1
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python -m table_ocr.pdf_to_images $PDF | grep .png > /tmp/pdf-images.txt
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cat /tmp/pdf-images.txt | xargs -I{} python -m table_ocr.extract_tables {} | grep table > /tmp/extracted-tables.txt
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cat /tmp/extracted-tables.txt | xargs -I{} python -m table_ocr.extract_cells {} | grep cells > /tmp/extracted-cells.txt
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cat /tmp/extracted-cells.txt | xargs -I{} python -m table_ocr.ocr_image {}
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for image in $(cat /tmp/extracted-tables.txt); do
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dir=$(dirname $image)
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python -m table_ocr.ocr_to_csv $(find $dir/cells -name "*.txt")
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done
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The package was written in a [literate programming](https://en.wikipedia.org/wiki/Literate_programming) style. The source code at
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<https://eihli.github.io/image-table-ocr/pdf_table_extraction_and_ocr.html> is
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meant to act as the documentation and reference material.
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