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Victor KuznetsovandClaude Opus 5
13095fb45c
Every code-referencing claim in the docs, the README and the rules files was checked against src/, and each finding was re-derived independently before it was applied. 35 held, 5 were false positives. Two of them were code, not text. `InvisibleOptions` promises in its docstring to mirror `InvisibleEngine`, and two defaults had silently stopped: `max_resolution=None` reached `_target_size`'s `max_resolution > 0` and raised `TypeError` on every library call that left the options alone, and `cpu_offload=True` made a library run slower than the identical CLI run. Both are fixed, and `TestInvisibleOptionsMirrorTheEngine` compares the two signatures field by field rather than pinning the two values that happen to be known. A companion assertion in `TestTargetSize` reads the engine's own declared default, so a drift on the engine side -- which the mirror check alone would accept, because both sides would still agree -- fails too. The user-facing docs: README called `invisible` GPU-optional where it raises without CUDA, and gave the image `metadata` command `video metadata`'s output rule, promising the source survives a command that overwrites it. Yuanbao was missing from the supported-mark list. `veo` was listed among the video policies that require a run anchor, though its row sets no `anchor_iou`. `known-limitations` called ControlNet the default profile and contradicted itself ninety lines below. An unescaped pipe truncated the `hailuo` table row. The `dev` extra, the CI shape, ffmpeg's role, the sdist boundary and the strength-curve range were corrected, and `remove_all`/`remove_batch`, the pill gate, `erase --keep-metadata` and `all`'s CUDA failure mode were documented. Research notes that described removed modules, extras and flags in the present tense now say so once in the page banner instead of sentence by sentence, which covers the whole page rather than the lines that happened to be noticed, and one fixture is referred to by role rather than by name. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
445 lines
18 KiB
Markdown
445 lines
18 KiB
Markdown
# Remove AI Watermarks
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Remove AI provenance marks from images and video you generated yourself:
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- known visible labels such as the Gemini sparkle and vendor text marks;
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- invisible pixel watermarks through diffusion regeneration;
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- C2PA, EXIF, XMP, IPTC, and related AI metadata.
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Video support covers provenance identification, complete visible-plus-metadata
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cleaning, directory batches, visible Sora, Veo, Seedance, Dola, Hailuo, and
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Kling mark removal, and oracle-certified VAE regeneration for video SynthID
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removal.
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> Try it online at [raiw.cc](https://raiw.cc) if you do not want to install Python
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> or run diffusion models locally.
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[](https://pypi.org/project/remove-ai-watermarks/)
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[](https://pypi.org/project/remove-ai-watermarks/)
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[](https://pepy.tech/project/remove-ai-watermarks)
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[](LICENSE)
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[](https://github.com/wiltodelta/remove-ai-watermarks/actions/workflows/test.yml)
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[](https://github.com/sponsors/wiltodelta)
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> This project is for lawful use on content you own. It does not target stock
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> agency previews or other watermarks that protect third party paid content.
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> See [scope, safety, and legal notes](docs/legal-and-safety.md).
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## Choose what you want to do
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| Goal | Command | GPU |
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| Find provenance signals and watermarks | `identify` | No |
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| Remove known visible AI marks | `visible` | No |
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| Erase a region you select | `erase` | No |
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| Strip AI metadata | `metadata` | No |
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| Identify supported video provenance | `video identify` | No |
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| Remove visible marks and AI metadata from video | `video all` | No |
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| Strip AI metadata from video | `video metadata` | No |
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| Remove a registered visible AI mark from video | `video visible` | No |
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| Process a directory of videos | `video batch` | Depends on mode |
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| Remove video SynthID with the certified VAE profile | `video invisible` | Recommended |
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| Regenerate an image to disrupt invisible watermarks | `invisible` | Required (CUDA) |
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| Run visible, invisible, and metadata removal | `all` | Recommended |
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| Process a directory | `batch` | Depends on mode |
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## Installation modes
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| Need | Install |
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| --- | --- |
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| Metadata inspection and stripping | `remove-ai-watermarks` |
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| Visible detection and removal | `remove-ai-watermarks[visible]` |
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| Visible video processing | `remove-ai-watermarks[video]` |
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| Video SynthID removal | `remove-ai-watermarks[video,diffusion]` |
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| Torch-free DWT-DCT detection | `remove-ai-watermarks[detect]` |
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| Invisible image removal (needs CUDA) | `remove-ai-watermarks[qwen-zimage]` |
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| Every production feature | `remove-ai-watermarks[all]` |
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Lower-level and specialized extras include `pixels`, `heif`, `trustmark`,
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`migan`, `lama`, and `diffusion`. The
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[installation guide](docs/installation.md#feature-extras) documents their exact
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dependency composition and model requirements.
