#!/usr/bin/env python3
"""Test PaddleOCR on a sample PDF page."""

import fitz  # PyMuPDF
from paddleocr import PaddleOCR
import numpy as np
from PIL import Image
import cv2
from pathlib import Path

# Configuration
TEST_PDF = "/Volumes/NV2/PDF-Processing/signature-image-output/201301_1324_AI1_page3.pdf"
DPI = 300

print("="*80)
print("Testing PaddleOCR on macOS Apple Silicon")
print("="*80)

# Step 1: Render PDF to image
print("\n1. 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 2: Initialize PaddleOCR
print("\n2. Initializing PaddleOCR...")
print("   (First run will download models, may take a few minutes...)")
try:
    # Use the correct syntax from official docs
    ocr = PaddleOCR(
        use_doc_orientation_classify=False,
        use_doc_unwarping=False,
        use_textline_orientation=False,
        lang='ch'  # Chinese language
    )
    print("   ✅ PaddleOCR initialized successfully")
except Exception as e:
    print(f"   ❌ Error: {e}")
    import traceback
    traceback.print_exc()
    print("\n   Note: PaddleOCR requires PaddlePaddle backend.")
    print("   If this is a module import error, PaddlePaddle may not support this platform.")
    exit(1)

# Step 3: Run OCR
print("\n3. Running OCR to detect printed text...")
try:
    result = ocr.ocr(image, cls=False)

    if result and result[0]:
        print(f"   ✅ Detected {len(result[0])} text regions")

        # Show first few detections
        print("\n   Sample detections:")
        for i, item in enumerate(result[0][:5]):
            box = item[0]  # Bounding box coordinates
            text = item[1][0]  # Detected text
            confidence = item[1][1]  # Confidence score
            print(f"      {i+1}. Text: '{text}' (confidence: {confidence:.2f})")
            print(f"         Box: {box}")
    else:
        print("   ⚠️  No text detected")

except Exception as e:
    print(f"   ❌ Error during OCR: {e}")
    import traceback
    traceback.print_exc()
    exit(1)

# Step 4: Visualize detection
print("\n4. Creating visualization...")
try:
    vis_image = image.copy()

    if result and result[0]:
        for item in result[0]:
            box = np.array(item[0], dtype=np.int32)
            cv2.polylines(vis_image, [box], True, (0, 255, 0), 2)

    # Save visualization
    output_path = "/Volumes/NV2/PDF-Processing/signature-image-output/paddleocr_test_detection.png"
    cv2.imwrite(output_path, cv2.cvtColor(vis_image, cv2.COLOR_RGB2BGR))
    print(f"   ✅ Saved visualization: {output_path}")

except Exception as e:
    print(f"   ❌ Error during visualization: {e}")

print("\n" + "="*80)
print("PaddleOCR test completed!")
print("="*80)