image-metadata-recorder 1.2.0

A tool to extract, analyze, and report on metadata from TIFF, QPTIFF, and CZI files.

Image Metadata Recorder

A specialized tool for biomedical researchers to extract, analyze, and document metadata from various microscopy image formats. This package is designed to support research workflows by providing detailed insights into image acquisition parameters and experimental conditions.

Features

• Multi-format Support

  • TIFF and QPTIFF file processing
  • CZI (Carl Zeiss Image) file support
  • Extensible architecture for additional formats

• Comprehensive Metadata Extraction

  • Image dimensions and properties
  • Channel information and configurations
  • Acquisition parameters
  • Instrument settings
  • Custom metadata fields

• Analysis Tools

  • Metadata structure analysis
  • Key path extraction
  • Template generation for metadata validation
  • Pattern recognition in metadata structures

• Reporting Capabilities

  • Markdown report generation
  • PDF report creation (requires pandoc)
  • Structured data output in JSON format
  • Customizable report templates

Installation

Prerequisites

• Python 3.8 or higher
• pip (Python package installer)
• pandoc (optional, for PDF report generation)

Basic Installation

pip install image-metadata-recorder

Development Installation

git clone https://github.com/saptarshichakrabarti/image-metadata-recorder.git
cd image-metadata-recorder
pip install -e ".[dev]"

Usage

Command Line Interface

The tool can be used directly from the command line:

# Process all supported files in the current directory
record_image_metadata

# Skip PDF generation
record_image_metadata --skip-pdf

Output Files

For each processed image, the tool generates:

• *_metadata.json: Complete metadata in JSON format
• *_key_paths.txt: List of all metadata paths
• *_structure_template.txt: Template of metadata structure
• *_report.md: Human-readable report
• *_report.pdf: PDF version of the report (if pandoc is available)

Example Workflow

1. Place your image files in a directory
2. Run the tool:

   record_image_metadata
   

3. Review the generated reports and metadata files
4. Use the structure templates for metadata validation

Contributing

Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• aicspylibczi for CZI file support
• tifffile for TIFF processing
• pypandoc for PDF generation