OCR-to-RAG pipeline for life science screenshots

PaddleOCR with preprocessing, scispaCy NER, figure/table detection,
citation extraction, and chunked Markdown output with frontmatter.
Includes watch mode and notebook reprocessing.
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Metadata-Version: 2.4
Name: ocr-pipeline
Version: 0.1.0
Summary: OCR pipeline for life science screenshots - RAG ready
Requires-Python: >=3.11
Description-Content-Type: text/markdown
Requires-Dist: typer[all]>=0.9.0
Requires-Dist: pydantic>=2.6.0
Requires-Dist: pydantic-settings>=2.2.0
Requires-Dist: pyyaml>=6.0.1
Requires-Dist: structlog>=24.1.0
Requires-Dist: rich>=13.7.0
Requires-Dist: tqdm>=4.66.0
Requires-Dist: opencv-python-headless>=4.9.0
Requires-Dist: pillow>=10.2.0
Requires-Dist: numpy>=1.26.0
Requires-Dist: scikit-image>=0.22.0
Requires-Dist: paddleocr>=2.7.0
Requires-Dist: pytesseract>=0.3.10
Requires-Dist: torch>=2.2.0
Requires-Dist: torchvision>=0.17.0
Requires-Dist: transformers>=4.38.0
Requires-Dist: layoutparser>=0.3.0
Requires-Dist: langchain-text-splitters>=0.0.2
Requires-Dist: spacy>=3.7.0
Requires-Dist: sqlite-utils>=3.37.0
Requires-Dist: watchdog>=3.0.0
Requires-Dist: python-slugify>=8.0.0
Requires-Dist: xxhash>=3.4.0
Requires-Dist: python-magic>=0.4.27
Provides-Extra: dev
Requires-Dist: pytest>=8.0.0; extra == "dev"
Requires-Dist: pytest-cov>=4.1.0; extra == "dev"
Requires-Dist: pytest-mock>=3.12.0; extra == "dev"
Requires-Dist: ruff>=0.2.0; extra == "dev"
Requires-Dist: mypy>=1.8.0; extra == "dev"
Requires-Dist: pre-commit>=3.6.0; extra == "dev"
Provides-Extra: grobid
Requires-Dist: grobid-client>=0.8.0; extra == "grobid"
Provides-Extra: full
Requires-Dist: ocr-pipeline[dev]; extra == "full"
Requires-Dist: ocr-pipeline[grobid]; extra == "full"
# OCR Pipeline for Life Science Screenshots
A production-ready OCR pipeline that extracts text from scientific screenshots and converts them into RAG-ready Markdown files with rich metadata.
## Features
- **Multi-engine OCR**: PaddleOCR (primary) with Tesseract fallback
- **Image preprocessing**: Deskewing, denoising, CLAHE contrast enhancement, line removal
- **Parallel processing**: Multi-process worker pool for throughput
- **Scientific entity recognition**: Genes, proteins, chemicals, species, diseases, cell lines via scispaCy
- **Figure & table detection**: LayoutParser + Table Transformer
- **Citation extraction**: DOI, PMID, arXiv, PMC, ISBN via regex + optional GROBID
- **Semantic chunking**: LangChain recursive splitter optimized for scientific text
- **RAG-ready output**: Markdown with YAML frontmatter (source, hash, timestamp, entities, confidence)
- **Watch mode**: File system monitoring with SQLite persistence for incremental processing
- **Notebook migration**: Reprocess screenshots from existing Jupyter notebooks
- **Life-science focused**: Handles scientific notation, units, gene symbols, chemical formulas
## Quick Start
```bash
# Install with uv (recommended)
uv sync
# Or with pip
pip install -e .
# Install pre-commit hooks
pre-commit install
# Run on your screenshots
ocr-pipeline run
# Watch for new screenshots
ocr-pipeline watch
# Reprocess from notebook
ocr-pipeline reprocess ocr_sc.ipynb
# Check status
ocr-pipeline status
```
## Configuration
Edit `config.yaml`:
```yaml
input:
paths: ["~/Pictures", "/mnt/storage3/aman/screenshots"]
patterns: ["SCR-*.png", "*.jpg", "*.jpeg", "*.tiff"]
recursive: true
ocr:
engine: "paddleocr" # paddleocr | tesseract | auto
languages: ["en", "latin"]
use_gpu: false
preprocess:
deskew: true
denoise: true
clahe: true
adaptive_threshold: true
remove_lines: true
processing:
workers: 4
batch_size: 10
retry_attempts: 2
detectors:
figures:
enabled: true
confidence_threshold: 0.7
tables:
enabled: true
confidence_threshold: 0.7
entities:
enabled: true
model: "en_core_sci_lg" # scispaCy large model
citations:
regex_enabled: true
grobid_enabled: false # Set true if running GROBID server
chunking:
chunk_size: 1000
chunk_overlap: 200
output:
base_directory: "./data/ocr_output"
organize_by: "date_run" # date_run | source_dir | flat
frontmatter:
- source_path
- source_hash
- timestamp
- ocr_engine
- ocr_confidence_mean
- language
- detected_entities
- has_figures
- has_tables
- citations_found
- chunk_index
- total_chunks
watch:
enabled: true
debounce_seconds: 5
db_path: "./data/processed_files.db"
```
## Output Format
Each chunk produces a Markdown file with YAML frontmatter:
```markdown
---
source_path: "/Users/Aman/Pictures/SCR-20250115-gel.png"
source_hash: "a1b2c3d4e5f6..."
timestamp: "2025-01-15T10:30:00Z"
ocr_engine: "paddleocr"
ocr_confidence_mean: 0.91
language: "en"
detected_entities: ["GENE", "PROTEIN", "CHEMICAL"]
has_figures: true
has_tables: false
citations_found: ["DOI:10.1038/nature12345", "PMID:12345678"]
chunk_index: 0
total_chunks: 2
---
# Screenshot: SCR-20250115-gel.png
## Figures
### Figure 1
- **BBox**: [100, 200, 800, 600]
- **Confidence**: 0.92
- **Caption**: "Western blot showing BRCA1 expression..."
## Detected Entities
- BRCA1
- CRISPR
- β-actin
## Citations
- DOI: 10.1038/nature12345
- PMID: 12345678
## Extracted Text
**Western Blot Analysis of BRCA1 Expression**
Lane 1: WT control
Lane 2: BRCA1 KO (CRISPR)
Lane 3: BRCA1 KO + pBRCA1-WT rescue
Lane 4: BRCA1 KO + pBRCA1-C61G mutant
Anti-BRCA1 (1:1000), Anti-β-actin (1:5000)
```
## Directory Structure
```
data/ocr_output/
├── 2025-01-15/
│ ├── run_001/
│ │ ├── SCR-20250115-gel_chunk_000.md
│ │ └── SCR-20250115-gel_chunk_001.md
│ └── run_002/
│ └── ...
└── 2025-01-16/
└── run_001/
└── ...
```
## Docker
```bash
# Build
docker build -t ocr-pipeline .
# Run once
docker run -v ~/Pictures:/data/screenshots -v ./data:/app/data ocr-pipeline run
# Watch mode
docker run -v ~/Pictures:/data/screenshots -v ./data:/app/data ocr-pipeline watch
```
## Life Science Optimizations
| Feature | Implementation |
|---------|----------------|
| Gene/Protein names | scispaCy `en_core_sci_lg` NER |
| Chemical formulas | Regex + unit normalization (µM, ng/mL, kb, etc.) |
| Scientific notation | `1.5×10⁻³` → `1.5×10^-3` |
| Gel/blot lanes | Figure detection + caption extraction |
| Citations | DOI, PMID, arXiv, PMC, ISBN patterns |
| Units | µM, ng/mL, kb/Mb/Gb, °C, ×g, etc. |
## Development
```bash
# Install dev dependencies
uv sync --dev
# Run tests
pytest
# Lint
ruff check .
ruff format .
# Type check
mypy src/
```
## Model Downloads
First run downloads models automatically:
- PaddleOCR detection/recognition models (~200MB)
- scispaCy `en_core_sci_lg` (~800MB)
- Table Transformer (~500MB)
- LayoutParser PubLayNet (~300MB)
Cache location: `~/.cache/ocr_pipeline/`
## License
MIT

