mirror of
https://github.com/wiltodelta/remove-ai-watermarks.git
synced 2026-07-21 07:00:56 +02:00
test-user
d7614a7b45
- Add disclaimer section to README (research/education purposes) - Remove incorrect Apache-2.0 license claim from ctrlregen docstrings - Expand Credits with CtrlRegen and NeuralBleach attribution - Add license info (MIT) for GeminiWatermarkTool and NeuralBleach
162 lines
4.8 KiB
Markdown
162 lines
4.8 KiB
Markdown
# Remove-AI-Watermarks
|
|
|
|
Unified tool for removing **visible** and **invisible** AI watermarks from images.
|
|
|
|
## Features
|
|
|
|
- **Visible watermark removal** — Gemini sparkle logo via reverse alpha blending (fast, offline, deterministic)
|
|
- **Invisible watermark removal** — SynthID, StableSignature, TreeRing via diffusion-based regeneration
|
|
- **AI metadata stripping** — EXIF, PNG text chunks, C2PA provenance manifests
|
|
- **Analog Humanizer** — film grain and chromatic aberration injection to bypass AI image classifiers
|
|
- **Smart Face Protection** — automatic extraction and blending of human faces to prevent AI distortion
|
|
- **High-Res Upscaler** — prevents resolution degradation during invisible watermark removal
|
|
- **Batch processing** — process entire directories
|
|
- **Detection** — three-stage NCC watermark detection with confidence scoring
|
|
|
|
## Examples
|
|
|
|
| Before (Watermarked) | After (Cleaned) |
|
|
| --- | --- |
|
|
|  |  |
|
|
|
|
## Installation
|
|
|
|
### Recommended (macOS)
|
|
|
|
Install as an isolated CLI tool — no need to manage virtual environments:
|
|
|
|
```bash
|
|
# Using pipx (brew install pipx)
|
|
pipx install git+https://github.com/wiltodelta/remove-ai-watermarks.git
|
|
|
|
# Or using uv (brew install uv)
|
|
uv tool install git+https://github.com/wiltodelta/remove-ai-watermarks.git
|
|
```
|
|
|
|
### Install from repository (macOS)
|
|
|
|
**Prerequisites:** Python 3.10+ and `pip` (or [`uv`](https://docs.astral.sh/uv/)).
|
|
|
|
```bash
|
|
# 1. Clone the repository
|
|
git clone https://github.com/wiltodelta/remove-ai-watermarks.git
|
|
cd remove-ai-watermarks
|
|
|
|
# 2. Install the package in editable mode
|
|
pip install -e .
|
|
|
|
# Or, if you use uv:
|
|
uv pip install -e .
|
|
```
|
|
|
|
After installation the `remove-ai-watermarks` command is available system-wide.
|
|
|
|
#### Invisible watermark removal (optional)
|
|
|
|
Invisible removal uses diffusion models and requires a **HuggingFace token** and a decent GPU (CUDA) or Apple Silicon (MPS).
|
|
|
|
```bash
|
|
# 1. Create a free token at https://huggingface.co/settings/tokens
|
|
# 2. Copy the example env file and paste your token
|
|
cp .env.example .env
|
|
# Edit .env and set HF_TOKEN=hf_your_token_here
|
|
|
|
# 3. On first run, the model (~2 GB) will be downloaded automatically.
|
|
# On macOS with Apple Silicon, MPS acceleration is used by default.
|
|
# On macOS without GPU, add --device cpu (inference will be slow).
|
|
```
|
|
|
|
#### Developer setup
|
|
|
|
```bash
|
|
# Install with dev dependencies (pytest, ruff, pyright)
|
|
pip install -e ".[dev]"
|
|
# Or with uv:
|
|
uv pip install -e ".[dev]"
|
|
|
|
# Run tests
|
|
pytest
|
|
|
|
# Run linters
|
|
./maintain.sh
|
|
```
|
|
|
|
## Usage
|
|
|
|
### CLI
|
|
|
|
```bash
|
|
# Remove visible Gemini watermark
|
|
remove-ai-watermarks visible image.png -o clean.png
|
|
|
|
# Remove invisible watermarks (SynthID etc.) with optimal quality retention
|
|
remove-ai-watermarks invisible image.png -o clean.png --humanize 4.0
|
|
|
|
# Strip AI metadata
|
|
remove-ai-watermarks metadata image.png --check
|
|
remove-ai-watermarks metadata image.png --remove
|
|
|
|
# Batch processing
|
|
remove-ai-watermarks batch ./images/ --mode visible
|
|
|
|
# Full pipeline: visible + invisible + metadata
|
|
remove-ai-watermarks all image.png -o clean.png
|
|
```
|
|
|
|
### Python API
|
|
|
|
```python
|
|
from remove_ai_watermarks.gemini_engine import GeminiEngine
|
|
import cv2
|
|
|
|
engine = GeminiEngine()
|
|
image = cv2.imread("watermarked.png")
|
|
|
|
# Detect
|
|
result = engine.detect_watermark(image)
|
|
print(f"Detected: {result.detected} (confidence: {result.confidence:.1%})")
|
|
|
|
# Remove
|
|
clean = engine.remove_watermark(image)
|
|
cv2.imwrite("clean.png", clean)
|
|
```
|
|
|
|
### Metadata stripping
|
|
|
|
```python
|
|
from remove_ai_watermarks.metadata import has_ai_metadata, remove_ai_metadata
|
|
from pathlib import Path
|
|
|
|
if has_ai_metadata(Path("image.png")):
|
|
remove_ai_metadata(Path("image.png"), Path("clean.png"))
|
|
```
|
|
|
|
## Requirements
|
|
|
|
- Python ≥ 3.10
|
|
- **Visible removal / metadata**: CPU only, no GPU required
|
|
- **Invisible removal**: GPU recommended (CUDA or MPS), works on CPU (slow)
|
|
|
|
## Credits
|
|
|
|
- [noai-watermark](https://github.com/mertizci/noai-watermark) by mertizci — invisible watermark removal engine
|
|
- [GeminiWatermarkTool](https://github.com/allenk/GeminiWatermarkTool) by Allen Kuo (MIT) — visible watermark removal algorithm
|
|
- [CtrlRegen](https://github.com/yepengliu/CtrlRegen) by Liu et al. (ICLR 2025) — controllable regeneration pipeline
|
|
- [NeuralBleach](https://github.com/...) (MIT) — analog humanizer technique
|
|
|
|
## ⚠️ Disclaimer
|
|
|
|
This tool is provided for **educational and research purposes only**.
|
|
|
|
Removing AI watermarks to misrepresent AI-generated content as human-created
|
|
may violate applicable laws, including the U.S. Digital Millennium Copyright Act
|
|
(DMCA) and the COPIED Act. Users are solely responsible for ensuring their use
|
|
complies with all applicable laws and platform terms of service.
|
|
|
|
The authors do not condone the use of this tool for deception, fraud,
|
|
or any activity that violates applicable laws or regulations.
|
|
|
|
## License
|
|
|
|
MIT
|