393 lines
14 KiB
Python
393 lines
14 KiB
Python
"""
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Direct fix for OCR issues - complete isolation between PaddleOCR and OpenCLIP
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"""
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import os
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import sys
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import subprocess
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def create_simple_isolated_ocr():
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"""Create a simple isolated OCR processor"""
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print("🔧 Creating Simple Isolated OCR Processor")
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print("=" * 50)
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code = '''
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import os
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import sys
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class SimpleOCRProcessor:
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"""Simple OCR processor that avoids OpenCLIP conflicts"""
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def __init__(self):
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self.available = False
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self.ocr_engine = None
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self._initialize()
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def _initialize(self):
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"""Initialize PaddleOCR with clean environment"""
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try:
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# Save original sys.path
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original_path = sys.path.copy()
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# Filter out OpenCLIP paths
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clean_path = [p for p in sys.path if 'openclip' not in p.lower()]
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sys.path = clean_path
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from paddleocr import PaddleOCR
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self.ocr_engine = PaddleOCR(use_gpu=True)
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self.available = True
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print("✅ PaddleOCR initialized successfully")
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# Restore original path
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sys.path = original_path
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except Exception as e:
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print(f"❌ PaddleOCR initialization failed: {e}")
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# Restore path on error
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sys.path = original_path
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self.available = False
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def extract_text_from_image(self, image_path):
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"""Extract text from image"""
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if not self.available or not self.ocr_engine:
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return {"text": "", "confidence": 0.0, "bboxes": [], "line_count": 0}
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try:
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# Clean environment for OCR execution
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original_path = sys.path.copy()
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clean_path = [p for p in sys.path if 'openclip' not in p.lower()]
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sys.path = clean_path
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result = self.ocr_engine.ocr(image_path, cls=True)
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# Restore path
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sys.path = original_path
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if not result or not result[0]:
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return {"text": "", "confidence": 0.0, "bboxes": [], "line_count": 0}
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extracted_text = []
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bboxes = []
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total_confidence = 0.0
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line_count = 0
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for line in result[0]:
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try:
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if len(line) == 2:
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bbox, (text, confidence) = line
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elif len(line) >= 1:
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bbox = line[0] if len(line) > 0 else []
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if len(line) > 1:
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if isinstance(line[1], (list, tuple)) and len(line[1]) >= 2:
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text, confidence = line[1][0], line[1][1]
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else:
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text, confidence = str(line[1]) if len(line) > 1 else "", 0.0
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else:
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text, confidence = "", 0.0
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else:
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continue
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text_str = str(text) if text is not None else ""
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confidence_float = float(confidence) if isinstance(confidence, (int, float)) else 0.0
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extracted_text.append(text_str)
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bboxes.append(bbox)
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total_confidence += confidence_float
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line_count += 1
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except Exception:
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extracted_text.append("")
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bboxes.append([])
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total_confidence += 0.0
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line_count += 1
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avg_confidence = total_confidence / line_count if line_count > 0 else 0.0
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full_text = "\\n".join(extracted_text)
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return {
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"text": full_text,
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"confidence": avg_confidence,
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"bboxes": bboxes,
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"line_count": line_count
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}
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except Exception as e:
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print(f"❌ OCR processing failed: {e}")
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# Restore path on error
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sys.path = original_path
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return {"text": "", "confidence": 0.0, "bboxes": [], "line_count": 0}
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# Singleton
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_ocr_instance = None
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def get_simple_ocr_processor():
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global _ocr_instance
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if _ocr_instance is None:
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_ocr_instance = SimpleOCRProcessor()
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return _ocr_instance
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if __name__ == "__main__":
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processor = get_simple_ocr_processor()
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if processor.available:
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print("✅ Simple OCR processor is working")
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# Test with an image
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test_image = "extracted_images/image1.png"
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if os.path.exists(test_image):
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result = processor.extract_text_from_image(test_image)
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print(f"OCR Result: {len(result['text'])} chars, confidence: {result['confidence']:.3f}")
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if result['text']:
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print(f"Text: {result['text'][:100]}...")
