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https://github.com/wiltodelta/remove-ai-watermarks.git
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feat: complete product video watermark pipeline
This commit is contained in:
Victor Kuznetsov
+94
-19
@@ -125,9 +125,57 @@ The command also supports the audio and video containers listed in
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[supported signals](supported-signals.md). ffmpeg must be available for the
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non-ISOBMFF audio and video path.
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## Identify and clean video
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Inspect every locally supported video signal:
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```bash
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remove-ai-watermarks video identify input.mp4
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remove-ai-watermarks video identify input.mp4 --json
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remove-ai-watermarks video identify input.mp4 --no-visible
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```
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The default scans the complete clip for stable registered visible marks and
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inspects supported metadata. A result with no signals is reported as unknown,
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not clean, because proprietary pixel watermarks have no public local decoder.
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`--no-visible` performs metadata-only inspection.
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Use the complete locally verifiable cleaning path:
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```bash
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remove-ai-watermarks video all input.mp4 -o clean.mp4
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```
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It removes a stable supported visible mark when found and always strips
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verified AI metadata. When neither signal is found, it writes a same-container
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passthrough instead of returning a missing output. The source is never
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overwritten.
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Invisible regeneration is deliberately opt-in:
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```bash
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remove-ai-watermarks video all input.mp4 -o clean.mp4 --invisible
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```
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That option is supported only for MP4, MOV, and M4V. It is lossy and uses the
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same oracle-certified profile as `video invisible`.
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Process all supported files in a top-level directory:
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```bash
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remove-ai-watermarks video batch ./videos --mode all
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remove-ai-watermarks video batch ./videos --mode visible
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remove-ai-watermarks video batch ./videos --mode metadata
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```
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The batch runs sequentially, preserves successful outputs when another file
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fails, and exits nonzero if any item failed. Visible no-op files are copied
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byte-for-byte so the output directory remains complete. `--invisible` is
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available only with `--mode all`.
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## Strip AI metadata from video
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The experimental video namespace starts with metadata inspection and removal:
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Metadata inspection and removal are also available as an isolated operation:
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```bash
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remove-ai-watermarks video metadata input.mp4 --check
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@@ -139,8 +187,11 @@ delegates to the same verified metadata scanner and stripper as the generic
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`metadata` command, so detection and removal stay in parity. Video and audio
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streams are not transcoded. For MP4 and MOV, this includes the native TC260
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`AIGC` key and JSON value stored in `moov.udta.meta.keys/ilst`. The inspector
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seeks past a large `mdat` to find a tail `moov`; removal blanks the key and
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value in place so box sizes and media offsets do not move.
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seeks past a large `mdat` to find a tail `moov`. Removal stream-copies the
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container in bounded chunks, converts supported top-level provenance boxes to
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same-size `free` boxes, and blanks the TC260 key/value in place. Box sizes,
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media offsets, and encoded stream bytes do not move; the result is atomically
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published only after the complete copy succeeds.
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For MKV and WebM, the inspector reads the native TC260
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`Segment.Tags.Tag.SimpleTag` entry. Removal uses ffmpeg stream copying to
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@@ -156,14 +207,14 @@ different container extension.
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Visible video labels and invisible video watermarks are not handled by this
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command.
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## Generate a video SynthID candidate
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## Remove video SynthID
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```bash
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uv tool install --force "remove-ai-watermarks[gpu]"
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remove-ai-watermarks video invisible input.mp4 -o candidate.mp4
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remove-ai-watermarks video invisible input.mp4 -o clean.mp4
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```
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The experimental command supports MP4, MOV, and M4V. It samples the complete
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The command supports MP4, MOV, and M4V. It samples the complete
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sequence at the configured frame rate, resizes frames to the configured long
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side, regenerates them through a VAE, and applies one deterministic latent-noise
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field to every frame. Reusing one spatial field avoids the unnecessary flicker
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@@ -171,22 +222,28 @@ caused by independent per-frame noise. Frames are regenerated in bounded
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batches and streamed directly to ffmpeg, which encodes the result, copies
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audio, and drops source metadata.
