convert pdf into txt using tesseract ocr

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# EXPLANATION
# EN  https://neculaifantanaru.com/en/convert-pdf-into-txt-using-tesseract-ocr.html
# RO  https://neculaifantanaru.com/convert-pdf-into-txt-using-tesseract-ocr.html
# --------------------------


import platform
from tempfile import TemporaryDirectory
from pathlib import Path
import os

import pytesseract
from pdf2image import convert_from_path
import PIL.Image
PIL.Image.MAX_IMAGE_PIXELS = 933120000

if platform.system() == "Windows":
    print("windows")
    # We may need to do some additional downloading and setup...
    # Windows needs a PyTesseract Download
    # https://github.com/UB-Mannheim/tesseract/wiki/Downloading-Tesseract-OCR-Engine

    pytesseract.pytesseract.tesseract_cmd = (
        r"c:\Program Files (x86)\Tesseract-OCR\tesseract.exe"
    )

    # Windows also needs poppler_exe
    # https://anaconda.org/conda-forge/poppler/files
    # Go to System Properties window (search on windows) -> click “Environment Variables.” -> PATH -> Edit -> New -> c:\Program Files\poppler-22.04.0\Library\bin   (put there the version of poppler with bin)
    path_to_poppler_exe = Path(r"c:\Program Files\poppler-22.04.0\Library\bin")

    # Put our output files in a sane place...
    out_directory = Path(r"~\Desktop").expanduser()
else:
    out_directory = Path("~").expanduser()
    print(out_directory)

# base psth in which all the xml files is present
base_path = r"1"
subfolders = []
converted_files = Path(r"converted files").expanduser()

# getting names of all xml files
for file in os.listdir(base_path):
  subfolders.append(file)

for i in range(len(subfolders)):
    print(f"Converted {subfolders[i]} \n")
    input_file = base_path+"/"+subfolders[i]
    # Path of the Input pdf
    PDF_file = Path(input_file)
    output_file = subfolders[i].replace(".pdf",".txt")
    # Store all the pages of the PDF in a variable
    image_file_list = []

    text_file = converted_files / Path(output_file)

    ''' Main execution point of the program'''
    with TemporaryDirectory() as tempdir:
        # Create a temporary directory to hold our temporary images.
        if platform.system() == "Windows":
            # print("Windows")
            pdf_pages = convert_from_path(PDF_file, 500, poppler_path=path_to_poppler_exe)
        else:
            pdf_pages = convert_from_path(PDF_file, 500)
        # Read in the PDF file at 500 DPI

        # Iterate through all the pages stored above
        for page_enumeration, page in enumerate(pdf_pages, start=1):
            # enumerate() "counts" the pages for us.

            # Create a file name to store the image
            filename = f"{tempdir}\page_{page_enumeration:03}.jpg"

            # Declaring filename for each page of PDF as JPG
                # For each page, filename will be:
                # PDF page 1 -> page_001.jpg
                # PDF page 2 -> page_002.jpg
                # PDF page 3 -> page_003.jpg
                # ....
                # PDF page n -> page_00n.jpg

                # Save the image of the page in system
            page.save(filename, "JPEG")
            image_file_list.append(filename)

            """
            Part #2 - Recognizing text from the images using OCR
            """

        with open(text_file, "a") as output_file:
                # Open the file in append mode so that
                # All contents of all images are added to the same file

                # Iterate from 1 to total number of pages
            for image_file in image_file_list:

                    # Set filename to recognize text from
                    # Again, these files will be:
                    # page_1.jpg
                    # page_2.jpg
                    # ....
                    # page_n.jpg

                    # Recognize the text as string in image using pytesserct
                text = str(((pytesseract.image_to_string(PIL.Image.open(image_file)))))

                    # The recognized text is stored in variable text
                    # Any string processing may be applied on text
                    # Here, basic formatting has been done:
                    # In many PDFs, at line ending, if a word can't
                    # be written fully, a 'hyphen' is added.
                    # The rest of the word is written in the next line
                    # Eg: This is a sample text this word here GeeksF-
                    # orGeeks is half on first line, remaining on next.
                    # To remove this, we replace every '-\n' to ''.
                text = text.replace("-\n", "")
                print(text)
                    # Finally, write the processed text to the file.
                output_file.write(text)

                # At the end of the with .. output_file block
                # the file is closed after writing all the text.
            # At the end of the with .. tempdir block, the
            # TemporaryDirectory() we're using gets removed!
        # End of main function!