Table of Contents

1. Overview
2. Requirements
3. Demo
4. Modules

Overview

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"

Requirements

Along with the python requirements that are listed in setup.py and that are automatically installed when installing this package through pip, there are a few external requirements for some of the modules.

I haven’t looked into the minimum required versions of these dependencies, but I’ll list the versions that I’m using.

• pdfimages 20.09.0 of Poppler
• tesseract 5.0.0 of Tesseract
• mogrify 7.0.10 of ImageMagick

Demo

There is a demo module that will download an image given a URL and try to extract tables from the image and process the cells into a CSV. You can try it out with one of the images included in this repo.

1. pip3 install table_ocr
2. python3 -m table_ocr.demo https://raw.githubusercontent.com/eihli/image-table-ocr/master/resources/test_data/simple.png

That will run against the following image:

The following should be printed to your terminal after running the above commands.

Running `extract_tables.main([/tmp/demo_p9on6m8o/simple.png]).`
Extracted the following tables from the image:
[('/tmp/demo_p9on6m8o/simple.png', ['/tmp/demo_p9on6m8o/simple/table-000.png'])]
Processing tables for /tmp/demo_p9on6m8o/simple.png.
Processing table /tmp/demo_p9on6m8o/simple/table-000.png.
Extracted 18 cells from /tmp/demo_p9on6m8o/simple/table-000.png
Cells:
/tmp/demo_p9on6m8o/simple/cells/000-000.png: Cell
/tmp/demo_p9on6m8o/simple/cells/000-001.png: Format
/tmp/demo_p9on6m8o/simple/cells/000-002.png: Formula
...

Here is the entire CSV output:

Cell,Format,Formula
B4,Percentage,None
C4,General,None
D4,Accounting,None
E4,Currency,"=PMT(B4/12,C4,D4)"
F4,Currency,=E4*C4

Modules

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 {}

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.