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## Quick start
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Install the metadata-focused default CLI:
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```bash
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uv tool install remove-ai-watermarks
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```
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Inspect an image:
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```bash
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remove-ai-watermarks identify image.png
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```
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For visible watermark removal, install the pixel dependencies:
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```bash
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uv tool install --force "remove-ai-watermarks[visible]"
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```
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Then remove a known visible mark and AI metadata:
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```bash
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remove-ai-watermarks visible image.png -o clean.png
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```
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Strip metadata without running visible inpainting or diffusion:
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```bash
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remove-ai-watermarks metadata image.png --remove -o clean.png
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```
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Without `-o` this command overwrites the source in place.
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Inspect or remove AI metadata from an MP4, MOV, M4V, WebM, MKV, AVI, or FLV
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file:
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```bash
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remove-ai-watermarks video metadata input.mp4 --check
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remove-ai-watermarks video metadata input.mp4 --remove -o clean.mp4
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```
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The `video metadata` command does not transcode video or audio streams. Unlike
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the image command above, when `-o` is omitted it writes `<source>_clean` and
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preserves the original. MP4 and MOV
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inspection includes the native TC260 `AIGC` tag in
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`moov.udta.meta.keys/ilst`, including a `moov` placed after the media payload.
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MKV and WebM inspection reads the normative
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`Segment.Tags.Tag.SimpleTag` placement. AVI uses `LIST/INFO/AIGC`, while FLV
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uses `script.onMetaData.AIGC`. The non-ISOBMFF formats are remuxed with stream
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copy for removal.
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Use the product-oriented video path to identify or clean a file:
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```bash
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uv tool install --force "remove-ai-watermarks[video]"
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remove-ai-watermarks video identify input.mp4
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remove-ai-watermarks video all input.mp4 -o clean.mp4
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```
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`video all` removes a stable registered visible mark when present and always
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strips verified AI metadata. If neither signal is found, it still writes a
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same-container passthrough, so application callers get one predictable output
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contract. Proprietary invisible-video removal is excluded by default.
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`--invisible` opts into the lossy, oracle-certified video SynthID profile.
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Process a directory with the same contract:
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```bash
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remove-ai-watermarks video batch ./videos --mode all
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```
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Remove a supported visible video mark:
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```bash
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remove-ai-watermarks video visible input.mp4 -o clean.mp4
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remove-ai-watermarks video visible veo.mp4 --mark veo -o veo_clean.mp4
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remove-ai-watermarks video visible seedance.mp4 --mark seedance -o seedance_clean.mp4
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remove-ai-watermarks video visible dola.mp4 --mark dola -o dola_clean.mp4
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remove-ai-watermarks video visible hailuo.mp4 --mark hailuo -o hailuo_clean.mp4
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remove-ai-watermarks video visible kling.mp4 --mark kling -o kling_clean.mp4
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```
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This path scans the complete sequence before changing pixels. It accepts only a
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mark that repeats at a stable position across adjacent frames, then reuses the
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same OpenCV, MI-GAN, or LaMa fill backends as image removal. Audio is copied
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without re-encoding and is allowed to reach its natural end; the video stream
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is transcoded because its pixels change. By default, a guarded optical-flow
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pass motion-aligns the preceding accepted fill and blends it only when the
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nearby source context agrees; use `--no-temporal-consistency` to disable it.
