mirror of
https://github.com/wiltodelta/remove-ai-watermarks.git
synced 2026-08-31 17:50:35 +02:00
Victor Kuznetsov
23696f42a8
The OCR badge census split the 343 Microsoft-C2PA uploads into 86 badge carriers and 257 true badge-less files (the watermark is a per-user opt-in). Badge-less scores max 0.251 / p99 0.213, so the 0.266 relaxed gate admits the three faint badges in [0.251, 0.38) with zero measured false fills; re-verified on the provenance path as 3 band detections and 0/257 badge-less fires.
109 lines
4.5 KiB
Python
109 lines
4.5 KiB
Python
"""Microsoft top-right AI-badge detector/localizer.
|
|
|
|
This engine covers one measured Microsoft output variant: a white pill with dark
|
|
internal shapes in the top-right corner. The evaluated files used both "Made with
|
|
AI" and "AI-Generated" wording. This is narrower than Microsoft's documented
|
|
watermark feature, which can use a Copilot icon or text and can place the mark in
|
|
other positions. A Microsoft provenance signal therefore does not establish that
|
|
this exact visible variant is present.
|
|
|
|
Detection matches a synthetic pill silhouette (white pill with the sparkle and
|
|
text KNOCKED OUT) against the top-hat blob of the located box: the holes are what
|
|
discriminate this pill from any other bright rounded element in the corner.
|
|
Removal is the shared **localize -> fill**; the glyph-bbox :meth:`footprint_mask`
|
|
covers the whole pill including its text.
|
|
|
|
The tuned numbers below were remeasured on 2026-08-27 with the registered engine
|
|
and ``scripts/registered_mark_calibrate.py``. The arms were kept distinct: 17
|
|
visually confirmed carriers, 343 Microsoft-provenance files whose visible-mark
|
|
status was not adjudicated, and 1200 non-overlapping no-signal controls:
|
|
|
|
* Geometry is single-mode and tight: pill 0.152 x 0.040 of the LONG side
|
|
(aspect 3.73-3.89 over 720..1536 px), margins ~0.010/0.007 of the same basis. One size
|
|
mode, so the shared 3-rung ladder is untouched and the locate box simply
|
|
wraps the pill with NCC slack.
|
|
* Provenance relaxation 0.7 (relaxed gate 0.266), enabled 2026-08-28 when the
|
|
cohort the strict-only note was waiting for became available: an OCR badge
|
|
census split the 343 Microsoft-C2PA uploads into 86 badge carriers and 257
|
|
true badge-less files (the watermark is a per-user opt-in, so 75% of MS
|
|
uploads carry none). Badge-less max 0.251 / p99 0.213, so the relaxed band
|
|
[0.251, 0.38) holds three genuine faint badges and zero false fills
|
|
(measured 3/3; doubao ships 0.7 on a 58%-precision band). Strict controls
|
|
max 0.293 / p99 0.200 vs the 0.38 gate.
|
|
* Front-end "binary": the pill is a bold opaque overlay; the tophat blob is
|
|
solid with dark-text holes, exactly the template's shape.
|
|
"""
|
|
|
|
# pyright: reportUnusedFunction=false
|
|
|
|
from __future__ import annotations
|
|
|
|
from typing import TYPE_CHECKING, Any
|
|
|
|
from remove_ai_watermarks import _text_mark_engine
|
|
from remove_ai_watermarks._text_mark_engine import TextMarkConfig, TextMarkEngine
|
|
|
|
if TYPE_CHECKING:
|
|
from numpy.typing import NDArray
|
|
|
|
# Locate geometry as a fraction of the image LONG side (measured; scale_basis="long":
|
|
# on 1024x1536 portraits the pill tracks the 1536, and a width basis undersized
|
|
# the template until the portrait carriers fell to 0.15-0.32 NCC).
|
|
# The box wraps the measured pill rect (0.152W x 0.040W) with NCC slack; margins
|
|
# sit inside the pill's own ~0.010W-right / ~0.007W-top insets.
|
|
WM_WIDTH_FRAC = 0.170
|
|
WM_HEIGHT_FRAC = 0.055
|
|
MARGIN_RIGHT_FRAC = 0.004
|
|
MARGIN_TOP_FRAC = 0.003
|
|
|
|
# Glyph appearance: a bright near-white pill (luma ~245), gray-scale (sat < 60).
|
|
MAX_SATURATION = 60
|
|
LOGO_MIN_LUMA = 170
|
|
TOPHAT_DELTA = 10
|
|
|
|
# Calibrated 2026-08-27: non-overlapping no-signal controls (n=1200) max 0.293 /
|
|
# p99 0.200; visually confirmed carriers (n=17) p50 0.519 / p90 0.578 / max
|
|
# 0.579, with 15/17 above the 0.38 gate. The two misses score 0.249 and 0.315.
|
|
DETECT_MIN_COVERAGE = 0.30 # the pill fills most of its box; content corners do not
|
|
DETECT_NCC_THRESHOLD = 0.38
|
|
|
|
# Pill silhouette geometry (fraction of width): 0.152W x 0.040W, aspect ~3.78.
|
|
_ALPHA_NATIVE_WIDTH = 335
|
|
_ALPHA_WIDTH_FRAC = 0.152
|
|
_ALPHA_HEIGHT_FRAC = 0.040
|
|
|
|
_CONFIG = TextMarkConfig(
|
|
name="Microsoft top-right AI badge",
|
|
asset_name="microsoft_alpha.png",
|
|
corner="tr",
|
|
margin_floor=2,
|
|
width_frac=WM_WIDTH_FRAC,
|
|
height_frac=WM_HEIGHT_FRAC,
|
|
margin_x_frac=MARGIN_RIGHT_FRAC,
|
|
margin_bottom_frac=MARGIN_TOP_FRAC,
|
|
max_saturation=MAX_SATURATION,
|
|
logo_min_luma=LOGO_MIN_LUMA,
|
|
tophat_delta=TOPHAT_DELTA,
|
|
morph_open_size=5,
|
|
detect_min_coverage=DETECT_MIN_COVERAGE,
|
|
detect_ncc_threshold=DETECT_NCC_THRESHOLD,
|
|
alpha_width_frac=_ALPHA_WIDTH_FRAC,
|
|
alpha_height_frac=_ALPHA_HEIGHT_FRAC,
|
|
min_gw=24,
|
|
detect_frontend="binary",
|
|
scale_basis="long",
|
|
provenance_ncc_factor=0.7,
|
|
)
|
|
|
|
|
|
def _alpha_template() -> NDArray[Any] | None:
|
|
"""The bundled Microsoft pill template (float [0,1]), or None."""
|
|
return _text_mark_engine.load_alpha_template(_CONFIG.asset_name)
|
|
|
|
|
|
class MicrosoftEngine(TextMarkEngine):
|
|
"""Detect/localize the measured Microsoft top-right AI badge."""
|
|
|
|
def __init__(self) -> None:
|
|
super().__init__(_CONFIG)
|