'commit'

Util/PaddleOCRKit.py

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+# coding=utf-8
+import os
+import sys
+import logging
+import cv2
+import numpy as np
+from paddleocr import PaddleOCR
+from Util.OcrParser import OcrParser
+
+# Initialize logger
+logger = logging.getLogger("PaddleOCRKit")
+
+class PaddleOCRKit:
+    _instance = None
+    _ocr = None
+
+    def __new__(cls):
+        if cls._instance is None:
+            cls._instance = super(PaddleOCRKit, cls).__new__(cls)
+            cls._instance._initialize_model()
+        return cls._instance
+
+    def _initialize_model(self):
+        """
+        Initialize the PaddleOCR model once.
+        Using PP-OCRv4 mobile model for speed.
+        """
+        try:
+            logger.info("Initializing PaddleOCR (PP-OCRv4 Mobile)...")
+            # use_angle_cls is deprecated, using use_textline_orientation instead
+            # ocr_version='PP-OCRv4' defaults to mobile model
+            self._ocr = PaddleOCR(
+                use_textline_orientation=True, 
+                lang="ch", 
+                ocr_version='PP-OCRv4'
+            )
+            logger.info("PaddleOCR initialized successfully.")
+        except Exception as e:
+            logger.error(f"Failed to initialize PaddleOCR: {e}")
+            self._ocr = None
+
+    def recognize(self, image_input):
+        """
+        Recognize text from an image and parse it into structured data.
+        
+        :param image_input: Image path (str) or OpenCV image object (numpy.ndarray)
+        :return: Parsed structured data (dict) or None if failed
+        """
+        if self._ocr is None:
+            logger.error("PaddleOCR model is not initialized.")
+            return None
+
+        try:
+            # PaddleOCR handles both path and ndarray
+            # predict() is recommended over ocr() in newer versions, but ocr() is the stable high-level API
+            # We use ocr() as in the test script which worked well.
+            # cls=True was causing issues in test, but use_textline_orientation=True in init handles it?
+            # actually in test script: ocr = PaddleOCR(use_textline_orientation=True, ...)
+            # result = ocr.ocr(image_path) -> this worked, but gave a warning about predict.
+            # Let's stick to ocr() for now as it returns the structure we expect.
+            
+            result = self._ocr.ocr(image_input)
+            
+            ocr_text_lines = []
+            
+            # Handle result structure
+            if not result:
+                logger.warning("OCR returned empty result.")
+            else:
+                res = result[0]
+                if res is None:
+                    logger.warning("OCR result[0] is None.")
+                elif isinstance(res, dict) and 'rec_texts' in res:
+                    # New PaddleOCR / Paddlex format
+                    ocr_text_lines = res['rec_texts']
+                elif isinstance(res, list):
+                    # Legacy PaddleOCR format
+                    for line in res:
+                        # line structure: [[points], (text, confidence)]
+                        if len(line) >= 2 and isinstance(line[1], (tuple, list)):
+                            ocr_text_lines.append(line[1][0])
+            
+            # --- 关键：打印原始识别内容 ---
+            if ocr_text_lines:
+                logger.info(f"🔍 OCR 原始识别文字 ({len(ocr_text_lines)} 行):")
+                for i, line in enumerate(ocr_text_lines):
+                    logger.info(f"  [{i+1}] {line}")
+            else:
+                logger.info("No text detected.")
+                return {}
+
+            # Parse with Regex Parser
+            parsed_data = OcrParser.parse(ocr_text_lines)
+            
+            # --- 关键：打印解析后的结构化数据 ---
+            if parsed_data:
+                logger.info("📦 OCR 解析结果 (JSON):")
+                logger.info(f"  {parsed_data}")
+            
+            return parsed_data
+
+        except Exception as e:
+            logger.error(f"Error during OCR recognition: {e}")
+            return None
+
+# Global instance for easy access
+_kit_instance = None
+
+def get_ocr_kit():
+    global _kit_instance
+    if _kit_instance is None:
+        _kit_instance = PaddleOCRKit()
+    return _kit_instance