# sem-meta
A unified Python package for SEM (Scanning Electron Microscopy) image processing, providing metadata extraction, OCR-based pixel size estimation, and unit conversion utilities.
## Features
- **SEMMetaData**: Extract and format metadata from SEM images
- **SEMOCR**: OCR-based pixel size estimation from scale bars
- **ConvertPS**: Unit conversion and error analysis for pixel size data
- **FullSEMKeys**: Standardized metadata key list for SEM images
## Installation
Install from PyPI:
```bash
pip install sem-meta
```
## Quick Start
```python
from sem_meta import SEMMeta, OCRPS, ConvertScale, FullSEMKeys
# Extract metadata from SEM images
metadata = SEMMeta.extract_metadata("path/to/sem/image.tif")
# Perform OCR on scale bars
pixel_size = OCRPS.extract_pixel_size("path/to/image/with/scalebar.tif")
# Convert units
converted_size = ConvertScale.convert_units(pixel_size, "μm", "nm")
# Access standardized SEM metadata keys
sem_keys = FullSEMKeys
```
## Main Components
### SEMMetaData
Extracts and processes metadata from SEM image files, particularly TIFF files with EXIF data.
### SEMOCR
Uses OCR (Optical Character Recognition) to extract pixel size information from scale bars in SEM images. Includes noise filtering and error correction for common OCR mistakes.
### ConvertPS
Handles unit conversion and normalization for pixel size measurements, supporting various scientific units commonly used in microscopy.
### FullSEMKeys
Provides a standardized set of metadata keys for consistent SEM image annotation and data extraction.
## Dependencies
- numpy: Numerical computations
- PIL (Pillow): Image processing
- pymysql: SQL safety utilities
- termcolor: Terminal output styling
- matplotlib: Visualization
- opencv-python: Advanced image preprocessing
- pytesseract: OCR functionality
## Requirements
- Python 3.6+
- Tesseract OCR engine (for OCR functionality)
### Installing Tesseract
**Ubuntu/Debian:**
```bash
sudo apt install tesseract-ocr
```
**macOS:**
```bash
brew install tesseract
```
**Windows:**
Download and install from: https://github.com/UB-Mannheim/tesseract/wiki
## Usage Examples
### Extracting SEM Metadata
```python
from sem_meta import SEMMeta
# Initialize and extract metadata
sem_processor = SEMMeta
metadata = sem_processor.extract_metadata("sample.tif")
print(metadata)
```
### OCR-based Scale Bar Reading
```python
from sem_meta import OCRPS
# Extract pixel size from scale bar
ocr_processor = OCRPS
pixel_size = ocr_processor.extract_pixel_size("sem_image.tif")
print(f"Pixel size: {pixel_size}")
```
### Unit Conversion
```python
from sem_meta import ConvertScale
# Convert between units
converter = ConvertScale
result = converter.convert_units("0.5 μm", "nm")
print(f"Converted: {result}")
```
## File Structure
```
sem-meta/
├── src/
│ └── sem_meta/
│ ├── __init__.py
│ ├── metadata_Module.py # SEMMetaData class
│ ├── ocr_Module.py # SEMOCR class
│ ├── convert_Module.py # ConvertPS class
│ ├── SEMKEYS.py # FullSEMKeys definitions
│ └── OCR_NOISE_DB.py # OCR noise patterns database
├── README.md
├── LICENSE
└── pyproject.toml
```
## Contributing
1. Fork the repository
2. Create a feature branch (`git checkout -b feature/amazing-feature`)
3. Commit your changes (`git commit -m 'Add some amazing feature'`)
4. Push to the branch (`git push origin feature/amazing-feature`)
5. Open a Pull Request
## License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
## Authors
- Ahmed Khalil - Initial work
## Acknowledgments
- Built for the SEM imaging community
- Supports various SEM manufacturers' metadata formats
- Includes extensive OCR noise pattern recognition
## Support
If you encounter any problems or have questions, please open an issue on the GitHub repository.
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