---
license: mit
language:
- en
pipeline_tag: image-to-text
tags:
- gregg-shorthand
- handwriting-recognition
- ocr
- historical-documents
- stenography
library_name: pytorch
---

# Gregg Shorthand Recognition Model

This model recognizes Gregg shorthand notation from images and converts it to readable text.

## Model Description

- **Model Type**: Image-to-Text recognition
- **Architecture**: CNN-LSTM with advanced pattern recognition
- **Training Data**: Gregg shorthand samples
- **Language**: English
- **License**: MIT

## Intended Use

This model is designed to:
- Recognize Gregg shorthand from scanned documents
- Convert historical stenographic notes to digital text
- Assist in digitizing shorthand archives
- Support stenography education and research

## How to Use

### Using the Hugging Face Transformers library

```python
from transformers import pipeline
from PIL import Image

# Load the pipeline
pipe = pipeline("image-to-text", model="a0a7/gregg-recognition")

# Load an image
image = Image.open("path/to/shorthand/image.png")

# Generate text
result = pipe(image)
print(result[0]['generated_text'])
```

### Using the original package

```python
from gregg_recognition import GreggRecognition

# Initialize the recognizer
recognizer = GreggRecognition(model_type="image_to_text")

# Recognize text from image
result = recognizer.recognize("path/to/image.png")
print(result)
```

### Command Line Interface

```bash
# Install the package
pip install gregg-recognition

# Use the CLI
gregg-recognize path/to/image.png --verbose
```

## Model Performance

The model uses advanced pattern recognition techniques optimized for Gregg shorthand notation.

## Training Details

- **Framework**: PyTorch
- **Optimizer**: Adam
- **Architecture**: Custom CNN-LSTM with pattern database
- **Input Resolution**: 256x256 pixels
- **Preprocessing**: Grayscale conversion, normalization

## Limitations

- Optimized specifically for Gregg shorthand notation
- Performance may vary with image quality
- Best results with clear, high-contrast images

## Citation

If you use this model in your research, please cite:

```bibtex
@misc{gregg-recognition,
  title={Gregg Shorthand Recognition Model},
  author={Your Name},
  year={2025},
  url={https://huggingface.co/a0a7/gregg-recognition}
}
```

## Contact

For questions or issues, please open an issue on the [GitHub repository](https://github.com/a0a7/GreggRecognition).