""" Tesseract OCR Engine Fallback OCR engine using Tesseract. Provides broad language support and is widely available. """ import time from typing import List, Optional, Dict, Any import numpy as np from loguru import logger from .base import OCREngine, OCRConfig, OCRResult from ..schemas.core import BoundingBox, OCRRegion # Try to import pytesseract try: import pytesseract from PIL import Image HAS_TESSERACT = True except ImportError: HAS_TESSERACT = False logger.warning( "pytesseract not installed. Install with: pip install pytesseract " "Also install Tesseract: apt-get install tesseract-ocr" ) class TesseractOCREngine(OCREngine): """ OCR engine using Tesseract. Features: - Broad language support (100+ languages) - Mature and well-tested - No GPU required - Page segmentation modes for different layouts """ # Tesseract language codes (subset of common ones) LANGUAGE_MAP = { "en": "eng", "ch": "chi_sim", "chinese_cht": "chi_tra", "fr": "fra", "german": "deu", "es": "spa", "it": "ita", "pt": "por", "ru": "rus", "japan": "jpn", "korean": "kor", "ar": "ara", "hi": "hin", "latin": "lat", } # Page segmentation modes PSM_AUTO = 3 # Fully automatic page segmentation PSM_SINGLE_BLOCK = 6 # Assume single uniform block of text PSM_SINGLE_LINE = 7 # Treat image as single line PSM_SPARSE = 11 # Sparse text with no particular order def __init__(self, config: Optional[OCRConfig] = None): """Initialize Tesseract OCR engine.""" super().__init__(config) self._tesseract_cmd: Optional[str] = None def initialize(self): """Initialize Tesseract engine.""" if not HAS_TESSERACT: raise RuntimeError( "pytesseract not installed. Install with: pip install pytesseract. " "Also install Tesseract: apt-get install tesseract-ocr" ) if self._initialized: return logger.info("Initializing Tesseract OCR engine...") # Test Tesseract installation try: version = pytesseract.get_tesseract_version() logger.info(f"Tesseract version: {version}") self._initialized = True except Exception as e: logger.error(f"Tesseract not properly installed: {e}") raise RuntimeError( f"Tesseract not properly installed: {e}. " "Install with: apt-get install tesseract-ocr" ) def recognize( self, image: np.ndarray, page_number: int = 0, ) -> OCRResult: """ Perform OCR on an image using Tesseract. Args: image: Image as numpy array (RGB, HWC format) page_number: Page number for multi-page documents Returns: OCRResult with recognized text and regions """ if not self._initialized: self.initialize() start_time = time.time() try: # Convert numpy array to PIL Image pil_image = Image.fromarray(image) # Build language string lang = self._get_tesseract_lang() # Configure Tesseract custom_config = self._build_config() # Get detailed data with bounding boxes data = pytesseract.image_to_data( pil_image, lang=lang, config=custom_config, output_type=pytesseract.Output.DICT, ) # Process results regions = [] all_texts = [] total_confidence = 0.0 valid_count = 0 height, width = image.shape[:2] # Group words into lines current_line_id = -1 word_id = 0 for i in range(len(data['text'])): text = data['text'][i].strip() conf = int(data['conf'][i]) # Skip empty or low confidence if not text or conf < 0: continue confidence = conf / 100.0 if confidence < self.config.min_confidence: continue # Track line changes block_num = data['block_num'][i] line_num = data['line_num'][i] line_id = block_num * 1000 + line_num if line_id != current_line_id: current_line_id = line_id word_id = 0 else: word_id += 1 # Get bounding box x = data['left'][i] y = data['top'][i] w = data['width'][i] h = data['height'][i] bbox = BoundingBox( x_min=float(x), y_min=float(y), x_max=float(x + w), y_max=float(y + h), normalized=False, page_width=width, page_height=height, ) region = OCRRegion( text=text, confidence=confidence, bbox=bbox, page=page_number, line_id=line_id, word_id=word_id, engine="tesseract", ) regions.append(region) all_texts.append(text) total_confidence += confidence valid_count += 1 # Also get full text for better formatting full_text = pytesseract.image_to_string( pil_image, lang=lang, config=custom_config, ) processing_time = (time.time() - start_time) * 1000 return OCRResult( regions=regions, full_text=full_text.strip(), confidence_avg=total_confidence / valid_count if valid_count > 0 else 0.0, processing_time_ms=processing_time, engine="tesseract", success=True, ) except Exception as e: logger.error(f"Tesseract recognition failed: {e}") return OCRResult( regions=[], full_text="", confidence_avg=0.0, processing_time_ms=(time.time() - start_time) * 1000, engine="tesseract", success=False, error=str(e), ) def _get_tesseract_lang(self) -> str: """Get Tesseract language string from config.""" langs = [] for lang in self.config.languages: tess_lang = self.LANGUAGE_MAP.get(lang, "eng") if tess_lang not in langs: langs.append(tess_lang) return "+".join(langs) if langs else "eng" def _build_config(self) -> str: """Build Tesseract config string.""" config_parts = [ f"--psm {self.PSM_AUTO}", # Page segmentation mode "--oem 3", # Use both legacy and LSTM engines ] # Add more options as needed if self.config.return_word_boxes: config_parts.append("-c preserve_interword_spaces=1") return " ".join(config_parts) def get_supported_languages(self) -> List[str]: """Return list of supported language codes.""" return list(self.LANGUAGE_MAP.keys()) def get_installed_languages(self) -> List[str]: """Get list of languages installed in Tesseract.""" if not self._initialized: self.initialize() try: langs = pytesseract.get_languages() return langs except Exception as e: logger.warning(f"Could not get installed languages: {e}") return ["eng"] def recognize_with_hocr( self, image: np.ndarray, page_number: int = 0, ) -> tuple: """ Perform OCR and return hOCR format for detailed layout. Args: image: Image as numpy array page_number: Page number Returns: Tuple of (OCRResult, hOCR string) """ if not self._initialized: self.initialize() pil_image = Image.fromarray(image) lang = self._get_tesseract_lang() config = self._build_config() # Get standard result ocr_result = self.recognize(image, page_number) # Get hOCR for layout analysis try: hocr = pytesseract.image_to_pdf_or_hocr( pil_image, lang=lang, config=config, extension='hocr', ) return ocr_result, hocr.decode('utf-8') except Exception as e: logger.warning(f"Failed to generate hOCR: {e}") return ocr_result, None