WatermarkRemover-AI

AI-Powered Watermark Removal Tool using Florence-2 and LaMA Models

🇬🇧 English | 🇫🇷 Français | 🇨🇳 中文 | 🇯🇵 日本語 | 🇧🇷 Português | 🧠 Brainrot

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Overview

WatermarkRemover-AI is a cutting-edge application that leverages AI models for precise watermark detection and seamless removal. Perfect for removing watermarks from AI-generated videos like Sora, Sora 2, Runway, and others.

It uses Florence-2 for watermark identification and LaMA for inpainting to fill in the removed regions naturally. The software features a modern web-based GUI accessible from your browser — runs on Windows, Google Colab, and Vercel.

Screenshot

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✨ Features

• Smart Detection — AI-powered watermark detection using Florence-2
• Seamless Removal — LaMA inpainting for natural-looking results
• Video Support — Process videos with two-pass detection and audio preservation
• AI Video Ready — Remove watermarks from Sora, Sora 2, Runway, and other AI-generated videos
• Batch Processing — Handle entire folders at once
• Preview Mode — Preview detected watermarks before processing
• Fade In/Out Handling — Extend masks for watermarks that fade in/out
• GPU Acceleration — CUDA support for faster processing
• Multi-Language UI — English, French, Chinese, Japanese, Portuguese, and Brainrot
• 8 Themes — Brainrot, Slay Queen, Sigma Grindset, WitchTok, Korpo Baddie, Coquette, Windows XP, Anime Kawaii
• Multi-Platform — Windows localhost, Google Colab (free GPU), and Vercel

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🚀 Quick Start

Windows

Requires Python 3.10+ installed (check "Add Python to PATH" during installation).

git clone https://github.com/imsovikde/WatermarkRemover-AI.git
cd WatermarkRemover-AI

Setup (one-time):

Double-click setup.bat

Run:

Double-click run.bat

Opens http://localhost:5000 in your browser automatically.

Google Colab (Free GPU) ⚡

The easiest way to run — no setup needed, free T4 GPU included.

1. Click the "Open in Colab" badge above
2. Set runtime to T4 GPU (Runtime → Change runtime type)
3. Run all 4 cells in order
4. Click the ngrok URL that appears to open the web interface

Linux / macOS

git clone https://github.com/imsovikde/WatermarkRemover-AI.git
cd WatermarkRemover-AI
chmod +x setup.sh run.sh
./setup.sh    # one-time setup
./run.sh      # start server

Vercel (UI Preview)

npm i -g vercel
vercel

Note: Vercel serves the UI preview only. AI processing requires a local server or Google Colab due to model size (~2GB).

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📖 Usage

Web GUI

1. Run the app (run.bat on Windows, ./run.sh on Linux/macOS, or use Colab)
2. Open http://localhost:5000 in your browser
3. Select your preferred language and theme from the dropdown menus
4. Drag & drop images/videos or click to upload
5. Configure settings (detection threshold, prompt, etc.)
6. Hit Start Processing
7. Download the processed files

CLI Mode

# Basic usage
python remwm.py input.png output_folder/

# With options
python remwm.py ./images ./output --overwrite --max-bbox-percent=15 --force-format=PNG

# Process video with two-pass detection
python remwm.py video.mp4 ./output --detection-skip=3 --fade-in=0.5 --fade-out=0.5

# Preview mode (detect without processing)
python remwm.py input.png --preview

CLI Options

Option	Description
--overwrite	Overwrite existing files
--transparent	Make watermark regions transparent (images only)
--max-bbox-percent	Max detection size as % of image (default: 10)
--force-format	Force output format (PNG, WEBP, JPG, MP4, AVI)
--detection-prompt	Custom detection prompt (default: "watermark")
--detection-skip	Detect every N frames for videos (1-10, default: 1)
--fade-in	Extend mask backwards by N seconds
--fade-out	Extend mask forwards by N seconds
--preview	Preview detected watermarks without processing

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🎬 Video Processing

• Supported formats: MP4, AVI, MOV, MKV, FLV, WMV, WEBM
• Audio preservation: Requires FFmpeg installed
• Two-pass mode: Faster processing with --detection-skip > 1
• Fade handling: Use --fade-in / --fade-out for watermarks that appear/disappear gradually

FFmpeg Installation

Platform	Command
Windows	Download from ffmpeg.org, add to PATH
Linux	sudo apt install ffmpeg
macOS	brew install ffmpeg

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🛠 Tech Stack

Component	Technology
Watermark Detection	Florence-2 (Microsoft)
Inpainting	LaMA (Large Mask Inpainting)
Web Server	Flask
Frontend	Alpine.js + Tailwind CSS
Deep Learning	PyTorch (CUDA)
Deployment	Windows / Google Colab / Vercel

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🤝 Contributing

Contributions are welcome! Feel free to:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

Please read our Code of Conduct before contributing.

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📄 License

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

Copyright © 2025 Souvik Dey

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👤 Author

Souvik Dey

• GitHub: @imsovikde

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Made with ❤️ by Souvik Dey