Skill: fusae/fusae-watermark-remover (version 0.1.0)

--- name: watermark-remover version: 0.1.0 description: Automatically detects and removes watermarks from images using AI-powered inpainting. Use when user asks to "remove watermark", "clean image", or "去水印". --- # 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: ```bash # 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 ```bash 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 ```bash # 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 1. Scans image corners (default 15% area) 2. Detects watermarks using edge detection + high-frequency analysis 3. Generates precise mask 4. Removes watermark using LaMa AI model (auto-downloads on first run) 5. Falls back to OpenCV inpaint if LaMa fails ## Supported Formats JPG, JPEG, PNG, BMP, TIFF, WEBP

path: README.md
content: # Watermark Remover Skill

Claude Code skill for automatically detecting and removing watermarks from images using AI.

## Installation

### 1. Install the skill

```bash
# Clone or symlink this skill to your Claude skills directory
ln -s /path/to/watermark-remover/skills/watermark-remover ~/.claude/skills/watermark-remover
```

### 2. Install dependencies

This skill requires the `watermark-remover` Python package:

```bash
# Option A: Install from PyPI (when published)
pip install watermark-remover

# Option B: Install from source
git clone https://github.com/yourusername/watermark-remover.git
cd watermark-remover
pip install -e .
```

**Requirements:**
- Python 3.9+
- opencv-python
- numpy
- Pillow
- iopaint (for LaMa AI model)

### 3. Verify installation

```bash
watermark-remover --help
```

## Usage

In Claude Code, simply ask:
- "Remove watermark from image.jpg"
- "Clean watermarks from ./photos/ directory"
- "去掉这张图片的水印"

## Manual Usage

```bash
# Single image
python ~/.claude/skills/watermark-remover/scripts/main.py image.jpg

# Directory
python ~/.claude/skills/watermark-remover/scripts/main.py ./photos/

# Preview detection
python ~/.claude/skills/watermark-remover/scripts/main.py ./photos/ --preview

# Adjust sensitivity
python ~/.claude/skills/watermark-remover/scripts/main.py image.jpg --corner-ratio 0.2 --threshold 20
```

## How It Works

1. Scans image corners (default 15% area)
2. Detects watermarks using edge detection + high-frequency analysis
3. Generates precise mask
4. Removes watermark using LaMa AI model (auto-downloads on first run)
5. Falls back to OpenCV inpaint if LaMa fails

## Troubleshooting

**Error: watermark-remover not found**
- Make sure you've installed the package: `pip install -e /path/to/watermark-remover`
- Or install from PyPI: `pip install watermark-remover`

**LaMa model download fails**
- Use `--no-lama` flag to use OpenCV inpaint instead
- Check your internet connection

## License

MIT


path: requirements.txt
content: opencv-python>=4.8
numpy>=1.24
Pillow>=10.0
iopaint>=1.5


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)