| |
|
|
| from PIL import Image |
| import pytesseract |
| from pdf2image import convert_from_bytes |
| import os |
| from concurrent.futures import ThreadPoolExecutor |
|
|
| def enhance_image_fast(image: Image.Image) -> Image.Image: |
| """A lightweight image enhancement pipeline optimized for speed.""" |
| return image.convert('L').point(lambda x: 0 if x < 155 else 255, '1') |
|
|
| def extract_text_from_image_fast(image: Image.Image) -> str: |
| """Extracts text using Tesseract with a configuration favoring speed.""" |
| fast_config = r'--oem 1 --psm 6' |
| text = pytesseract.image_to_string(image, config=fast_config) |
| return text |
|
|
| def _process_single_page_fast(page_image: Image.Image) -> str: |
| """Helper function that uses the new fast methods.""" |
| enhanced_image = enhance_image_fast(page_image) |
| return extract_text_from_image_fast(enhanced_image) |
|
|
| def process_pdf_in_parallel(pdf_bytes: bytes) -> list[dict]: |
| """Converts a PDF and processes pages in parallel using the FAST pipeline.""" |
| print("FAST MODE: Converting PDF pages at 150 DPI...") |
| images = convert_from_bytes(pdf_bytes, dpi=150) |
| print(f"FAST MODE: PDF has {len(images)} pages. Starting optimized parallel OCR...") |
|
|
| page_results = [] |
| with ThreadPoolExecutor(max_workers=2) as executor: |
| results = executor.map(_process_single_page_fast, images) |
| for i, text in enumerate(results): |
| page_results.append({ |
| "page_number": i + 1, |
| "text": text |
| }) |
|
|
| print("FAST MODE: Finished all pages.") |
| return page_results |
|
|
