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README.md

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+# PDF Pipeline
+
+A comprehensive PDF-to-Markdown extraction pipeline using state-of-the-art layout detection, OCR, and table extraction models.
+
+## Features
+
+- **Layout Detection**: Uses PP-DocLayoutV3 (ONNX) for accurate document layout analysis
+- **OCR Support**: Multiple OCR backends - PaddleOCR, RapidOCR, Pytesseract
+- **Table Extraction**: TableFormerONNX with OTSL (Object Table Structure Language) output
+- **Dual Input Support**: Process both PDFs and standalone images (PNG, JPG, etc.)
+- **Streamlit UI**: Interactive web interface for easy document processing
+
+## Architecture
+
+```
+PDF/Image Input
+       │
+       ▼
+┌─────────────────────────────────────────────────────────────┐
+│                    Layout Detection                          │
+│              PP-DocLayoutV3 (ONNX)                          │
+└─────────────────────────────────────────────────────────────┘
+       │
+       ▼
+┌─────────────────────────────────────────────────────────────┐
+│              Text Extraction Strategy                        │
+├─────────────────────────────────────────────────────────────┤
+│  Native PDF Text │  OCR Fallback (Paddle/Rapid/Tesseract)   │
+│  (pdfplumber)    │                                          │
+└─────────────────────────────────────────────────────────────┘
+       │
+       ▼
+┌─────────────────────────────────────────────────────────────┐
+│               Region Classification                          │
+│  • Text Blocks  • Tables  • Figures  • Headers  • Footers     │
+└─────────────────────────────────────────────────────────────┘
+       │
+       ▼
+┌─────────────────────────────────────────────────────────────┐
+│              Table Extraction (if applicable)                │
+│         TableFormerONNX → OTSL → Markdown                   │
+└─────────────────────────────────────────────────────────────┘
+       │
+       ▼
+┌─────────────────────────────────────────────────────────────┐
+│              Markdown Output                                 │
+│  • Structured text  • Extracted tables  • Figure references   │
+└─────────────────────────────────────────────────────────────┘
+```
+
+## Project Structure
+
+```
+pdf_pipeline_project/
+├── main.py                      # Streamlit web interface with HuggingFace Hub integration
+├── example_usage.py             # Python API examples
+├── html_to_table.py             # HTML table utilities
+├── requirements.txt             # Python dependencies
+├── PP-DocLayout/                # Layout detection models (282MB) - auto-downloaded
+├── tableformerv1/               # Table extraction models (205MB) - auto-downloaded
+├── pp_ocr_small/                # Small OCR models (~35MB) - auto-downloaded
+├── pp_ocr_medium/               # Medium OCR models (~100MB) - auto-downloaded
+├── pdf_pipeline/                # Core Python package
+│   ├── __init__.py             # Public API exports
+│   ├── layout.py               # DocLayoutV3 ONNX wrapper
+│   ├── ocr_backends.py         # OCR implementations (RapidOCR, Pytesseract)
+│   ├── pipeline.py             # Main processing pipeline
+│   ├── table_extraction.py     # TableFormer integration
+│   ├── logging_config.py       # Logging utilities
+│   └── ch_en_dict.txt          # OCR character dictionary
+├── examples/                    # Sample PDFs and outputs
