remove-ai-watermarks

# Remove AI Watermarks

Remove AI provenance marks from images and video you generated yourself:

- known visible labels such as the Google Gemini sparkle watermark and vendor text marks;
- invisible pixel watermarks through direct local-format disruption or diffusion regeneration;
- C2PA, EXIF, XMP, IPTC, and related AI metadata.

| Before | After |
| --- | --- |
| ![Image with a visible Gemini watermark](demo_banana_before.png) | ![Image after visible watermark removal](demo_banana_after.png) |

```bash
uv tool install "remove-ai-watermarks[visible]"   # CLI for visible marks and metadata
npx skills add wiltodelta/remove-ai-watermarks    # agent skill for Claude Code, Codex, Cursor, and other agents
```

Video support covers provenance identification, complete visible-plus-metadata
cleaning, directory batches, visible Sora, Veo, Seedance, Doubao, Dola,
Hailuo AI, and Kling AI mark removal, and oracle-certified VAE regeneration for video SynthID
removal.

> [raiw.cc](https://raiw.cc) runs this library as a hosted service, with the GPU
> included and nothing to install. Visible mark and metadata removal at Standard
> output up to 12 MP are free there; original resolution above 12 MP and invisible
> watermark removal are paid.

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> This is a research project on AI provenance signals, for lawful use on content
> you own. It is provided as is, without warranty or liability, and each user is
> responsible for how they use it. It does not target stock agency previews or
> other watermarks that protect third party paid content. Some jurisdictions,
> including China, restrict removing AI labels or supplying tools that do. See
> [scope, safety, and legal notes](docs/legal-and-safety.md).

## Choose what you want to do

| Goal | Command | GPU |
| --- | --- | --- |
| Find provenance signals and watermarks | `identify` | No |
| Classify a photograph from pixels (opt-in, not provenance) | `classify` | No |
| Remove known visible AI marks | `visible` | No |
| Erase a region you select | `erase` | No |
| Strip AI metadata | `metadata` | No |
| Identify supported video provenance | `video identify` | No |
| Remove visible marks and AI metadata from video | `video all` | No |
| Strip AI metadata from video | `video metadata` | No |
| Remove a registered visible AI mark from video | `video visible` | No |
| Process a directory of videos | `video batch` | Depends on mode |
| Apply the calibrated video-pixel SynthID-removal profile | `video invisible` | Recommended |
| Regenerate an image to disrupt invisible watermarks | `invisible` | Required (CUDA) |
| Run visible, invisible, and metadata removal | `all` | Recommended |
| Process a directory | `batch` | Depends on mode |

Microsoft Paint and Photos InvisMark declarations are routed automatically to
pixel regeneration. The `all` command removes both the hidden pixel watermark and
its linked C2PA manifest; metadata stripping alone removes only the manifest. A
specialized Python API can inspect and disrupt the validated local
`Watermarker.dll` payload without diffusion.

## Installation modes

| Need | Install |
| --- | --- |
| Metadata inspection and stripping | `remove-ai-watermarks` |
| Photograph AI-versus-camera classification | `remove-ai-watermarks[classify]` |
| OpenAI/Google/unknown source-export classification | `remove-ai-watermarks[source-classify]` |
| Visible detection and removal | `remove-ai-watermarks[visible]` |
| Visible video processing | `remove-ai-watermarks[video]` |
| Video SynthID removal | `remove-ai-watermarks[video,diffusion]` |
| Torch-free DWT-DCT detection | `remove-ai-watermarks[detect]` |
| Direct local Paint InvisMark disruption | `remove-ai-watermarks[pixels]` |
| Invisible image removal (needs CUDA) | `remove-ai-watermarks[qwen-zimage]` |
| Every production feature available on the active Python | `remove-ai-watermarks[all]` |

Lower-level and specialized extras include `pixels`, `heif`, `trustmark`,
`migan`, `lama`, `diffusion`, `classify-onnx`, and `source-classify`. The
[installation guide](docs/installation.md#feature-extras) documents their exact
dependency composition, Python compatibility, and model requirements.

## Quick start

Install the metadata-focused default CLI:

```bash
uv tool install remove-ai-watermarks
```

Inspect an image:

```bash
remove-ai-watermarks identify image.png
```

To classify a photograph from pixels (AI versus camera, optional provider),
install the extra and call `classify`. `identify` never starts it:

```bash
uv tool install --force "remove-ai-watermarks[classify]"
remove-ai-watermarks classify image.png
```

Guide: [photo pixel classification](docs/photo-classify.md).

