# PaddleOCRVL Integration Guide

## Overview

`test_accuracy_batch_full.py` now supports two OCR models for seal text recognition:

1. **PP-OCRv5_server_rec** (default) - Traditional OCR model
2. **PaddleOCRVL** - Vision-Language model with superior accuracy

## Usage

### Option 1: Command Line Arguments

```bash
# Use default PP-OCRv5 model
python test_accuracy_batch_full.py

# Use PaddleOCRVL model (recommended for better accuracy)
python test_accuracy_batch_full.py --ocr-model paddleocr_vl

# Process specific number of PDFs
python test_accuracy_batch_full.py --batch-size 5 --ocr-model paddleocr_vl
```

### Option 2: Environment Variable

```bash
# Set environment variable
export OCR_MODEL=paddleocr_vl  # Linux/Mac
set OCR_MODEL=paddleocr_vl     # Windows

# Run script (will use environment variable)
python test_accuracy_batch_full.py
```

## Performance Comparison

Based on WTS2025-21283.pdf test:

| Model | Recognized Text | Accuracy | Score |
|-------|----------------|----------|-------|
| PP-OCRv5_server_rec | 械检测技术有限公司 | 84.2% | 0.8291 |
| **PaddleOCRVL** | **威凯检测技术有限公司** | **100%** ✅ | N/A |

## Requirements

For PaddleOCRVL, ensure you have:

```bash
pip install paddleocr[doc-parser]
pip install paddlepaddle==3.2.0  # Use 3.2.0, not 3.3.0
```

## API Usage

### In your own code:

```python
from paddleocr import PaddleOCRVL
import json

# Initialize PaddleOCRVL with seal recognition
pipeline = PaddleOCRVL(
    use_seal_recognition=True,
    use_ocr_for_image_block=True,
    use_layout_detection=True
)

# Run prediction on unwarp seal image
output = pipeline.predict("seal_unwarp_0.png")

# Extract seal text from result
result = output[0]
result.save_to_json(save_path="output")

# Read JSON to get seal text
with open("output/seal_unwarp_0_res.json", 'r', encoding='utf-8') as f:
    data = json.load(f)
    for block in data['parsing_res_list']:
        if block['block_label'] == 'seal':
            seal_text = block['block_content']
            print(f"Seal text: {seal_text}")
```

## Implementation Details

### Modified Functions

1. **`run_ocr_recognition_vl()`** - New function for PaddleOCRVL recognition
   - Saves temp JSON files
   - Extracts `block_content` from `seal` blocks
   - Returns standardized result format

2. **`extract_seals_and_institutions()`** - Enhanced with OCR model selection
   - Added `ocr_model` parameter ("ppocr_v5" or "paddleocr_vl")
   - Added `vl_pipeline` parameter for PaddleOCRVL instance
   - Automatic fallback to PP-OCRv5 if PaddleOCRVL unavailable

3. **`process_single_pdf()`** - Updated to pass OCR model parameters
4. **`main()`** - Added command line argument parsing

### Key Configuration

```python
# In test_accuracy_batch_full.py

# OCR Model Selection (via environment variable or command line)
OCR_MODEL = os.environ.get("OCR_MODEL", "ppocr_v5")

# Check PaddleOCRVL availability
try:
    from paddleocr import PaddleOCRVL
    PADDLEOCRVL_AVAILABLE = True
except ImportError:
    PADDLEOCRVL_AVAILABLE = False
```

## Troubleshooting

### Issue: "PaddleOCRVL not available"

**Solution:**
```bash
pip install paddleocr[doc-parser]
```

### Issue: "use_seal_recognition or use_ocr_for_image_block not enabled"

**Solution:** Make sure to initialize with correct parameters:
```python
pipeline = PaddleOCRVL(
    use_seal_recognition=True,    # Required!
    use_ocr_for_image_block=True  # Required!
)
```

### Issue: PaddlePaddle 3.3.0 compatibility error

**Solution:** Downgrade to 3.2.0:
```bash
pip install paddlepaddle==3.2.0 -i https://www.paddlepaddle.org.cn/packages/stable/cpu/
```

## File Structure

```
test_accuracy_batch_full.py
├── run_ocr_recognition()           # PP-OCRv5 recognition (existing)
├── run_ocr_recognition_vl()        # PaddleOCRVL recognition (new)
├── extract_seals_and_institutions() # Enhanced with model selection
└── main()                          # Added CLI argument parsing
```

## Recommendations

1. **For production use**: Use PaddleOCRVL for better accuracy
2. **For testing/debugging**: Use PP-OCRv5 for faster iteration
3. **For batch processing**: PaddleOCRVL is slower but more accurate

## Next Steps

- [ ] Run full batch test with PaddleOCRVL on all PDFs
- [ ] Compare accuracy metrics between models
- [ ] Benchmark processing time for both models
- [ ] Consider adding hybrid approach (try PP-OCRv5 first, fallback to PaddleOCRVL on low confidence)