What do I need to build or improve this OCR (Optical character recognition) that can return any handwritten accurately out of a pdf file? I really need your help guys. So far, when I run it the code return wrong value for what is handwritten. What do you think I can add so the program can adapt. The goal is to create a simple program that can succeed to adapt and be accurate as PEN TO PRINT software of Mac. ANY IDEA AND SUGGESTION IS WELCOMED.
import cv2
from pdf2image import convert_from_path
import pytesseract
import numpy as np
# Step 1: Convert PDF to images
pdf_path = '/Location of your file/')
# Step 2: Preprocess and extract text from images
def preprocess_image(image):
processed_image = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2GRAY)
return processed_image
# Step 3: Recognize text using Tesseract OCR
def recognize_text(image):
recognized_text = pytesseract.image_to_string(image)
return recognized_text
# Step 4: Extract text from PDF
def extract_text_from_pdf(images):
extracted_text = []
for image in images:
# Step 2: Preprocess the image
processed_image = preprocess_image(image)
# Step 3: Recognize text using Tesseract OCR
text = recognize_text(processed_image)
# Append the recognized text to the extracted_text list
extracted_text.append(text)
return extracted_text
# Step 5: Process the PDF and extract text
extracted_text = extract_text_from_pdf(images)
# Step 6: Print the extracted text
for page_num, text in enumerate(extracted_text):
print(f"Page {page_num+1}:\n{text}\n")
