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This python package contains modules to help with finding and extracting tabular data from a PDF or image into a CSV format.

Given an image that contains a table…

Extract the the text into a CSV format…

PRIZE,ODDS 1 IN:,# OF WINNERS*
$3,9.09,"282,447"
$5,16.66,"154,097"
$7,40.01,"64,169"
$10,26.67,"96,283"
$20,100.00,"25,677"
$30,290.83,"8,829"
$50,239.66,"10,714"
$100,919.66,"2,792"
$500,"6,652.07",386
"$40,000","855,899.99",3
1,i223,
Toa,,
,,
,,"* Based upon 2,567,700"

The package is split into modules with narrow focuses.

pdf_to_images uses Poppler and ImageMagick to extract images from a PDF.
extract_tables finds and extracts table-looking things from an image.
extract_cells extracts and orders cells from a table.
ocr_image uses Tesseract to OCR the text from an image of a cell.
ocr_to_csv converts into a CSV the directory structure that ocr_image outputs.

The outputs of a previous module can be used by a subsequent module so that they can be chained together to create the entire workflow, as demonstrated by the following shell script.

#!/bin/sh

PDF=$1

python -m table_ocr.pdf_to_images $PDF | grep .png > /tmp/pdf-images.txt
cat /tmp/pdf-images.txt | xargs -I{} python -m table_ocr.extract_tables {}  | grep table > /tmp/extracted-tables.txt
cat /tmp/extracted-tables.txt | xargs -I{} python -m table_ocr.extract_cells {} | grep cells > /tmp/extracted-cells.txt
cat /tmp/extracted-cells.txt | xargs -I{} python -m table_ocr.ocr_image {} --psm 7 -l table-ocr

for image in $(cat /tmp/extracted-tables.txt); do
    dir=$(dirname $image)
    python -m table_ocr.ocr_to_csv $(find $dir/cells -name "*.txt")
done

The package was written in a literate programming style. The source code at https://eihli.github.io/image-table-ocr/pdf_table_extraction_and_ocr.html is meant to act as the documentation and reference material.

BeyondYourself/image-table-ocr

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