+└── README.md                    # This file
+```
+
+## Installation
+
+### Prerequisites
+
+- Python 3.10+
+- Tesseract OCR (for Pytesseract backend)
+- HuggingFace account token (for model downloading)
+
+### Setup
+
+1. **Clone the repository**:
+```bash
+git clone <repository-url>
+cd pdf_pipeline_project
+```
+
+2. **Install Python dependencies**:
+```bash
+pip install -r requirements.txt
+```
+
+3. **Install Tesseract** (Ubuntu/Debian):
+```bash
+sudo apt-get update
+sudo apt-get install -y tesseract-ocr tesseract-ocr-fra tesseract-ocr-eng
+```
+
+For macOS:
+```bash
+brew install tesseract
+```
+
+### Model Download (Automatic)
+
+Models are automatically downloaded from HuggingFace Hub on first run:
+
+| Model | Repository | Size |
+|-------|------------|------|
+| **PP-DocLayoutV3** | `PaddlePaddle/PP-DocLayoutV3_onnx` | ~282MB |
+| **TableFormer** | `bakhil-aissa/tableformerv1` | ~205MB |
+| **PaddleOCR Medium** | `PaddlePaddle/PP-OCRv6_medium_*_onnx` | ~100MB |
+| **PaddleOCR Small** | `PaddlePaddle/PP-OCRv6_small_*_onnx` | ~35MB |
+
+To pre-download models:
+```python
+from huggingface_hub import snapshot_download
+
+snapshot_download(repo_id="PaddlePaddle/PP-DocLayoutV3_onnx", local_dir="PP-DocLayout")
+snapshot_download(repo_id="bakhil-aissa/tableformerv1", local_dir="tableformerv1")
+```
+
+## Usage
+
+### Streamlit Web Interface
+
+Run the interactive web UI:
+
+```bash
+streamlit run main.py
+```
+
+Then open your browser to `http://localhost:8501`
+
+Features:
+- Upload PDF or image files
+- Configure OCR backend (PaddleOCR, RapidOCR, Pytesseract)
+- Adjust rendering resolution
+- Preview extracted markdown
+- Download results
+
+### Python API
+
+#### Process a PDF:
+
+```python
+from pdf_pipeline import (
+    DocLayoutV3,
+    TableFormerONNX,
+    get_ocr_backend,
+    process_document,
+)
+from huggingface_hub import snapshot_download
+import os
+
+# Model paths (auto-download from HuggingFace)
+PP_DOCLAYOUT_PATH = ("PP-DocLayout/inference.onnx" if os.path.exists("PP-DocLayout/inference.onnx") 
+    else os.path.join(snapshot_download(repo_id="PaddlePaddle/PP-DocLayoutV3_onnx", local_dir="PP-DocLayout"), "inference.onnx")
+)
+
+DET_PATH_MEDIUM = (
+    "pp_ocr_medium/det/inference.onnx" if os.path.exists("pp_ocr_medium/det/inference.onnx") 
+    else os.path.join(snapshot_download(repo_id="PaddlePaddle/PP-OCRv6_medium_det_onnx", local_dir="pp_ocr_medium", subfolder="det"), "inference.onnx")
+)
+
+REC_PATH_MEDIUM = (
+    "pp_ocr_medium/rec/inference.onnx" if os.path.exists("pp_ocr_medium/rec/inference.onnx") 
+    else snapshot_download(repo_id="PaddlePaddle/PP-OCRv6_medium_rec_onnx", local_dir="pp_ocr_medium", subfolder="rec")
+)
+
+REC_KEYS_PATH = "ch_en_dict.txt"
+
+# Initialize components
+layout_detector = DocLayoutV3(PP_DOCLAYOUT_PATH)
+page_ocr_backend = get_ocr_backend("rapidocr", det_model_path=DET_PATH_MEDIUM, rec_model_path=REC_PATH_MEDIUM, rec_keys_path=REC_KEYS_PATH)
+table_runner = TableFormerONNX(artifact_root="tableformerv1", variant="accurate")
+table_ocr_backend = get_ocr_backend("rapidocr", det_model_path=DET_PATH_MEDIUM, rec_model_path=REC_PATH_MEDIUM, rec_keys_path=REC_KEYS_PATH)
+
+# Process document
+markdown_doc = process_document(
+    "document.pdf",
+    layout_detector,
+    page_ocr_backend=page_ocr_backend,
+    table_runner=table_runner,
+    table_ocr_backend=table_ocr_backend,
+)
+
+print(markdown_doc)
+```
+
+#### Process an Image:
+
+```python
+# Same setup as above...
