Add PaddleOCR masking and region detection pipeline

- Created PaddleOCR client for remote server communication
- Implemented text masking + region detection pipeline
- Test results: 100% recall on sample PDF (found both signatures)
- Identified issues: split regions, printed text not fully masked
- Documented 5 solution options in PADDLEOCR_STATUS.md
- Next: Implement region merging and two-stage cleaning

test_paddleocr_client.py

@@ -0,0 +1,81 @@
+#!/usr/bin/env python3
+"""Test PaddleOCR client with a real PDF page."""
+
+import fitz  # PyMuPDF
+import numpy as np
+import cv2
+from paddleocr_client import create_ocr_client
+
+# Test PDF
+TEST_PDF = "/Volumes/NV2/PDF-Processing/signature-image-output/201301_1324_AI1_page3.pdf"
+DPI = 300
+
+print("="*80)
+print("Testing PaddleOCR Client with Real PDF")
+print("="*80)
+
+# Step 1: Connect to server
+print("\n1. Connecting to PaddleOCR server...")
+try:
+    client = create_ocr_client()
+    print(f"   ✅ Connected: {client.server_url}")
+except Exception as e:
+    print(f"   ❌ Connection failed: {e}")
+    exit(1)
+
+# Step 2: Render PDF
+print("\n2. Rendering PDF to image...")
+try:
+    doc = fitz.open(TEST_PDF)
+    page = doc[0]
+    mat = fitz.Matrix(DPI/72, DPI/72)
+    pix = page.get_pixmap(matrix=mat)
+    image = np.frombuffer(pix.samples, dtype=np.uint8).reshape(pix.height, pix.width, pix.n)
+
+    if pix.n == 4:  # RGBA
+        image = cv2.cvtColor(image, cv2.COLOR_RGBA2RGB)
+
+    print(f"   ✅ Rendered: {image.shape[1]}x{image.shape[0]} pixels")
+    doc.close()
+except Exception as e:
+    print(f"   ❌ Error: {e}")
+    exit(1)
+
+# Step 3: Run OCR
+print("\n3. Running OCR on image...")
+try:
+    results = client.ocr(image)
+    print(f"   ✅ OCR successful!")
+    print(f"   Found {len(results)} text regions")
+
+    # Show first few results
+    if results:
+        print("\n   Sample detections:")
+        for i, result in enumerate(results[:5]):
+            text = result['text']
+            confidence = result['confidence']
+            print(f"      {i+1}. '{text}' (confidence: {confidence:.2f})")
+
+except Exception as e:
+    print(f"   ❌ OCR failed: {e}")
+    import traceback
+    traceback.print_exc()
+    exit(1)
+
+# Step 4: Get bounding boxes
+print("\n4. Getting text bounding boxes...")
+try:
+    boxes = client.get_text_boxes(image)
+    print(f"   ✅ Got {len(boxes)} bounding boxes")
+
+    if boxes:
+        print("   Sample boxes (x, y, w, h):")
+        for i, box in enumerate(boxes[:3]):
+            print(f"      {i+1}. {box}")
+
+except Exception as e:
+    print(f"   ❌ Error: {e}")
+
+print("\n" + "="*80)
+print("Test completed successfully!")
+print("="*80)