mirror of
https://github.com/wiltodelta/remove-ai-watermarks.git
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133 lines
4.7 KiB
Python
133 lines
4.7 KiB
Python
"""Remove-AI-Watermarks: Unified tool for removing visible and invisible AI watermarks.
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High-level API (lazy, so ``import remove_ai_watermarks`` stays cheap)::
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import remove_ai_watermarks as raiw
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raiw.remove_visible("in.png", "out.png") # clean a file (provenance auto)
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result, removed = raiw.remove_visible(bgr_array) # array -> array
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report = raiw.remove_visible_detailed(bgr_array) # cleaned / partial / unvalidated
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raiw.visible_provenance("in.png") # -> frozenset of confirmed vendors
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raiw.identify_video("in.mp4") # -> VideoProvenanceReport
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raiw.inspect_video_metadata("in.mp4") # -> VideoMetadataReport
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raiw.remove_video_all("in.mp4", "out.mp4") # visible + verified metadata
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raiw.remove_video_batch("videos", "videos_clean") # complete per-file results
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raiw.remove_video_metadata("in.mp4", "out.mp4") # verified metadata strip
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raiw.remove_video_invisible("in.mp4", "out.mp4") # calibrated video-pixel regeneration
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raiw.remove_video_visible("in.mp4", "out.mp4") # stable visible video-mark removal
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raiw.classify_source("in.png") # source pipeline, not SynthID detection
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raiw.classify_image_source("in.png") # newer source patterns, not SynthID detection
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For a provenance verdict use the ``identify`` submodule::
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from remove_ai_watermarks.identify import identify
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report = identify("in.png")
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"""
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import os as _os
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import warnings as _warnings
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from typing import TYPE_CHECKING
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# transformers prints a noisy deprecation for the Siglip2ImageProcessorFast
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# alias when it is imported (by the optional GPU/ML path). Silence it before
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# any submodule pulls transformers in, so the CLI startup stays quiet. Uses
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# setdefault so a user-set TRANSFORMERS_VERBOSITY still wins.
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_os.environ.setdefault("TRANSFORMERS_VERBOSITY", "error")
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_warnings.filterwarnings("ignore", message=r".*ImageProcessorFast.*")
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__version__ = "0.42.0"
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__all__ = [
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"BatchItemResult",
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"BatchSummary",
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"ImageSourceClassification",
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"InvisibleOptions",
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"MetadataStripIncomplete",
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"RemoveAllResult",
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"SourceClassification",
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"VisibleRemovalResult",
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"__version__",
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"classify_image_source",
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"classify_source",
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"identify_video",
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"inspect_video_metadata",
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"remove_all",
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"remove_batch",
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"remove_video_all",
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"remove_video_batch",
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"remove_video_invisible",
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"remove_video_metadata",
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"remove_video_visible",
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"remove_visible",
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"remove_visible_detailed",
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"visible_provenance",
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]
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if TYPE_CHECKING:
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from remove_ai_watermarks.api import (
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BatchItemResult,
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BatchSummary,
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InvisibleOptions,
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MetadataStripIncomplete,
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RemoveAllResult,
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VisibleRemovalResult,
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remove_all,
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remove_batch,
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remove_visible,
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remove_visible_detailed,
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visible_provenance,
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)
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from remove_ai_watermarks.source_classify import SourceClassification, classify_source
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from remove_ai_watermarks.source_classify_v2 import ImageSourceClassification, classify_image_source
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from remove_ai_watermarks.video import (
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identify_video,
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inspect_video_metadata,
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remove_video_all,
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remove_video_batch,
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remove_video_invisible,
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remove_video_metadata,
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remove_video_visible,
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)
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def __getattr__(name: str) -> object:
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"""Lazily resolve the high-level API (PEP 562), so the heavy imports (cv2, the
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metadata/identify stack) load only when a caller actually reaches for them."""
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if name in (
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"BatchItemResult",
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"BatchSummary",
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"InvisibleOptions",
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"MetadataStripIncomplete",
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"RemoveAllResult",
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"VisibleRemovalResult",
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"remove_all",
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"remove_batch",
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"remove_visible",
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"remove_visible_detailed",
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"visible_provenance",
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):
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from remove_ai_watermarks import api
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return getattr(api, name)
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if name in ("SourceClassification", "classify_source"):
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from remove_ai_watermarks import source_classify
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return getattr(source_classify, name)
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if name in ("ImageSourceClassification", "classify_image_source"):
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from remove_ai_watermarks import source_classify_v2
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return getattr(source_classify_v2, name)
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if name in (
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"identify_video",
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"inspect_video_metadata",
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"remove_video_all",
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"remove_video_batch",
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"remove_video_invisible",
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"remove_video_metadata",
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"remove_video_visible",
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):
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from remove_ai_watermarks import video
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return getattr(video, name)
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raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
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