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README.md
pyproject.toml
src/ocr_pipeline/__init__.py
src/ocr_pipeline/cli.py
src/ocr_pipeline/config.py
src/ocr_pipeline/pipeline.py
src/ocr_pipeline/watch.py
src/ocr_pipeline.egg-info/PKG-INFO
src/ocr_pipeline.egg-info/SOURCES.txt
src/ocr_pipeline.egg-info/dependency_links.txt
src/ocr_pipeline.egg-info/entry_points.txt
src/ocr_pipeline.egg-info/requires.txt
src/ocr_pipeline.egg-info/top_level.txt
src/ocr_pipeline/citations/__init__.py
src/ocr_pipeline/citations/extractor.py
src/ocr_pipeline/citations/regex_extractor.py
src/ocr_pipeline/detectors/__init__.py
src/ocr_pipeline/detectors/figures.py
src/ocr_pipeline/detectors/tables.py
src/ocr_pipeline/ocr/__init__.py
src/ocr_pipeline/ocr/engine.py
src/ocr_pipeline/ocr/parallel.py
src/ocr_pipeline/output/__init__.py
src/ocr_pipeline/output/markdown.py
src/ocr_pipeline/postprocess/__init__.py
src/ocr_pipeline/postprocess/chunk.py
src/ocr_pipeline/postprocess/clean.py
src/ocr_pipeline/postprocess/entities.py
src/ocr_pipeline/utils/__init__.py
src/ocr_pipeline/utils/db.py
src/ocr_pipeline/utils/logging.py
src/ocr_pipeline/utils/migrate.py
src/ocr_pipeline/watch/__init__.py
src/ocr_pipeline/watch/watcher.py
tests/test_postprocess.py

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[console_scripts]
ocr-pipeline = ocr_pipeline.cli:app

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typer[all]>=0.9.0
pydantic>=2.6.0
pydantic-settings>=2.2.0
pyyaml>=6.0.1
structlog>=24.1.0
rich>=13.7.0
tqdm>=4.66.0
opencv-python-headless>=4.9.0
pillow>=10.2.0
numpy>=1.26.0
scikit-image>=0.22.0
paddleocr>=2.7.0
pytesseract>=0.3.10
torch>=2.2.0
torchvision>=0.17.0
transformers>=4.38.0
layoutparser>=0.3.0
langchain-text-splitters>=0.0.2
spacy>=3.7.0
sqlite-utils>=3.37.0
watchdog>=3.0.0
python-slugify>=8.0.0
xxhash>=3.4.0
python-magic>=0.4.27
[dev]
pytest>=8.0.0
pytest-cov>=4.1.0
pytest-mock>=3.12.0
ruff>=0.2.0
mypy>=1.8.0
pre-commit>=3.6.0
[full]
ocr-pipeline[dev]
ocr-pipeline[grobid]
[grobid]
grobid-client>=0.8.0

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ocr_pipeline