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---
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license: mit
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language:
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- en
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pipeline_tag: image-to-text
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tags:
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- gregg-shorthand
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- handwriting-recognition
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- ocr
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- historical-documents
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- stenography
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library_name: pytorch
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---
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# Gregg Shorthand Recognition Model
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This model recognizes Gregg shorthand notation from images and converts it to readable text.
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## Model Description
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- **Model Type**: Image-to-Text recognition
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- **Architecture**: CNN-LSTM with advanced pattern recognition
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- **Training Data**: Gregg shorthand samples
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- **Language**: English
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- **License**: MIT
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## Intended Use
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This model is designed to:
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- Recognize Gregg shorthand from scanned documents
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- Convert historical stenographic notes to digital text
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- Assist in digitizing shorthand archives
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- Support stenography education and research
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## How to Use
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### Using the Hugging Face Transformers library
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```python
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from transformers import pipeline
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from PIL import Image
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# Load the pipeline
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pipe = pipeline("image-to-text", model="a0a7/gregg-recognition")
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# Load an image
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image = Image.open("path/to/shorthand/image.png")
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# Generate text
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result = pipe(image)
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print(result[0]['generated_text'])
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```
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### Using the original package
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```python
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from gregg_recognition import GreggRecognition
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# Initialize the recognizer
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recognizer = GreggRecognition(model_type="image_to_text")
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# Recognize text from image
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result = recognizer.recognize("path/to/image.png")
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print(result)
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```
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### Command Line Interface
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```bash
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# Install the package
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pip install gregg-recognition
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# Use the CLI
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gregg-recognize path/to/image.png --verbose
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```
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## Model Performance
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The model uses advanced pattern recognition techniques optimized for Gregg shorthand notation.
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## Training Details
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- **Framework**: PyTorch
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- **Optimizer**: Adam
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- **Architecture**: Custom CNN-LSTM with pattern database
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- **Input Resolution**: 256x256 pixels
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- **Preprocessing**: Grayscale conversion, normalization
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## Limitations
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- Optimized specifically for Gregg shorthand notation
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- Performance may vary with image quality
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- Best results with clear, high-contrast images
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## Citation
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If you use this model in your research, please cite:
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```bibtex
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@misc{gregg-recognition,
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title={Gregg Shorthand Recognition Model},
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author={Your Name},
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year={2025},
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url={https://huggingface.co/a0a7/gregg-recognition}
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}
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```
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## Contact
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For questions or issues, please open an issue on the [GitHub repository](https://github.com/a0a7/GreggRecognition).
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