If you’ve ever downloaded images generated by Gemini, you’ve probably noticed the watermark.
It’s subtle, but once you start using those images for documentation, thumbnails, slide decks, or internal tools, the watermark quickly becomes friction.
That’s why I built Gemini Watermark Cleaner — a Chrome extension that removes the Gemini watermark automatically when you download images, including Nano Banana Images.
No extra steps.
No UI changes.
No manual uploads.
You download images exactly the same way as before — the watermark simply disappears.
👉 Homepage: https://geminiwatermarkcleaner.com/
👉 Online Tool : Gemini Watermark Remover
How This Project Started
This wasn’t built with a single “AI magic” solution from day one.
Like most real-world tools, it evolved through multiple technical iterations, each with clear trade-offs.
Phase 1: OpenCV (Fast, but Limited)
The first version was based on OpenCV.
The idea was straightforward:
- detect the watermark region
- apply traditional image inpainting
- reconstruct the background using surrounding pixels
This approach worked fine for:
- flat backgrounds
- solid colors
- low-complexity images
But once images became more complex — gradients, textures, or rich colors — the results were inconsistent.
OpenCV is rule-based.
Watermarks are not.
Phase 2: LaMa Local Model (Very Accurate, Very Slow)
Next, I experimented with LaMa (Large Mask Inpainting) running as a local model.
The results were honestly impressive:
- extremely high accuracy
- almost no visible artifacts
- works on nearly all image types
However, the trade-offs were obvious:
- large model size
- high memory usage
- ~30 seconds per image on average
That kind of latency is unacceptable for a browser extension or a smooth online workflow.
Accuracy alone wasn’t enough.
Phase 3: Lightweight Algorithm Inspired by Open Source
The final solution came from rethinking the problem.
Instead of relying on a massive general-purpose model, I built a specialized lightweight algorithm, inspired by techniques from the open-source computer vision and image inpainting community, and optimized specifically for Gemini watermark patterns.
Key improvements:
- model size reduced to under 2MB
- processing time down to milliseconds
- works entirely client-side
- no noticeable quality regression in real-world usage
This version finally struck the right balance between:
speed, size, and visual quality.
Chrome Extension: Invisible by Design
The Chrome extension integrates directly into the image download flow.
From the user’s perspective:
1. Click “Download image”
2. The extension processes the image locally
3. The watermark is removed
4. A clean image is saved
No dashboards.
No popups.
No extra clicks.
Most users forget the extension is even installed — which is exactly the point.
Gemini Watermark Remover (Online Tool)
For users who prefer not to install an extension, I also provide an online version called Gemini Watermark Remover.
👉 https://geminiwatermarkcleaner.com/gemini-watermark-remover.html
The Gemini Watermark Remover uses the same lightweight algorithm as the extension and runs entirely in the browser.
- freemium
- instant usage
- no account required
- no uploads to a server
It’s essentially the same engine, delivered as a web tool.
Privacy First, Always
Both the Chrome extension and Gemini Watermark Remover are built with the same principle:
All processing happens locally.
- images are not uploaded
- no data is stored
- no tracking or analytics on image content
Your images never leave your device.
Demo Video
Here’s a short demo showing the Gemini watermark removal in action:
Final Thoughts
This project wasn’t about chasing the largest model or the latest AI buzzword.
It was about:
- identifying a very specific pain point
- learning from open-source techniques
- iterating through real engineering constraints
- and shipping something that stays out of the way
If you regularly work with Gemini-generated images, I hope Gemini Watermark Cleaner and Gemini Watermark Remover save you time — and a bit of frustration.
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