File size: 1,809 Bytes
d9e3edb | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 | import fitz # PyMuPDF
import pytesseract
from PIL import Image
# Define a function to extract text from all pages of a PDF
def extract_text_from_pdf(pdf_path, dpi=300):
"""
Extract text from all pages of a PDF.
Args:
pdf_path (str): Path to the PDF file.
dpi (int): Resolution for converting PDF pages to images (default: 300).
Returns:
dict: A dictionary where keys are page numbers (1-based) and values are extracted text.
"""
# Open the PDF file
pdf_document = fitz.open(pdf_path)
extracted_text = {}
for page_number in range(len(pdf_document)):
# Select the page
page = pdf_document[page_number]
# Convert the page to an image
pixmap = page.get_pixmap(dpi=dpi)
# Save the image to a temporary file
image = Image.frombytes("RGB", [pixmap.width, pixmap.height], pixmap.samples)
# Extract text from the image using Tesseract
text = pytesseract.image_to_string(image)
print(text)
# Store the text in the dictionary
extracted_text[page_number + 1] = text
# Close the PDF document
pdf_document.close()
return extracted_text
# Usage example
if __name__ == "__main__":
# pdf_path = "c:/Abhi-MTech/Sem-1/AI/Books/Artificial.Intelligence.A.Modern.Approach.4th.Edition.Peter.Norvig. Stuart.Russell.Pearson.9780134610993.EBooksWorld.ir.pdf" # Path to your PDF file
pdf_path = "c:/Abhi-MTech/Sem-1/AI/AI Technical.pdf" # Path to your PDF file
try:
all_text = extract_text_from_pdf(pdf_path)
for page_num, text in all_text.items():
print(f"Page {page_num} Text:")
print(text)
print("-" * 80) # Separator for readability
except Exception as e:
print(f"Error: {e}")
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