title: How to extract data from image that contains tabular data?
body: <p>I am using pytesseract, pillow,cv2 to OCR an image and get the text present in the image. Since my input is a scanned PDF document, I first converted it into an image (JPEG) format and then tried extracting the text. I am only half way there. The input is a table and the titles are not being displayed, since the titles have a black background. I also tried <code>getstructuringelement</code> but unable to figure out a way. Here is what I have done until now-</p>
  
  <pre><code>import cv2
  import os  
  import numpy as np 
  import pytesseract
  #import pillow 
  
  #Since scanned PDF can't be handled by pdf2image, convert the scanned PDF into a JPEG format using the below code- 
  filename = path   
  from pdf2image import convert_from_path 
  pages = convert_from_path(filename, 500) for page in pages:
  page.save("dest", 'JPEG')
  
  
  imgname = "path" 
  oriimg = cv2.imread(imgname,cv2.IMREAD_COLOR) 
  cv2.imshow("original image", oriimg)
  cv2.waitKey(0)
  
  
  #img = cv2.resize(oriimg,None,fx=0.5,fy=0.5,interpolation=cv2.INTER_CUBIC) 
  img = cv2.resize(oriimg,(700,1500),interpolation=cv2.INTER_AREA) 
  #here length height  
  cv2.imshow("lol", img) 
  cv2.waitKey(0) 
  cv2.imwrite("changed_dimensionsimgpath", img)
  
  
  import PIL.Image  
  image = cv2.imread(imgname,cv2.IMREAD_COLOR) 
  grayedimg = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) grayedimg = 
  cv2.threshold(grayedimg, 0, 255, cv2.THRESH_BINARY | cv2.THRESH_OTSU)[1] 
  cv2.imwrite("H://newim.jpg", grayedimg)
  
  
  pytesseract.pytesseract.tesseract_cmd = r"C:\Program Files (x86)\Tesseract- 
  OCR\tesseract.exe"
  
  
  text = pytesseract.image_to_string(PIL.Image.open("path"))
  print(text)
  </code></pre>
  
  <p>My input table looks like below. The regions which have black background are not being identified by OCR and not being extracted as text.
  Any help would be greatly appreciated.<a href="https://i.stack.imgur.com/eMmNE.jpg" rel="noreferrer"><img src="https://i.stack.imgur.com/eMmNE.jpg" alt="My sample input"></a></p>
  
  <p>Output of this code for the image sample- </p>
  
  <pre><code>Sun by Select .
  
  F'I‘L‘Mlm":[ [Juir SHIIEF'. ”ﬁllﬁt Fadll'fi
  
  
  
  Brand Type Fragranm Unit: Ithange Dollm 'LChanga Men
  Eleanit' Sprayl Grange J.?IEBﬂI-Eﬂ' 11% '5H'1Elﬁ9ﬂﬂﬂ 35% I E
  Eleanlt! kﬁmnsul' Grange IEEEESWI 39% I521LESM1MH 1113553 ‘ E
  Dehuxe F‘mmr [emu 525.940 461% '51:EE?,GED,00 433.6% 5
  Datum: Anus»! ﬁring?) 4,3341%} 29% 513573300119 215% E
  Dem Spray ‘Drangr: £432,100 09% 515.223.:53000 154%
  
  Min Blaster Aemgul: Dramge ”2114033111 59% :SHSiMMﬂ H94:
  
  DiFlEIESIEf Sprawl Drama “NEW. 50% ‘5E1D1_E-BDM 141% I
  Incredlme Spray Lem 1.513.410" 483% a HELENE] $11143 I E
  
  t“ In
  
  1'"
  </code></pre>