invoice-processor-ml / src /pdf_utils.py
GSoumyajit2005's picture
feat: Update Dockerfile and requirements for PDF processing, add new dependencies, and refactor API structure
faa3050
# src/pdf_utils.py
import pdfplumber
from pdf2image import convert_from_path
from pathlib import Path
from typing import List, Union
import numpy as np
import cv2
def extract_text_from_pdf(pdf_path: str) -> str:
"""Extracts raw text from a digital PDF"""
path = Path(pdf_path)
if not path.exists():
raise FileNotFoundError(f"PDF not found: {pdf_path}")
try:
with pdfplumber.open(pdf_path) as pdf:
full_text = ""
for page in pdf.pages:
page_text = page.extract_text() or ""
full_text += page_text + "\n"
return full_text.strip()
except Exception as e:
raise ValueError(f"Failed to read PDF {pdf_path}: {str(e)}")
def convert_pdf_to_images(pdf_path: str) -> List[np.ndarray]:
"""
Converts a PDF into a list of OpenCV images (numpy arrays).
Required for the ML pipeline (LayoutLM) or Scanned PDFs.
Logic:
1. Use 'convert_from_path' to get PIL images.
2. Convert PIL images to numpy arrays (OpenCV format).
3. Return list of arrays.
"""
# 1. Convert to PIL images
try:
pil_images = convert_from_path(pdf_path)
except Exception as e:
raise ValueError(f"Error converting PDF to image: {e}")
cv_images = []
for pil_img in pil_images:
array = np.array(pil_img)
cv_images.append(cv2.cvtColor(array, cv2.COLOR_RGB2BGR))
return cv_images