feat: Agregar soporte OCR con Tesseract para PDFs escaneados
- Integrar Tesseract OCR para leer PDFs escaneados automáticamente - Detectar automáticamente si el PDF tiene texto o requiere OCR - Agregar servicio ocr_service.py con funciones de OCR - Actualizar Dockerfile con tesseract-ocr, tesseract-ocr-spa y poppler-utils - Agregar variables de configuración OCR (OCR_ENABLED, OCR_LANGUAGE, OCR_DPI, OCR_TIMEOUT) - Crear endpoint de debug para ver texto extraído (/api/v1/debug/extract-text) - Agregar scripts de instalación y prueba (install_ocr.ps1, test_ocr.py, debug_pdf.ps1) - Documentación completa (OCR_SETUP.md, DOCKER_OCR.md, COMO_PROBAR.md) - Actualizar docker-compose.yml con variables de entorno OCR - Modificar pdf_text.py para usar OCR cuando sea necesario - Actualizar requirements.txt con pytesseract, Pillow, pdf2image
This commit is contained in:
Ernesto Herrera
197
app/services/ocr_service.py
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197
app/services/ocr_service.py
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"""OCR service using Tesseract for scanned PDFs."""
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import pytesseract
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from pdf2image import convert_from_bytes
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from PIL import Image
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import logging
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from typing import Tuple, List, Optional
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from io import BytesIO
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logger = logging.getLogger(__name__)
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class OCRError(Exception):
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"""Custom exception for OCR processing errors."""
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pass
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def is_pdf_scanned(text: str, min_char_threshold: int = 50) -> bool:
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"""
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Determine if a PDF is scanned (no selectable text) or has text.
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Args:
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text: Extracted text from PDF
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min_char_threshold: Minimum characters to consider as "has text"
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Returns:
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True if PDF appears to be scanned (no text), False otherwise
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"""
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# Remove whitespace and count actual characters
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cleaned_text = text.replace(" ", "").replace("\n", "").replace("\t", "")
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if len(cleaned_text) < min_char_threshold:
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logger.info(f"PDF appears to be scanned (only {len(cleaned_text)} characters found)")
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return True
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logger.info(f"PDF has selectable text ({len(cleaned_text)} characters)")
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return False
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def extract_text_with_ocr(
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pdf_bytes: bytes,
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lang: str = "spa",
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dpi: int = 300,
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timeout: int = 300
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) -> Tuple[str, int]:
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"""
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Extract text from scanned PDF using Tesseract OCR.
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Args:
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pdf_bytes: PDF file content as bytes
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lang: Language for OCR (default: "spa" for Spanish, use "eng" for English)
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dpi: DPI for image conversion (higher = better quality but slower)
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timeout: Maximum time in seconds for OCR processing
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Returns:
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Tuple of (extracted_text, page_count)
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Raises:
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OCRError: If OCR processing fails
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"""
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try:
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logger.info(f"Starting OCR extraction with language={lang}, dpi={dpi}")
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# Convert PDF to images
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images = convert_from_bytes(
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pdf_bytes,
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dpi=dpi,
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fmt='png',
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thread_count=2,
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timeout=timeout
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)
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page_count = len(images)
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logger.info(f"Converted PDF to {page_count} images")
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# Extract text from each page
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text_parts = []
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for i, image in enumerate(images, 1):
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try:
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# Perform OCR on the image
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page_text = pytesseract.image_to_string(
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image,
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lang=lang,
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timeout=timeout // page_count # Distribute timeout across pages
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)
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if page_text.strip():
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text_parts.append(f"--- Página {i} ---\n{page_text}")
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logger.debug(f"Page {i}: Extracted {len(page_text)} characters")
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else:
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logger.warning(f"Page {i}: No text extracted")
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text_parts.append(f"--- Página {i} ---\n[Sin texto detectado]\n")
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except Exception as e:
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logger.error(f"OCR failed on page {i}: {str(e)}")
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text_parts.append(f"--- Página {i} ---\n[Error en OCR: {str(e)}]\n")
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full_text = "\n\n".join(text_parts)
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logger.info(f"OCR extraction completed: {len(full_text)} characters from {page_count} pages")
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return full_text, page_count
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except Exception as e:
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logger.error(f"OCR extraction failed: {str(e)}")
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raise OCRError(f"OCR extraction failed: {str(e)}")
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def optimize_image_for_ocr(image: Image.Image) -> Image.Image:
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"""
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Optimize image for better OCR results.
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Args:
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image: PIL Image object
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Returns:
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Optimized PIL Image
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"""
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# Convert to grayscale
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image = image.convert('L')
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# Optional: Apply threshold to make text clearer
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# This can be adjusted based on your PDFs
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# from PIL import ImageEnhance
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# enhancer = ImageEnhance.Contrast(image)
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# image = enhancer.enhance(2)
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return image
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def extract_text_with_ocr_optimized(
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pdf_bytes: bytes,
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lang: str = "spa",
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dpi: int = 300,
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timeout: int = 300,
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optimize: bool = True
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) -> Tuple[str, int]:
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"""
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Extract text from scanned PDF with image optimization.
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Args:
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pdf_bytes: PDF file content as bytes
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lang: Language for OCR
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dpi: DPI for image conversion
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timeout: Maximum time in seconds
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optimize: Whether to optimize images before OCR
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Returns:
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Tuple of (extracted_text, page_count)
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Raises:
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OCRError: If OCR processing fails
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"""
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try:
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logger.info(f"Starting optimized OCR extraction")
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# Convert PDF to images
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images = convert_from_bytes(
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pdf_bytes,
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dpi=dpi,
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fmt='png',
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thread_count=2,
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timeout=timeout
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)
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page_count = len(images)
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text_parts = []
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for i, image in enumerate(images, 1):
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try:
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# Optimize image if requested
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if optimize:
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image = optimize_image_for_ocr(image)
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# Perform OCR
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page_text = pytesseract.image_to_string(
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image,
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lang=lang,
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config='--psm 1', # Automatic page segmentation with OSD
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timeout=timeout // page_count
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)
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if page_text.strip():
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text_parts.append(f"--- Página {i} ---\n{page_text}")
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else:
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text_parts.append(f"--- Página {i} ---\n[Sin texto detectado]\n")
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except Exception as e:
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logger.error(f"OCR failed on page {i}: {str(e)}")
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text_parts.append(f"--- Página {i} ---\n[Error en OCR]\n")
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full_text = "\n\n".join(text_parts)
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logger.info(f"Optimized OCR completed: {len(full_text)} characters")
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return full_text, page_count
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except Exception as e:
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logger.error(f"Optimized OCR failed: {str(e)}")
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raise OCRError(f"Optimized OCR failed: {str(e)}")
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