This helps us to extract text as a separate instance of image

East Text Detection.py

# Necessary Imports
import textseg as ts
from PyPDF2 import PdfFileReader
from pdf2image import convert_from_path
import cv2
import json
import pandas as pd
import glob
import os

data = pd.DataFrame()
final_name_list=[]
final_text_opencv=[]
final_text_tessaract=[]
# Path of all Resume files
for i in resumes:
    pdf = PdfFileReader(open(i,'rb'))
    
    # Get fileName of each PDF File
    fname = i.split('/')[-1]
    
    # Check how many page each PDF contains 
    print(pdf.getNumPages())
    
    # Convert pdf object to image 
    images = convert_from_path(i)
    resumes_img=[]
    
    # append all image instance to a list to pass them through model
    for j in range(len(images)):
    
         # Save pages as images in the pdf
        images[j].save(path_to_write+fname.split('.')[0]+'_'+ str(j) +'.jpg', 'JPEG')
        resumes_img.append(path_to_write+fname.split('.')[0]+'_'+ str(j) +'.jpg')
    name_list = fname.split('.')[0]+'_' +'.jpg'
    text_opencv=[]
    text_tessaract=[]
    for i in resumes_img:
    
        # read image using opencv
        frame=cv2.imread(i)
        os.remove(i)
        img = i.split("/")[2]
        
        # Pass the image to the model to get the text instance present in the image.
        output_img,label,dilate, c_dict,df1, split_img=ts.get_text_seg(frame, img)
        cv2.imwrite(path_to_write+img.split('.')[0]+".png",output_img)
        for i in range(len(split_img)):
        
            # This Loop will helps us to save the instance of text as a individual image.
            cv2.imwrite(path_to_write+img.split('.')[0]+str(i)+".png", split_img[i])
        text_opencv.append(c_dict)
        text_tessaract+=text_from_tesseract(output_img)
        tesseract_str = ''.join(text_tessaract)   
    final_name_list.append(name_list)
    final_text_opencv.append(text_opencv)
    final_text_tessaract.append(tesseract_str)
    
# we are selecting the index 0 as we have passed one PDF as a input which contains one Page
print(final_text_opencv[0])