Metadata Scrubber & Cryptographic Watermarker
The Problem:
Independent creators want to distribute proprietary promotional digital assets without leaving raw Exif trails or losing identifying ownership marks to asset theft.
The Complexity:
Medium-High. Strips raw tracking markers across image/video headers and embeds robust steganographic binary watermarks deep within the visual layers, making the marker resilient to re-compression or format conversions.
Pricing Strategy:
$149
Architecture Overview
The solution consists of a modular application architecture broken down into explicit core modules and an accessible UI layout layer:
- src/core/scrubber.py: Handles complete EXIF and header metadata stripping operations.
- src/core/watermarker.py: Implements Least Significant Bit (LSB) cryptographic steganographic marking for permanent tracking identification inside image matrices.
- src/ui/app.py: Lightweight desktop environment built using standard Python Tkinter abstractions for cross-platform compatibility.
Environment Preparation & Deployment
Run the architecture setup profile tailored directly to your production host workstation environment:
For macOS:
Execute `./scripts/setup_macos.sh`
For Linux:
Execute `./scripts/setup_linux.sh`
For Windows:
Execute `.\scripts\setup_windows.bat`
Application Startup Execution
Activate the compiled virtual runtime sandbox and launch the native desktop initialization frame:
On POSIX environments (Linux/macOS):
“`bash
source venv/bin/activate
python main.py
“`
On Windows environments:
“`cmd
venv\Scripts\activate.bat
python main.py
“`
Verification Test Pipeline Execution
Confirm local environment stability validation via regression testing structures:
“`bash
python -m unittest discover -s tests
“`
$149.00Read more