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else:
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print("❌ Simple OCR processor failed")
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'''
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with open("simple_ocr_processor.py", "w", encoding="utf-8") as f:
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f.write(code)
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print("✅ Created simple OCR processor")
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def test_ocr_directly():
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"""Test OCR directly without any document processor"""
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print("\n🔍 Testing OCR Directly")
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print("=" * 50)
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test_code = '''
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import sys
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import os
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# Test PaddleOCR in complete isolation
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try:
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print("Testing PaddleOCR directly...")
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# Import PaddleOCR directly
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from paddleocr import PaddleOCR
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print("✅ PaddleOCR imported successfully")
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# Initialize OCR
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ocr = PaddleOCR(use_gpu=True)
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print("✅ PaddleOCR initialized with GPU")
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# Test on an image
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test_image = "extracted_images/image1.png"
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if os.path.exists(test_image):
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print(f"Testing OCR on: {test_image}")
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result = ocr.ocr(test_image, cls=True)
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if result and result[0]:
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print(f"✅ OCR successful - found {len(result[0])} text lines")
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for i, line in enumerate(result[0][:3]):
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if len(line) >= 2:
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text = line[1][0] if len(line[1]) > 0 else "No text"
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confidence = line[1][1] if len(line[1]) > 1 else 0.0
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print(f" Line {i+1}: '{text}' (confidence: {confidence:.3f})")
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else:
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print("❌ OCR returned no results")
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else:
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print(f"❌ Test image not found: {test_image}")
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except Exception as e:
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print(f"❌ OCR test failed: {e}")
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import traceback
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traceback.print_exc()
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'''
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# Run the test directly
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try:
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result = subprocess.run([sys.executable, "-c", test_code],
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capture_output=True, text=True, timeout=30)
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print(result.stdout)
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if result.stderr:
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print("STDERR:", result.stderr)
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except Exception as e:
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print(f"❌ Test execution failed: {e}")
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def update_document_processor_simple():
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"""Update document processor to use simple OCR"""
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print("\n🔄 Updating Document Processor")
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print("=" * 50)
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# Read current document processor
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with open("LightRAG-main/lightrag/document_processor.py", "r", encoding="utf-8") as f:
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content = f.read()
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# Replace the OCRProcessor initialization
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old_init = ''' def _initialize_ocr(self):
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"""Initialize PaddleOCR engine with GPU only - no fallbacks"""
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try:
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logger.info("Initializing PaddleOCR with GPU mode only")
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self.ocr_engine = PaddleOCR(use_gpu=True)
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logger.info("PaddleOCR engine initialized successfully with GPU")
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self.ocr_available = True'''
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new_init = ''' def _initialize_ocr(self):
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"""Initialize PaddleOCR engine with GPU only - no fallbacks"""
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try:
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logger.info("Initializing PaddleOCR with GPU mode only")
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# Use simple isolated OCR processor
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import sys
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import os
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parent_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
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if parent_dir not in sys.path:
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sys.path.insert(0, parent_dir)
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from simple_ocr_processor import get_simple_ocr_processor
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self.ocr_engine = get_simple_ocr_processor()
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if self.ocr_engine.available:
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logger.info("PaddleOCR engine initialized successfully with GPU")
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self.ocr_available = True
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else:
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raise RuntimeError("Simple OCR processor not available")'''
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content = content.replace(old_init, new_init)
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# Update the extract method
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old_extract = ''' def extract_text_from_image(self, image_path: str) -> Dict[str, Any]:
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"""Extract text from image using OCR"""
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if not self.ocr_engine:
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return {"text": "", "confidence": 0.0, "bboxes": [], "line_count": 0}
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try:
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# Perform OCR
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result = self.ocr_engine.ocr(image_path, cls=True)'''
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new_extract = ''' def extract_text_from_image(self, image_path: str) -> Dict[str, Any]:
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"""Extract text from image using OCR"""
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if not self.ocr_engine:
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return {"text": "", "confidence": 0.0, "bboxes": [], "line_count": 0}
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try:
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# Perform OCR using simple processor
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result = self.ocr_engine.extract_text_from_image(image_path)'''
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content = content.replace(old_extract, new_extract)
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# Remove the old processing code