For a lightweight, abstaining OpenAI/Google/unknown source-export signal after
metadata removal, use the separate Python API. It is not a SynthID detector:

```python
import remove_ai_watermarks as raiw

result = raiw.classify_source("image.png")
print(result.label, result.reason)
```

Install `remove-ai-watermarks[source-classify]`. Guide:
[source-pipeline classification](docs/source-classify.md).

Signed provenance is the supported route for SynthID and `identify` reads it.
There is no local SynthID pixel detector in the package. Research on a
periodic lattice expert is in `scripts/synthid_runtime/` and
[synthid-detector-research.md](docs/synthid-detector-research.md).

For visible watermark removal, install the pixel dependencies:

```bash
uv tool install --force "remove-ai-watermarks[visible]"
```

Then remove a known visible mark and AI metadata:

```bash
remove-ai-watermarks visible image.png -o clean.png
```

Strip metadata without running visible inpainting or diffusion:

```bash
remove-ai-watermarks metadata image.png --remove -o clean.png
```

Without `-o` this command overwrites the source in place.

Inspect or remove AI metadata from an MP4, MOV, M4V, WebM, MKV, AVI, or FLV
file:

```bash
remove-ai-watermarks video metadata input.mp4 --check
remove-ai-watermarks video metadata input.mp4 --remove -o clean.mp4
```

The `video metadata` command does not transcode video or audio streams. Unlike
the image command above, when `-o` is omitted it writes `<source>_clean` and
preserves the original. MP4 and MOV
inspection includes the native TC260 `AIGC` tag in
`moov.udta.meta.keys/ilst`, including a `moov` placed after the media payload,
plus the QuickTime-form `meta` variants Doubao's iOS export writes (a bare
`meta` box as a direct `moov` child, and a keyless `hdlr=mdir` metadata list).
Keyed `workflow` and `prompt` entries in the same metadata-list structure are
also detected and removed, including ComfyUI exports.
MKV and WebM inspection reads the normative
`Segment.Tags.Tag.SimpleTag` placement. AVI uses `LIST/INFO/AIGC`, while FLV
uses `script.onMetaData.AIGC`. The non-ISOBMFF formats are remuxed with stream
copy for removal.

Use the product-oriented video path to identify or clean a file:

```bash
uv tool install --force "remove-ai-watermarks[video]"
remove-ai-watermarks video identify input.mp4
remove-ai-watermarks video all input.mp4 -o clean.mp4
```

`video all` removes a stable registered visible mark when present and always
strips verified AI metadata. If neither signal is found, it still writes a
same-container passthrough, so application callers get one predictable output
contract. Proprietary invisible-video removal is excluded by default.
`--invisible` opts into the lossy, oracle-certified video SynthID profile.

Process a directory with the same contract:

```bash
remove-ai-watermarks video batch ./videos --mode all
```

Remove a supported visible video mark:

```bash
remove-ai-watermarks video visible input.mp4 -o clean.mp4
remove-ai-watermarks video visible veo.mp4 --mark veo -o veo_clean.mp4
remove-ai-watermarks video visible seedance.mp4 --mark seedance -o seedance_clean.mp4
remove-ai-watermarks video visible dola.mp4 --mark dola -o dola_clean.mp4
remove-ai-watermarks video visible hailuo.mp4 --mark hailuo -o hailuo_clean.mp4
remove-ai-watermarks video visible kling.mp4 --mark kling -o kling_clean.mp4
```

This path scans the complete sequence before changing pixels. It accepts only a
mark that repeats at a stable position across adjacent frames, then reuses the
same OpenCV, MI-GAN, or LaMa fill backends as image removal. Audio is copied
without re-encoding and is allowed to reach its natural end; the video stream
is transcoded because its pixels change. By default, a guarded optical-flow
pass motion-aligns the preceding accepted fill and blends it only when the
nearby source context agrees; use `--no-temporal-consistency` to disable it.
The encoder preserves supported
8-bit source chroma sampling, color tags, and MP4/MOV track timescale instead
of relying on ffmpeg's implicit raw-BGR defaults. Variable frame intervals are
preserved through a timestamped in-memory NUT bridge instead of being flattened
to the average frame rate. Non-zero sourc