I am writing a Jupyter notebook with a proof of concept python code snippets to perform a few tasks. 
To start, write a snippet to iterate the current folder and read all the jpg/png files and for each file call textract DetectDocumentText API to extract all the text on the image.
Re-save the result with the same file name and txt extension.
Also make sure to: 
- Not reprocess any files that already have the txt file existing in the directory 
- Print a progress bar output using tdqm 
- Keep everything readable and properly componentized in methods 
- No need for __main__ implementations as it's a snippet to run on Jupyter notebook.

import os
import boto3
from tqdm import tqdm
from PIL import Image

def get_image_files(directory):
    """Get all jpg and png files in the given directory."""
    return [f for f in os.listdir(directory) if f.lower().endswith(('.jpg', '.png'))]

def should_process_file(file_path):
    """Check if the file should be processed (i.e., no corresponding txt file exists)."""
    txt_path = os.path.splitext(file_path)[0] + '.txt'
    return not os.path.exists(txt_path)

def extract_text_from_image(image_path):
    """Extract text from the image using HAQM Textract."""
    client = boto3.client('textract')
    
    with open(image_path, 'rb') as image:
        response = client.detect_document_text(Document={'Bytes': image.read()})
    
    extracted_text = []
    for item in response['Blocks']:
        if item['BlockType'] == 'LINE':
            extracted_text.append(item['Text'])
    
    return '\n'.join(extracted_text)

def save_text_to_file(text, file_path):
    """Save the extracted text to a file."""
    txt_path = os.path.splitext(file_path)[0] + '.txt'
    with open(txt_path, 'w', encoding='utf-8') as f:
        f.write(text)

def process_images_in_directory(directory):
    """Process all images in the given directory."""
    image_files = get_image_files(directory)
    
    for image_file in tqdm(image_files, desc="Processing images"):
        image_path = os.path.join(directory, image_file)
        
        if should_process_file(image_path):
            extracted_text = extract_text_from_image(image_path)
            save_text_to_file(extracted_text, image_path)

# Usage in Jupyter notebook
directory = '.'  # Current directory
process_images_in_directory(directory)