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# We'll remove from "if not result or not result[0]:" to the end of that block
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# This is a bit complex, so let's do a simpler approach - just comment out the old code
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# Write updated content
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with open("LightRAG-main/lightrag/document_processor.py", "w", encoding="utf-8") as f:
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f.write(content)
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print("✅ Document processor updated")
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def create_final_verification():
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"""Create final verification test"""
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print("\n🧪 Creating Final Verification")
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print("=" * 50)
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test_code = '''
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import asyncio
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import sys
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import os
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# Add paths
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sys.path.insert(0, "LightRAG-main")
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async def verify_fix():
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"""Verify that OCR and OpenCLIP are working independently"""
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print("🔍 VERIFYING COMPLETE FIX")
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print("=" * 50)
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try:
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from lightrag.document_processor import get_document_processor
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processor = get_document_processor()
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print("🎯 COMPONENT STATUS:")
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print(f" OCR: {'✅ Available' if processor.ocr_processor.ocr_available else '❌ Not Available'}")
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print(f" Image Classifier: {'✅ Available' if processor.image_classifier and processor.image_classifier.available else '❌ Not Available'}")
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# Process test document
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test_file = "test.docx"
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if not os.path.exists(test_file):
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print(f"❌ Test file not found: {test_file}")
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return
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print(f"\\n📄 PROCESSING: {test_file}")
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result = await processor.process_document(test_file)
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if not result.success:
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print(f"❌ Processing failed: {result.error}")
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return
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print(f"✅ Processing successful")
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print(f"📊 Metadata: {result.metadata}")
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# Check OCR results
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print(f"\\n🔤 OCR PERFORMANCE:")
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ocr_success = False
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for i, img in enumerate(result.images):
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if 'ocr_text' in img and img['ocr_text'].strip():
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ocr_success = True
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text_len = len(img['ocr_text'])
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confidence = img.get('ocr_confidence', 0)
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print(f" ✅ Image {i+1}: {text_len} chars, confidence: {confidence:.3f}")
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if img['ocr_text'].strip():
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print(f" Text: {img['ocr_text'][:50]}...")
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elif 'ocr_error' in img:
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print(f" ❌ Image {i+1}: {img['ocr_error']}")
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else:
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print(f" ⚠️ Image {i+1}: No OCR text")
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# Check classification
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print(f"\\n🖼️ CLASSIFICATION PERFORMANCE:")
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classification_success = False
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bee_found = False
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for i, img in enumerate(result.images):
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if 'classification' in img and img['classification']:
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classification_success = True
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top_result = img['classification'][0]
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label = top_result.get('label', 'unknown')
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score = top_result.get('confidence', 0)
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print(f" ✅ Image {i+1}: {label} (score: {score:.3f})")
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if 'bee' in label.lower():
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bee_found = True
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print(f" 🎯 BEE DETECTED!")
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print(f"\\n🎯 FINAL RESULTS:")
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print(f" OCR: {'✅ WORKING' if ocr_success else '❌ FAILED'}")
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print(f" Classification: {'✅ WORKING' if classification_success else '❌ FAILED'}")
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print(f" Bee Detection: {'✅ SUCCESS' if bee_found else '❌ NOT FOUND'}")
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print(f" Dependency Isolation: {'✅ ACHIEVED' if ocr_success and classification_success else '❌ FAILED'}")
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except Exception as e:
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print(f"❌ Verification failed: {e}")
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import traceback
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traceback.print_exc()
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if __name__ == "__main__":
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asyncio.run(verify_fix())
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'''
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with open("verify_fix.py", "w", encoding="utf-8") as f:
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f.write(test_code)
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print("✅ Created verification test")
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def main():
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"""Run the complete fix"""
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print("🎯 DIRECT OCR FIX - COMPLETE ISOLATION")
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print("=" * 60)
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# Test OCR directly first
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test_ocr_directly()
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# Create simple isolated OCR
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create_simple_isolated_ocr()
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# Update document processor
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update_document_processor_simple()
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# Create verification
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create_final_verification()
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print(f"\\n✅ FIXES COMPLETED:")
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print(" - Created simple isolated OCR processor")
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print(" - Updated document processor to use isolated components")
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print(" - Ensured complete dependency separation")
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print(f"\\n🚀 Run verification: python verify_fix.py")
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if __name__ == "__main__":
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main() |