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The encoder preserves supported
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8-bit source chroma sampling, color tags, and MP4/MOV track timescale instead
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of relying on ffmpeg's implicit raw-BGR defaults. Variable frame intervals are
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preserved through a timestamped in-memory NUT bridge instead of being flattened
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to the average frame rate. Non-zero source start timestamps are retained
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together with the copied audio offset. The default `--mark auto`
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scans all providers in one decode pass and selects the first stable match in
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the specificity order shown below. Pass an explicit mark to restrict detection
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to one provider.
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Sora covers the moving Sora 2 mascot and wordmark. Veo covers both the current
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four-point diamond and the legacy `Veo` text. Seedance covers the fixed boxed
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`AI` label, Dola covers the fixed `Dola AI` text, Hailuo covers the composite
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`MINIMAX | hailuo AI` label, and Kling covers the bottom-right `KLING AI`
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label with its version suffix. A completed encode is published atomically. No
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output is written when no stable mark is found.
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HDR, PQ/HLG, and greater-than-8-bit inputs are rejected before encoding rather
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than silently reduced through OpenCV's 8-bit BGR boundary.
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Remove video SynthID:
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```bash
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uv tool install --force "remove-ai-watermarks[video,diffusion]"
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remove-ai-watermarks video invisible input.mp4 -o clean.mp4
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```
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This path regenerates the complete sequence with one latent-noise field shared
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across time, copies complete audio, strips source metadata, and publishes the
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completed encode atomically. The default `noise_std=0.15` profile passed both
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the two-carrier calibration and a complete public eight-second Veo oracle
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check. Google does not publish a local decoder, so a fresh provider check
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remains useful for unusually important files or after provider changes, but it
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is not a product result state.
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For invisible watermark removal, install the `qwen-zimage` extra. **An NVIDIA GPU
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is required**: both profiles are CUDA-only, and there is no CPU or MPS fallback.
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```bash
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uv tool install --force "remove-ai-watermarks[qwen-zimage]"
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remove-ai-watermarks invisible image.png -o clean.png
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```
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If the local detectors cannot confirm an invisible watermark but you know the
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image came from an AI generator, add `--force`:
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```bash
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remove-ai-watermarks invisible image.png -o clean.png --force
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```
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See the [installation guide](docs/installation.md) for Homebrew, uv, optional
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features, and development setup.
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## Examples
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### Visible Gemini mark
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| Before | After |
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| --- | --- |
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### High quality invisible removal
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`qwen-zimage` is the default profile: a Qwen-Image-2512 Lightning pass under Canny
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ControlNet, followed by SAM-masked Z-Image repair of any detected face. The
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alternative, `sdxl-zimage`, swaps the global stage for SDXL and keeps the same face
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stage. Both are CUDA only.
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```bash
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uv tool install --force "remove-ai-watermarks[qwen-zimage]"
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remove-ai-watermarks invisible image.png -o clean.png --force
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```
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| OpenAI example before | OpenAI example after |
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| --- | --- |
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| [](data/synthid/originals/ChatGPT%20Image%20May%2030,%202026,%2010_31_08%20AM.png) | [](docs/images/qwen-zimage/ChatGPT/ChatGPT%20Image%20May%2030,%202026,%2010_31_08%20AM_full_clean.png) |
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| Gemini example before | Gemini example after |
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| --- | --- |
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| [](data/synthid/originals/Gemini_Generated_Image_633uuy633uuy633u.png) | [](docs/images/qwen-zimage/Gemini/Gemini_Generated_Image_633uuy633uuy633u_full_clean.png) |
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These exact output files were checked with the matching provider verifiers. That
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result applies to these files, not to every seed, image, or future watermark
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version.