+
+# Process standalone image (always uses OCR)
+markdown_doc = process_document(
+    "scanned_page.png",
+    layout_detector,
+    page_ocr_backend=page_ocr_backend,
+    table_runner=table_runner,
+    table_ocr_backend=table_ocr_backend,
+)
+```
+
+## OCR Backends
+
+Choose the best OCR backend for your needs:
+
+| Backend | Speed | Accuracy | Languages | Notes |
+|---------|-------|----------|-----------|-------|
+| **RapidOCR** | Very Fast | Good | 10+ | ONNX-based, lightweight |
+| **Pytesseract** | Medium | Good | 100+ | Tesseract wrapper, configurable |
+
+### Model Sizes
+
+RapidOCR supports two model sizes:
+
+| Model | Detection | Recognition | Size | Speed | Accuracy |
+|-------|-----------|-------------|------|-------|----------|
+| **Small** | PP-OCRv6_small | PP-OCRv6_small | ~35MB | Fast | Good |
+| **Medium** | PP-OCRv6_medium | PP-OCRv6_medium | ~100MB | Medium | Better |
+
+Switch backends and models:
+```python
+# RapidOCR with small model (faster)
+ocr = get_ocr_backend("rapidocr", 
+    det_model_path=DET_PATH_SMALL,
+    rec_model_path=REC_PATH_SMALL,
+    rec_keys_path=REC_KEYS_PATH)
+
+# RapidOCR with medium model (more accurate)
+ocr = get_ocr_backend("rapidocr",
+    det_model_path=DET_PATH_MEDIUM,
+    rec_model_path=REC_PATH_MEDIUM,
+    rec_keys_path=REC_KEYS_PATH)
+
+# Pytesseract (French + English)
+ocr = get_ocr_backend("pytesseract", lang="fra+eng")
+```
+
+## Troubleshooting
+
+### Issue: `ModuleNotFoundError: No module named 'pdf_pipeline'`
+
+**Solution**: Run from project root, or install as editable package:
+```bash
+pip install -e .
+```
+
+### Issue: `TesseractNotFoundError: tesseract is not installed`
+
+**Solution**: Install Tesseract system binary:
+```bash
+# Ubuntu/Debian
+sudo apt-get install tesseract-ocr
+
+# macOS
+brew install tesseract
+
+# Windows: Download installer from https://github.com/UB-Mannheim/tesseract/wiki
+```
+
+### Issue: `onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument`
+
+**Solution**: Check model files are not corrupted. Re-download if needed:
+```bash
+# Check file sizes match expected
+ls -lh PP-DocLayout/*.onnx
+ls -lh tableformerv1/onnx/accurate/*.onnx
+```
+
+### Issue: Out of Memory (OOM) on large PDFs
+
+**Solution**: Reduce rendering resolution:
+```python
+# Lower DPI for memory-constrained environments
+process_document(
+    "large.pdf",
+    layout_detector,
+    resolution=100,  # Default is 150, try 100 or 72
+)
+```
+
+### Issue: Slow OCR on CPU
+
+**Solution**: Use RapidOCR for faster CPU inference:
+```python
+ocr = get_ocr_backend("rapidocr")  # ~2-3x faster than PaddleOCR on CPU
+```
+
+## Performance Benchmarks
+
+Typical processing times (single page, Intel i7, 16GB RAM):
+
+| Stage | Time | Notes |
+|-------|------|-------|
+| PDF Rendering | 200-500ms | Depends on resolution |
+| Layout Detection | 300-800ms | ONNXRuntime, CPU |
+| Text Extraction | 100-300ms | Native PDF text |
+| OCR (fallback) | 1-3s | Only if no native text |
+| Table Extraction | 2-5s | Per table region |
+
+**Total**: ~1-5 seconds per page (depending on content density)
+
+## Contributing
+
+Contributions are welcome! Please follow these steps:
+
+1. Fork the repository
+2. Create a feature branch (`git checkout -b feature/amazing-feature`)
+3. Commit your changes (`git commit -m 'Add amazing feature'`)
+4. Push to the branch (`git push origin feature/amazing-feature`)
+5. Open a Pull Request
+
+### Development Setup
+
+```bash
+# Install development dependencies
+pip install -r requirements.txt
+pip install pytest black flake8 mypy
+
+# Run tests
+pytest tests/
+
+# Format code
+black pdf_pipeline/ main.py
+
+# Type checking
+mypy pdf_pipeline/
+```
+
+## License
+
+This project is licensed under the MIT License - see the LICENSE file for details.
+
+## Acknowledgments
+
+- **PaddleOCR** - For OCR model implementations
+- **PP-DocLayout** - For document layout detection
+- **TableFormer** - For table structure recognition
+- **Docling** - For OTSL to Markdown conversion
+
+## Contact
+
+For questions or support, please open an issue on GitHub or contact the maintainers.
+
+---
+
+**Made with ❤️ for document processing automation**