A Python tool to modify images in order to break perceptual hashes (dHash) while preserving visual quality as much as possible.
The script applies controlled image modifications such as:
- High-contrast diagonal lines.
- Smooth brightness gradient.
- Global brightness adjustment.
This can be used for testing the robustness of perceptual hash algorithms, digital forensics research, or educational purposes.
- Batch processing: Modifies all images from a selected folder.
- Prints original and new perceptual hashes (dHash).
- Prints original and new SHA256 hashes.
- Preserves maximum visual similarity when possible.
- Compatible with
.jpg,.jpeg,.pngformats.
- Python 3.x
Install required libraries:
pip install pillow opencv-python-
Place your original images inside the
input/folder. -
Run the script:
python dHashChanger.py- The modified images will be saved in the
output/folder with the same filename.
Example console output for a processed image:
Image: photo.jpg
Original perceptual hash: 30cd32b0000
New perceptual hash: ffff8cd32b3fff
Original SHA256 hash: 95b4303b31...
New SHA256 hash: e6d096b803...
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/
├── dHashChanger.py # Main script
├── input/ # Folder for original images
└── output/ # Folder for modified images
If you want to create a portable .exe file:
Install PyInstaller:
pip install pyinstallerBuild the executable:
pyinstaller --onefile dHashChanger.pyThe generated .exe file will be in the dist/ folder.
This tool is intended for educational and research purposes only.
Do not use it for illegal activities.
MIT License.