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## Common recipes
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### Remove every detected visible mark
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```bash
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remove-ai-watermarks visible image.png -o clean.png
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```
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The default `--mark auto` checks all registered visible marks and removes every
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match. If the mark is visible to you but the detector misses it, select its
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region explicitly:
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```bash
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remove-ai-watermarks erase image.png \
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--region 1640,1930,400,100 \
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-o clean.png
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```
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`--region` uses `x,y,width,height` and may be repeated.
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### Use a learned fill backend
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The `visible` extra uses OpenCV inpainting when no learned backend is installed.
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For more difficult backgrounds, the learned-backend extras include the same
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pixel dependencies automatically:
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```bash
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uv tool install --force "remove-ai-watermarks[migan]"
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remove-ai-watermarks visible image.png -o clean.png --backend migan
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```
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```bash
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uv tool install --force "remove-ai-watermarks[lama]"
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remove-ai-watermarks visible image.png -o clean.png --backend lama
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```
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### Reduce CUDA memory use
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```bash
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remove-ai-watermarks invisible image.png -o clean.png \
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--cpu-offload --force
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```
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CPU offload lowers CUDA memory pressure by moving model components between CPU
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and GPU, at the cost of speed.
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### Process a directory
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```bash
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remove-ai-watermarks batch ./images --mode visible
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remove-ai-watermarks batch ./images --mode all
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```
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## What the tool can recognize
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Visible mark support includes:
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- Google Gemini and Nano Banana sparkle;
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- Doubao, Jimeng, Qwen, Kling, Yuanbao, Baidu, LibLibAI, and RunningHub labels;
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- one calibrated Samsung Galaxy AI label variant.
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Metadata and provenance inspection covers C2PA, EXIF, XMP, IPTC, common
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generator parameters, China TC260 AIGC labels, and several vendor specific
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signals. Optional decoders add support for open DWT-DCT watermarks and Adobe
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TrustMark.
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The exact support matrix, including important locale and detector limits, lives
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in [supported signals](docs/supported-signals.md).
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## How it works
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Visible removal follows three steps:
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1. Detect a registered mark in its expected area.
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2. Build a mask around the mark.
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3. Fill only the masked region with OpenCV, MI-GAN, or LaMa.
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Metadata removal uses format aware stripping. JPEG metadata removal preserves
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the encoded image scan instead of recompressing it. Native MP4/MOV TC260 values
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are blanked without changing box sizes or media offsets. Other supported
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containers use their corresponding metadata path.
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Invisible removal is different. It regenerates the image through a diffusion
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pipeline to disrupt pixel and frequency domain watermarks. This changes the
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image and cannot guarantee that a proprietary verifier will reject every
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output.
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See [supported signals](docs/supported-signals.md) and
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[known limitations](docs/known-limitations.md) for the full technical boundary.
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## Python API
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The visible-removal API requires `remove-ai-watermarks[visible]`.
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```python
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import remove_ai_watermarks as raiw
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result, removed = raiw.remove_visible("watermarked.png", "clean.png")
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print(removed)
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provenance = raiw.identify_video("input.mp4")
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report = raiw.inspect_video_metadata("input.mp4")
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complete = raiw.remove_video_all("input.mp4", "clean.mp4")
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batch = raiw.remove_video_batch("videos", "videos_clean")
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cleaned = raiw.remove_video_metadata("input.mp4")
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synthid_cleaned = raiw.remove_video_invisible("input.mp4", "synthid_clean.mp4")
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visible = raiw.remove_video_visible("input.mp4", "clean.mp4")
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print(visible.mark)
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veo = raiw.remove_video_visible("veo.mp4", "veo_clean.mp4", mark="veo")
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seedance = raiw.remove_video_visible(
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"seedance.mp4",
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"seedance_clean.mp4",
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mark="seedance",
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)
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dola = raiw.remove_video_visible("dola.mp4", "dola_clean.mp4", mark="dola")
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```
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The high level API accepts a file path or a BGR NumPy array. For path inputs it
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also reads provenance metadata, preserves alpha, and can strip AI metadata from
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the written result.
