Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· AI
Gemini Watermark
Remove visible Gemini AI watermarks from images via reverse alpha blending. Use for cleaning Gemini-generated images, removing the star/sparkle logo watermar...
skill openclawclawhub Free
Remove visible Gemini AI watermarks from images via reverse alpha blending. Use for cleaning Gemini-generated images, removing the star/sparkle logo watermar...
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Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md, references/algorithm.md, scripts/remove_watermark.py
Validation
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- Review SKILL.md after the package is downloaded.
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Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 2.1.0
Provenance
- Publisher
- h1bomb
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Documentation
Gemini Watermark Remover
Remove the visible Gemini AI watermark (star/sparkle logo) from generated images using mathematically accurate reverse alpha blending. Fully offline β pure Python, no external binary downloads, no network access.
When to Use
Remove the Gemini watermark from AI-generated images Batch process a directory of Gemini-generated images Clean images before publishing or sharing Automate watermark removal in pipelines
Install Dependencies (one-time)
pip install Pillow numpy # Recommended: use uv for faster, isolated installs uv pip install Pillow numpy Requires: Python β₯ 3.9. No Rust toolchain, no compiled binaries, no downloads.
Basic Usage
# Single image (auto-detect watermark, save as photo_cleaned.jpg) python3 scripts/remove_watermark.py photo.jpg # Specify output path python3 scripts/remove_watermark.py photo.jpg -o clean_photo.jpg # Batch process directory python3 scripts/remove_watermark.py ./input_dir -o ./output_dir # Force removal without detection python3 scripts/remove_watermark.py photo.jpg -o clean.jpg --force
How It Works
Gemini adds a semi-transparent white star/sparkle logo to generated images using alpha blending: watermarked = alpha * 255 + (1 - alpha) * original This tool reverses the equation to recover the original pixels: original = (watermarked - alpha * 255) / (1 - alpha) The alpha map (watermark transparency pattern) is generated mathematically as a 4-pointed star (central Gaussian core + 4 elongated cardinal rays) at two sizes: 48Γ48 with 32 px margin β images where either dimension β€ 1024 px 96Γ96 with 64 px margin β images where both dimensions > 1024 px For improved accuracy you can supply your own alpha map derived from a background capture of the Gemini watermark on a white background (--alpha-map).
Detection
Before removal, a three-stage algorithm checks whether a watermark is present: Spatial NCC (50% weight) β normalised cross-correlation with the alpha map Gradient NCC (30% weight) β edge signature matching via Sobel operators Variance Analysis (20% weight) β texture dampening detection Images without detected watermarks are automatically skipped.
CLI Parameters
ParameterShortDefaultDescriptioninput(required)Input image file or directory--output-o{name}_cleaned.{ext}Output file or directory--force-ffalseSkip detection, process unconditionally--threshold-t0.35Detection confidence threshold (0.0β1.0)--force-smallfalseForce 48Γ48 watermark size--force-largefalseForce 96Γ96 watermark size--alpha-map(built-in)Custom grayscale alpha map image--verbose-vfalseEnable detailed output--quiet-qfalseSuppress all non-error output
Supported Formats
FormatReadWriteJPEG (.jpg, .jpeg)YesYes (quality 100)PNG (.png)YesYesWebP (.webp)YesYesBMP (.bmp)YesYes
Usage Examples
# Verbose output (shows detection confidence, watermark coordinates) python3 scripts/remove_watermark.py photo.png -o clean.png -v # Lower detection threshold (more sensitive) python3 scripts/remove_watermark.py photo.jpg -t 0.15 # Force large watermark size regardless of image dimensions python3 scripts/remove_watermark.py photo.jpg --force-large -o clean.jpg # Batch process, quiet mode python3 scripts/remove_watermark.py ./gemini_images/ -o ./cleaned/ -q # Supply a custom alpha map for higher accuracy python3 scripts/remove_watermark.py photo.jpg --alpha-map my_alpha.png
Deriving a Custom Alpha Map
For pixel-perfect removal, capture the Gemini watermark on a pure white background and compute: alpha(x, y) = max(R, G, B) / 255 Save the result as a grayscale PNG and pass it via --alpha-map.
Output
Single file β saves to -o path, or {name}_cleaned.{ext} by default Directory β saves all processed images to the output directory Skipped images β images without detected watermarks are not modified (unless --force) Exit code β 0 on success, 1 if any image fails
"No watermark detected" on a watermarked image
Try lowering the threshold: -t 0.1 Or bypass detection entirely: --force Consider supplying a custom alpha map for your watermark variant
Image looks distorted after removal
The image may not have a Gemini watermark. Use detection (avoid --force) Try --force-small or --force-large to match the correct size Supply a custom alpha map for better precision
"Image too small" warning
The image dimensions are smaller than the watermark region. This typically means the image does not have a Gemini watermark.
ModuleNotFoundError: Pillow or numpy
pip install Pillow numpy # or uv pip install Pillow numpy
Limitations
Visible watermark only β this tool removes the visible star/sparkle logo watermark Cannot remove SynthID β Google's invisible watermark (SynthID) is embedded at the pixel level during generation and cannot be reversed Fixed position only β handles watermarks in the standard bottom-right position only Built-in alpha map is approximate β use --alpha-map with a captured reference for exact results
Category context
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
2 Docs1 Scripts
- SKILL.md
- references/algorithm.md
- scripts/remove_watermark.py