Watermark Remover
Automatically detects watermarks in image corners and removes them using LaMa AI model.
Installation
This skill requires the watermark-remover Python package. Install it first:
# Install from PyPI (when published)
pip install watermark-remover
# Or install from source
git clone https://github.com/yourusername/watermark-remover.git
cd watermark-remover
pip install -e .
Dependencies: Python 3.9+, opencv-python, numpy, Pillow, iopaint
Script Directory
Scripts in scripts/ subdirectory. Replace ${SKILL_DIR} with this SKILL.md's directory path.
| Script | Purpose |
|---|---|
scripts/main.py |
Watermark removal CLI wrapper |
Usage
python ${SKILL_DIR}/scripts/main.py <input> [options]
Options
| Option | Description | Default |
|---|---|---|
<input> |
Image file or directory | Required |
--output |
Output path | <input>/no_watermark |
--corner-ratio |
Corner area ratio (0-1) | 0.15 |
--threshold |
Detection sensitivity (lower = more sensitive) | 30 |
--padding |
Mask dilation pixels | 10 |
--preview |
Generate mask preview only | false |
--no-lama |
Use OpenCV instead of LaMa | false |
Examples
# Single image
python ${SKILL_DIR}/scripts/main.py image.jpg
# Directory with custom output
python ${SKILL_DIR}/scripts/main.py ./photos/ --output ./cleaned/
# Preview detection (shows red marks on watermarks)
python ${SKILL_DIR}/scripts/main.py ./photos/ --preview
# Adjust detection sensitivity
python ${SKILL_DIR}/scripts/main.py image.jpg --corner-ratio 0.2 --threshold 20
# Use OpenCV inpaint (faster but lower quality)
python ${SKILL_DIR}/scripts/main.py image.jpg --no-lama
How It Works
- Scans image corners (default 15% area)
- Detects watermarks using edge detection + high-frequency analysis
- Generates precise mask
- Removes watermark using LaMa AI model (auto-downloads on first run)
- Falls back to OpenCV inpaint if LaMa fails
Supported Formats
JPG, JPEG, PNG, BMP, TIFF, WEBP