I am generating word x,y coordinates with PDFMiner in the below example, however the results are on a line by line basis. How can I split each word from another word, rather splitting groups of words line by line (see example below). I have tried several of the arguments in the PDFMiner tutorial. LTTextBox and LTText were both tried. Moreover, I cannot use beginning and end offsets normally used in text analytics.
This PDF is a good example, this is used in the code below.
http://www.africau.edu/images/default/sample.pdf
from pdfminer.layout import LAParams, LTTextBox, LTText
from pdfminer.pdfpage import PDFPage
from pdfminer.pdfinterp import PDFPageInterpreter, PDFResourceManager
from pdfminer.converter import PDFPageAggregator
#Imports Searchable PDFs and prints x,y coordinates
fp = open('C:\sample.pdf', 'rb')
manager = PDFResourceManager()
laparams = LAParams()
dev = PDFPageAggregator(manager, laparams=laparams)
interpreter = PDFPageInterpreter(manager, dev)
pages = PDFPage.get_pages(fp)
for page in pages:
print('--- Processing ---')
interpreter.process_page(page)
layout = dev.get_result()
for lobj in layout:
if isinstance(lobj, LTText):
x, y, text = lobj.bbox[0], lobj.bbox[3], lobj.get_text()
print('At %r is text: %s' % ((x, y), text))
This returns the x,y coordinates for the searchable PDF as demonstrated below:
--- Processing ---
At (57.375, 747.903) is text: A Simple PDF File
At (69.25, 698.098) is text: This is a small demonstration .pdf file -
At (69.25, 674.194) is text: just for use in the Virtual Mechanics tutorials. More text. And more
text. And more text. And more text. And more text.
Wanted result (the coordinates are proxy for demonstration):
--- Processing ---
At (57.375, 747.903) is text: A
At (69.25, 698.098) is text: Simple
At (69.25, 674.194) is text: PDF
At (69.25, 638.338) is text: File
With PDFMiner, after going through each line (as you already did), you may only go through each character in the line.
I did this with the code below, while trying to record the x, y of the first character per word and setting up a condition to split the words at each LTAnno (e.g. \n ) or .get_text() == ' ' empty space.
from pdfminer.layout import LAParams, LTTextBox, LTText, LTChar, LTAnno
from pdfminer.pdfpage import PDFPage
from pdfminer.pdfinterp import PDFPageInterpreter, PDFResourceManager
from pdfminer.converter import PDFPageAggregator
#Imports Searchable PDFs and prints x,y coordinates
fp = open('C:\sample.pdf', 'rb')
manager = PDFResourceManager()
laparams = LAParams()
dev = PDFPageAggregator(manager, laparams=laparams)
interpreter = PDFPageInterpreter(manager, dev)
pages = PDFPage.get_pages(fp)
for page in pages:
print('--- Processing ---')
interpreter.process_page(page)
layout = dev.get_result()
x, y, text = -1, -1, ''
for textbox in layout:
if isinstance(textbox, LTText):
for line in textbox:
for char in line:
# If the char is a line-break or an empty space, the word is complete
if isinstance(char, LTAnno) or char.get_text() == ' ':
if x != -1:
print('At %r is text: %s' % ((x, y), text))
x, y, text = -1, -1, ''
elif isinstance(char, LTChar):
text += char.get_text()
if x == -1:
x, y, = char.bbox[0], char.bbox[3]
# If the last symbol in the PDF was neither an empty space nor a LTAnno, print the word here
if x != -1:
print('At %r is text: %s' % ((x, y), text))
The output looks as follows
At (64.881, 747.903) is text: A
At (90.396, 747.903) is text: Simple
At (180.414, 747.903) is text: PDF
At (241.92, 747.903) is text: File
Perhaps you can optimize the conditions to detect the words for your requirements and liking. (e.g. cut punctuation marks .!? at the end of words)