I need to analyze the layout structure of different documents type like: pdf, doc, docx, odt etc.
My task is: Giving a document, group the text in blocks finding the correct boundaries of each.
I did some tests using Apache Tika, which is a good extractor, it is a very good tool but it often mess up the order of the block, let me explain a bit what i mean with ORDER.
Apache Tika just extracts the text, so if my document has two columns, Tika extracts the entire text of the first column and then the text of the second column, which is ok...but sometimes the text on the first column is related to the text on the second, like a table that has row relation.
So i must take care of the positions of each block, so the problems are:
Define the box boundaries, which is hard... i should understand if a sentence is starting a new block or not.
Define the orientation, for example, giving a table the "sentence" should be the row, NOT the column.
So basically here i have to deal with the layout structure to correcly understand the block boundaries.
I give you a visual example:
A classical extractor returns:
2019
2018
2017
2016
2015
2014
Oregon Arts Commission Individual Artist Fellowship...
Which is wrong (in my case) because the dates are related to the texts on the right.
This task is preparatory for other NLP analysis, so it is very important, because, for example doing, when i need to recognize the entities(NER) inside the text, and then identify their relations, working with the correct context is very important.
How to extract the text from the document and assembly related pieces of text (understanding the layout structure of the document) under the same block?
"Document Layout Analysis is performed to determine physical structure of a document, that is, to determine document components. These document components can consist of single connected components-regions [...] of pixels that are adjacent to form single regions [...] , or group of text lines.
LayoutParser is a Python library that provides a wide range of pre-trained deep learning models to detect the layout of a document image. The advantage of using LayoutParser is that it's really easy to implement. You literally only need a few lines of code to be able to detect the layout of your document image.
The definition. What Is Document Layout? Also called Document Design, it's the process of choosing how to present all of the basic document elements so your document's message is clear and effective. When a document is well designed, readers understand the information more quickly and easily.
This is but a partial solution to your issue, but it may simplify the task at hand. This tool receives PDF files and converts them to text files. It works pretty fast and can run on bulks of files.
It creates an output text file for each PDF. The advantage of this tool over others is that the output texts are aligned with accordance to their original layout.
For example, this is a resume with complex layout:
The output for it is the following text file:
Christopher Summary
Senior Web Developer specializing in front end development.
Morgan Experienced with all stages of the development cycle for
dynamic web projects. Well-versed in numerous programming
languages including HTML5, PHP OOP, JavaScript, CSS, MySQL.
Strong background in project management and customer
relations.
Skill Highlights
• Project management • Creative design
• Strong decision maker • Innovative
• Complex problem • Service-focused
solver
Experience
Contact
Web Developer - 09/2015 to 05/2019
Address: Luna Web Design, New York
177 Great Portland Street, London • Cooperate with designers to create clean interfaces and
W5W 6PQ simple, intuitive interactions and experiences.
• Develop project concepts and maintain optimal
Phone: workflow.
+44 (0)20 7666 8555
• Work with senior developer to manage large, complex
design projects for corporate clients.
Email:
• Complete detailed programming and development tasks
[email protected]
for front end public and internal websites as well as
challenging back-end server code.
LinkedIn:
• Carry out quality assurance tests to discover errors and
linkedin.com/christopher.morgan
optimize usability.
Languages Education
Spanish – C2
Bachelor of Science: Computer Information Systems - 2014
Chinese – A1
Columbia University, NY
German – A2
Hobbies Certifications
PHP Framework (certificate): Zend, Codeigniter, Symfony.
• Writing
Programming Languages: JavaScript, HTML5, PHP OOP, CSS,
• Sketching
SQL, MySQL.
• Photography
• Design
-----------------------Page 1 End-----------------------
Now your task is reduced to finding the bulks within a text file, and using the spaces between words as alignment hints.
As a start, I include a script that finds the margin between to columns of text and yields rhs
and lhs
- the text stream of the right and left columns respectively.
import numpy as np
import matplotlib.pyplot as plt
import re
txt_lines = txt.split('\n')
max_line_index = max([len(line) for line in txt_lines])
padded_txt_lines = [line + " " * (max_line_index - len(line)) for line in txt_lines] # pad short lines with spaces
space_idx_counters = np.zeros(max_line_index)
for idx, line in enumerate(padded_txt_lines):
if line.find("-----------------------Page") >= 0: # reached end of page
break
space_idxs = [pos for pos, char in enumerate(line) if char == " "]
space_idx_counters[space_idxs] += 1
padded_txt_lines = padded_txt_lines[:idx] #remove end page line
# plot histogram of spaces in each character column
plt.bar(list(range(len(space_idx_counters))), space_idx_counters)
plt.title("Number of spaces in each column over all lines")
plt.show()
# find the separator column idx
separator_idx = np.argmax(space_idx_counters)
print(f"separator index: {separator_idx}")
left_lines = []
right_lines = []
# separate two columns of text
for line in padded_txt_lines:
left_lines.append(line[:separator_idx])
right_lines.append(line[separator_idx:])
# join each bulk into one stream of text, remove redundant spaces
lhs = ' '.join(left_lines)
lhs = re.sub("\s{4,}", " ", lhs)
rhs = ' '.join(right_lines)
rhs = re.sub("\s{4,}", " ", rhs)
print("************ Left Hand Side ************")
print(lhs)
print("************ Right Hand Side ************")
print(rhs)
Plot output:
Text output:
separator index: 33
************ Left Hand Side ************
Christopher Morgan Contact Address: 177 Great Portland Street, London W5W 6PQ Phone: +44 (0)20 7666 8555 Email: [email protected] LinkedIn: linkedin.com/christopher.morgan Languages Spanish – C2 Chinese – A1 German – A2 Hobbies • Writing • Sketching • Photography • Design
************ Right Hand Side ************
Summary Senior Web Developer specializing in front end development. Experienced with all stages of the development cycle for dynamic web projects. Well-versed in numerous programming languages including HTML5, PHP OOP, JavaScript, CSS, MySQL. Strong background in project management and customer relations. Skill Highlights • Project management • Creative design • Strong decision maker • Innovative • Complex problem • Service-focused solver Experience Web Developer - 09/2015 to 05/2019 Luna Web Design, New York • Cooperate with designers to create clean interfaces and simple, intuitive interactions and experiences. • Develop project concepts and maintain optimal workflow. • Work with senior developer to manage large, complex design projects for corporate clients. • Complete detailed programming and development tasks for front end public and internal websites as well as challenging back-end server code. • Carry out quality assurance tests to discover errors and optimize usability. Education Bachelor of Science: Computer Information Systems - 2014 Columbia University, NY Certifications PHP Framework (certificate): Zend, Codeigniter, Symfony. Programming Languages: JavaScript, HTML5, PHP OOP, CSS, SQL, MySQL.
The next step would be to generalize this script to work on multi-page documents, remove redundant signs, etc.
Good luck!
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