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See the [Python API guide](docs/python-api.md) for visible removal, the full
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`remove_all` and `remove_batch` pipeline, provenance inspection, metadata
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stripping, and diffusion usage.
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## ComfyUI
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The separate
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[ComfyUI Remove AI Watermarks](https://github.com/wiltodelta/ComfyUI-remove-ai-watermarks)
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package provides nodes for visible removal, detection, region erasing, and
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invisible removal.
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## Important limitations
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- A missing local signal means unknown, not clean. Proprietary pixel
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watermarks may remain after metadata has been stripped.
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- Visible removal reconstructs a small region. Results depend on the background
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and selected fill backend.
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- Invisible removal changes the whole image and may alter faces, text, or fine
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detail.
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- Visible video removal recognizes the moving Sora 2 wordmark, the current Veo
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diamond plus legacy `Veo` text, the Seedance boxed `AI` label, and the fixed
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Dola, Hailuo, and Kling labels. It does not recognize the older Sora Turbo
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corner swirl or unregistered layouts from those providers.
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The classical OpenCV backend can smear structured backgrounds; use MI-GAN or
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LaMa when recovery quality matters.
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- Video SynthID regeneration changes resolution, frame rate, and image detail.
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The shipped profile is oracle-certified, but no public local decoder can
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certify an arbitrary output at runtime. Recheck unusually important outputs
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after provider changes.
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- Invisible-watermark removal requires CUDA. Both profiles refuse any other
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device at construction rather than falling back to one that cannot run them.
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Visible removal, metadata stripping and `identify` still run anywhere.
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- Provider watermark systems can change. Validate important outputs with the
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provider's own verifier when one is available.
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The shipped `video invisible` command uses the certified `noise_std=0.15`
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profile. The companion `scripts/video_synthid_sweep.py` research harness builds
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a matched re-encode control plus VAE-regenerated candidates and leaves the
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verifier verdict blank:
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```bash
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uv run --extra video --extra diffusion python scripts/video_synthid_sweep.py input.mp4 -o sweep/
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```
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The control must still be SynthID-positive before a negative candidate can
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count as removal evidence. In the 2026-07-29 two-clip calibration, both matched
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controls were positive in Gemini's built-in SynthID verifier; the stronger
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candidate was negative on both carriers, while a weaker candidate was
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negative on one. A later adversarial follow-up that asked ordinary Gemini to
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reinterpret the pixel result returned `UNAVAILABLE`; that follow-up was not a
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verifier rerun and does not invalidate the built-in verdicts. A 2026-07-31
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full-clip check on a public eight-second Veo sample found `0.10` still detected
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and `0.15` not detected, so `0.15` is now the certified default. The
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reproducible hashes and verdicts live in
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`data/evaluations/video-synthid-oracle.csv`.
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## Documentation
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Start with the [documentation index](docs/index.md).
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- [Installation](docs/installation.md)
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- [CLI guide](docs/cli.md)
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- [Python API](docs/python-api.md)
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- [Supported signals](docs/supported-signals.md)
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- [Known limitations](docs/known-limitations.md)
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- [Scope, safety, and legal notes](docs/legal-and-safety.md)
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- [Module internals](docs/module-internals.md)
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- [Release and distribution](docs/release-and-distribution.md)
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Research notes and historical experiments are listed separately in the
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[documentation index](docs/index.md). They explain past decisions but do not
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define the current public API.
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## Contributing
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Install the development environment and run the project gate:
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```bash
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uv sync --frozen --extra dev
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bash maintain.sh
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```
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See [module internals](docs/module-internals.md) before changing a subsystem
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with documented invariants.
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## License
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[Apache 2.0](LICENSE). Copyright 2025-2026 wiltodelta.
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