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The output is always an unverified candidate. The project has no local video
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SynthID decoder, and PSNR or temporal-residual metrics cannot prove watermark
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absence. After generation, upload the candidate to Gemini Flash and ask:
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The default `noise_std=0.15` profile is oracle-certified. The project has no
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local video SynthID decoder, so an optional per-file recheck is still useful
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for unusually important files or after provider changes. In a new Gemini chat,
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upload the original first, invoke the built-in verifier with `@synthid`, and ask:
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> Was this uploaded video created or edited by Google AI? Use the built-in
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> content verification result.
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> For the video attached to this message, was it created or edited by Google
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> AI? Use the built-in SynthID content verification result.
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Only an explicit built-in verification result is an oracle verdict. A response
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based on the visible logo, content appearance, or metadata is not. The command
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prints `UNVERIFIED` even when generation succeeds.
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The source must be positive. Then upload the processed result in a separate new
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chat and repeat the same built-in check. Only a source-positive, output-negative
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pair is a fresh per-file verification. Do not ask an adversarial follow-up that tells the
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chat model to ignore the verifier and reason about raw pixels: that is ordinary
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Gemini reasoning, not a second oracle check.
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The default output is `<source>_synthid_candidate` in the same container. The
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The default output is `<source>_clean` in the same container. The
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source is never overwritten. Use `--noise-std`, `--long-side`, `--fps`,
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`--batch-size`, `--seed`, and `--device` to control the regeneration. The
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defaults are calibrated operating points, not a guarantee for every carrier or
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future verifier version.
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default noise level is `0.15`. It cleared both carriers in the 2026-07-29
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short-clip calibration and the complete public eight-second Veo carrier in the
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2026-07-31 full-clip check; `0.10` remained detected on that complete clip. This
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calibration certifies the shipped operating point; the paired check above is an
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optional runtime audit, not a separate result state.
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## Remove a supported visible video mark
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@@ -199,7 +256,7 @@ 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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The experimental command supports the moving Sora mascot and wordmark, two Veo
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The command supports the moving Sora mascot and wordmark, two Veo
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corner variants, the Seedance boxed `AI` label, the `Dola AI` text label, the
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composite `MINIMAX | hailuo AI` label, and the bottom-right Kling label. Sora
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searches the whole frame at multiple scales. The other detectors search bounded
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@@ -218,13 +275,31 @@ provider.
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The video stream is transcoded and the complete original audio stream is
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copied without truncating an audio tail that extends beyond the final video
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frame.
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frame. The encoder probes the source stream and preserves supported 8-bit
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chroma sampling, color range/matrix/transfer/primaries tags, and MP4/MOV track
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timescale. For a variable-frame-rate source, decoded PTS are carried through a
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timestamped in-memory NUT bridge so the output retains the source frame
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intervals instead of flattening them to a constant rate. A non-zero source
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start PTS and the copied audio start offset are preserved as well.
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Supported input and output containers are MP4, MOV, M4V, WebM, MKV, AVI, and
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FLV; the output extension must match the input. The default `cv2` backend is
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fast but can smear structured backgrounds. Select `--backend migan` or
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`--backend lama` for a learned fill, or `--backend auto` to choose the best
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installed backend.
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`--temporal-consistency` is enabled by default. It motion-aligns the preceding
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accepted fill, requires overlapping removal masks and matching source context,
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and blends only the safely covered pixels. Scene cuts, disjoint moving marks,
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or a poor motion match keep the independent current-frame fill. Use
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`--no-temporal-consistency` for an exact frame-local baseline.
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The pixel path is intentionally limited to SDR 8-bit video. A high-bit-depth,
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PQ, or HLG source is rejected before ffmpeg starts, preserving any existing
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output instead of silently downconverting it through OpenCV's 8-bit boundary.
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On CPU, MI-GAN is the practical learned tier. LaMa remains an explicit offline
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quality option because full-sequence inference is too slow and memory-heavy
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for an online worker.
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AI metadata is stripped from the encoded output by default. Use
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`--keep-metadata` to retain mapped container metadata. When no temporally stable
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mark is found, the command writes no output and exits with the no-visible-mark
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