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MEDARS

MEtaDAta from image files in RuSt - A fast and simple command-line tool for inspecting and removing metadata from image files.


Features

  • Check Metadata: Check if an image contains metadata.
  • View Metadata: Display metadata in a human-readable table or JSON format.
  • Remove Metadata: Clean images by removing all embedded metadata.
  • Interactive TUI: Terminal user interface for easy navigation and image preview.
  • Log Actions: Keep a log of all operations performed.

Core Functionality

CLI mode

  • Check for metadata:

    medars check image.jpg
    
  • Show metadata:

    medars show image.jpg
    
  • Clean metadata:

    medars clean image.jpg
    
  • Launch the TUI:

    medars tui
    

    or

    medars tui <path/to/directory>
    

    TUI Navigation:

    • j/k or / - Navigate files/folders
    • h/l or / - Switch between panels
    • Enter - Open selected folder
    • Esc - Go to parent directory
    • Space - Select/deselect file
    • a - Select/deselect all files
    • d - Delete metadata from selected files
    • c - Copy files with metadata removed
    • q - Quit
  • Batch operations:

    medars clean "*.jpg"
    medars clean path1.jpg path2.png
    
  • Flags:

    • --copy [PATH] → Save as a new file. If PATH is not provided, it will be saved with a _medars suffix.
    • --dry-run → Show what will be removed without modifying the file.

Privacy & Security

MEDARS helps protect your privacy by:

  • Removing potentially sensitive EXIF data (GPS coordinates, camera settings, timestamps).
  • Working locally - no data is sent to external services.
  • Preserving image quality while removing metadata.

Dependencies

This project requires the gexiv2 library and its development headers.

On Ubuntu/Debian:

sudo apt install libgexiv2-2

On Arch:

yay -S libgexiv2

If you see an error about gexiv2.pc or gexiv2 not found, make sure the library is installed.

Installation

From Git Repository

cargo install --git https://github.com/brockar/medars.git

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Acknowledgments

Description
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Readme MIT 142 KiB
Languages
Rust 100%