fdwm 0.1.0

Frequency-domain watermarking library and CLI

FDWM - Frequency Domain Watermarking

A Python library for embedding and extracting watermarks in images using frequency domain techniques. Supports both image and text watermarks with a command-line interface.

Features

• Frequency Domain Watermarking: Uses FFT (Fast Fourier Transform) to embed watermarks in high-frequency regions
• Image Watermarks: Embed and extract image-based watermarks
• Text Watermarks: Embed and extract text watermarks with OCR support
• Command Line Interface: Easy-to-use CLI for batch processing
• Multiple Languages: Support for various text languages
• Robust Extraction: High correlation coefficients for reliable watermark detection

Installation

From PyPI (Recommended)

pip install fdwm

From Source

git clone https://github.com/Liam0205/fdwm.git
cd fdwm
pip install -e .

Quick Start

Python API

import cv2
from fdwm import embed, extract, extract_text

# Load host image and watermark
host_img = cv2.imread('host.jpg')
watermark_img = cv2.imread('watermark.png')

# Embed watermark
watermarked_img = embed(host_img, watermark_img, strength=0.1)

# Extract watermark
extracted_watermark = extract(watermarked_img, watermark_img.shape[:2])

# For text watermarks
text = "Hello World"
watermarked_img = embed(host_img, text, strength=0.1, is_text=True)
extracted_text = extract_text(watermarked_img)

Command Line Interface

# Embed image watermark
fdwm embed host.jpg watermark.png -o watermarked.jpg

# Embed text watermark
fdwm embed host.jpg "Hello World" -o watermarked.jpg --text

# Extract image watermark
fdwm extract watermarked.jpg watermark.png -o extracted.png

# Extract text watermark
fdwm extract watermarked.jpg --text

CLI Usage

Embed Command

fdwm embed <host_image> <watermark> [options]

Options:
  -o, --output PATH     Output file path
  --text               Treat watermark as text
  --strength FLOAT     Embedding strength (default: 0.1)
  --batch              Process directory of images

Extract Command

fdwm extract <watermarked_image> <watermark> [options]

Options:
  -o, --output PATH     Output file path
  --text               Extract text watermark
  --batch              Process directory of images

Examples

Batch Processing

# Embed watermark in all images in a directory
fdwm embed images/ watermark.png --batch -o watermarked/

# Extract watermark from all images
fdwm extract watermarked/ watermark.png --batch -o extracted/

g

Text Watermarking

# Embed Chinese text
fdwm embed image.jpg "Hello World" --text -o watermarked.jpg

# Extract text
fdwm extract watermarked.jpg --text

Requirements

• Python 3.8+
• numpy
• opencv-python
• Pillow
• pytesseract

License

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

Contributing

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

Acknowledgments

• Based on frequency domain watermarking techniques
• Uses OpenCV for image processing
• Tesseract OCR for text extraction