Seedance 2.0 Watermark Remover

Remove the Seedance 2.0 watermark ("AI生成" / AI-Generated) from videos automatically — no GPU required, no paid tools.

Works on all videos generated by Seedance 2.0, Seedance Pro, and Seedance Lite video generation models. Also removes watermarks from any corner-positioned logo or text overlay.

Free • Open Source • No GPU Needed • Works on CPU

Don't want to run code locally? Use the free cloud version at https://muapi.ai/playground/seedance-v2.0-watermark-remover — upload your video and get a clean version instantly.

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🎬 Generate Seedance Videos — Muapi Playgrounds

Related Projects

• Seedance-2.5-API — Python wrapper for the Seedance 2.5 API — text-to-video, image-to-video, character consistency

• Seedance-2.0-API — Python wrapper to generate Seedance 2 videos — then remove watermarks with this tool

• seedance2-comfyui — Generate Seedance 2 videos inside ComfyUI

• seedance2.5-comfyui — Native Seedance 2.5 ComfyUI custom nodes and example workflows

• n8n-nodes-seedance2 — Automate Seedance 2 generation in n8n workflows

• awesome-seedance-2.5-api-prompts — Curated Seedance 2.5 API guide, prompts, camera controls, and video generation examples

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• seedance-2.5-mcp — MCP server for generating Seedance 2.5 Preview videos through MuAPI.
• seedance-2-mcp — MCP server for generating Seedance 2 videos through MuAPI.

What Is the Seedance 2.0 Watermark?

Seedance 2.0 (by ByteDance) adds a small "AI生成" (AI-Generated) badge to the corner of every generated video. This tool detects and removes that watermark automatically, restoring a clean video without artifacts.

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How It Works

1. Sample & average ~60 frames — the static Seedance watermark becomes clearly visible in the mean frame while moving content blurs away
2. Auto-detect corner using Canny edge density × temporal stability score — the watermark is static and structured; moving content (people, water, foliage) scores low and is ignored
3. Build a precise mask via Canny edge detection on the watermark region — traces only the text strokes
4. Inpaint each frame with OpenCV TELEA (default, CPU-only) or optionally LaMa AI inpainting (--lama)
5. Reassemble all frames with the original audio using ffmpeg

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Installation

# Core dependencies (required)
pip install opencv-python-headless numpy

# ffmpeg (required for video reassembly)
# macOS
brew install ffmpeg
# Ubuntu / Debian
sudo apt install ffmpeg

# Optional: LaMa AI inpainting (--lama flag)
pip install torch iopaint

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Usage

# Remove Seedance 2.0 watermark — auto-detects corner
python watermark_remover.py input.mp4

# Save to custom output path
python watermark_remover.py input.mp4 -o clean.mp4

# Manual region if auto-detection fails (x, y, width, height in pixels)
python watermark_remover.py input.mp4 -r 10,5,120,60

# Use LaMa AI inpainting for higher quality output (requires torch + iopaint)
python watermark_remover.py input.mp4 --lama

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Features

• Removes Seedance 2.0 watermark ("AI生成") automatically
• Works on portrait and landscape video orientations
• Detects watermark in any of the four corners
• Handles videos where people or content move near the watermark corner
• Supports both opaque and semi-transparent watermarks
• No GPU required — runs entirely on CPU with OpenCV TELEA inpainting
• Preserves original audio in output
• Optional LaMa AI inpainting for higher quality results

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How Auto-Detection Works

Each corner region (8% height × 12% width) is scored:

score = edge_density × (1 / (1 + temporal_std))

Using tight corner regions prevents a moving person near the corner from masking the watermark signal.

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Options

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Requirements

• Python 3.8+
• opencv-python or opencv-python-headless
• numpy
• ffmpeg (system install)
• torch + iopaint (only for --lama)

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Related

• Free Cloud Version — remove Seedance watermarks online, no setup required
• muapi.ai — API platform for Seedance 2.0, Seedance Pro, and other generative media models
• Seedance 2.0 — ByteDance video generation model
• iopaint — LaMa inpainting library

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License

MIT