"""Qwen (Tongyi Qianwen, Alibaba) visible watermark detector/localizer. Qwen stamps its generations with a visible "千问AI生成" text strip in the bottom-right corner -- the explicit AIGC label mandated by China's GB 45438-2025 (the same 6-glyph house style as Doubao's "豆包AI生成": a 2-glyph vendor prefix plus the shared `AI生成` tail), preceded by the vendor's tri-lobe logo (not part of the detection silhouette -- logos vary between releases, the CJK run is what discriminates). Detection matches the bundled glyph silhouette against the corner; removal is the shared **localize -> fill** (the glyph-bbox :meth:`footprint_mask` feeds ``region_eraser``), NOT reverse-alpha. This module supplies only Qwen's tuned :class:`TextMarkConfig` (``assets/qwen_alpha.png`` -- a font-rendered synthetic silhouette from ``scripts/render_vendor_silhouettes.py``, never cut from an upload). It also feeds ``identify`` as the medium-confidence ``visible_qwen`` signal via the registry. EVERY tuned number below was measured on the vendor cohort (117 TC260 carriers whose producer USCC 91440101MA9Y9T4H7A names the entity, 2026-07-21; harness ``scripts/vendor_mark_calibrate.py``), NOT inherited from Doubao: * The mark sits in TWO size modes (frac of the short side ~0.124 and ~0.203, ratio 1.64 -- wider than the shared 3-rung ladder's 1.5625 span), so a single fraction on the shared ladder covers ~75% of marks and the rest land in the comb's collapse zone. Qwen therefore carries its OWN 2-rung ladder (``TextMarkConfig.ladder``), one rung centred on each mode; the shared default is untouched for every other mark. * The mark also sits FARTHER off the corner than Doubao's box assumes (right margin ~0.025 vs 0.004 of the short side), so Doubao's locate box clipped the first glyph and collapsed an exact-size template to 0.26; the box fractions below are fitted from the measured absolute mark rects. * ``alpha_height_frac`` comes from the aspect fit at the winning width (p50 aspect 0.26), not from the silhouette's own aspect (0.2219) and not from Doubao's ratio. * STRICT ONLY (``provenance_ncc_factor`` 1.0): the score band just below the gate is dominated by non-Qwen banners on same-cohort frames (a 夸克 anti-forgery strip at 0.274, a 造点 mark at 0.253), so a provenance-relaxed arm would be mostly false fills. No provenance relaxation exists for this mark. * No rival margin: at the shipped gate the template fires on 0 of 400 Doubao-marked frames, 0 of 298 Jimeng-marked frames and 0 of 286 hand-labelled clean frames (the shared tail correlates at ~0.22, far below the gate), while a 0.10 rival margin would have suppressed ~10% of genuine Qwen detections. """ # The module-level _alpha_template / _glyph_silhouette / _template_match_score below # are thin test-facing shims (imported by tests/), so pyright's src-only pass sees them # as unused; the use is cross-module. # 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, TextMarkDetection, TextMarkEngine if TYPE_CHECKING: from pathlib import Path from numpy.typing import NDArray # Locate geometry as a fraction of the image SHORT side (measured basis -- see # scale_base). The box is fitted to the measured mark rects: the mark's right # margin is ~0.025 of the short side (not Doubao's 0.004), so the box anchor is # wider off the corner; width/height cover the big size mode plus NCC slack. WM_WIDTH_FRAC = 0.231 WM_HEIGHT_FRAC = 0.074 MARGIN_RIGHT_FRAC = 0.0203 MARGIN_BOTTOM_FRAC = 0.0218 # Glyph appearance: a light, low-saturation gray rendered brighter than the local # background (white top-hat), same overlay class as Doubao -- inherited, and # harmless because the tophat front-end turns these gates into weights. MAX_SATURATION = 55 LOGO_MIN_LUMA = 150 TOPHAT_DELTA = 12 DETECT_MIN_COVERAGE = 0.04 # unused by the tophat front-end (kept for config parity) # Calibrated 2026-07-21 on the vendor cohort vs 286 hand-labelled clean frames # (cohort-contamination-guarded): clean p99 0.301 / max 0.316, and every cohort # frame scoring >= 0.45 carries a visible 千问AI生成 mark (86% of the eyeballed # visible marks fire, the misses being white-on-near-white contrast losses). # 0.45 was picked over 0.32 (identical clean fire) for margin against unseen # clean content at zero measured recall cost. DETECT_NCC_THRESHOLD = 0.45 # Detection-silhouette geometry (fraction of the short side), fitted on the # cohort: the mark's width modes and its aspect (0.26) at the winning width. _ALPHA_WIDTH_FRAC = 0.160 _ALPHA_HEIGHT_FRAC = 0.0416 # The two measured size modes as scale rungs: 0.124 and 0.203 of the short side, # expressed against the 0.160 nominal. Measured, not rounded: off-mode rungs drop # NCC from ~0.73 to ~0.37 on real marks (the comb), and a 4-rung variant scored # strictly worse (the extra rungs cover nothing and the big mode lands 4.6% off # its nearest rung). _LADDER = (0.78, 1.27) _CONFIG = TextMarkConfig( name="Qwen", asset_name="qwen_alpha.png", corner="br", margin_floor=4, width_frac=WM_WIDTH_FRAC, height_frac=WM_HEIGHT_FRAC, margin_x_frac=MARGIN_RIGHT_FRAC, margin_bottom_frac=MARGIN_BOTTOM_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, detect_frontend="tophat", scale_basis="short", # measured: frac_short CV 0.189 vs width 0.273 ladder=_LADDER, alpha_width_frac=_ALPHA_WIDTH_FRAC, alpha_height_frac=_ALPHA_HEIGHT_FRAC, min_gw=8, # STRICT ONLY: the sub-gate band is dominated by non-Qwen banners, so # provenance relaxation is disabled outright (factor 1.0 = never relaxed). provenance_ncc_factor=1.0, ) QwenDetection = TextMarkDetection def _alpha_template() -> NDArray[Any] | None: """The bundled Qwen alpha template (float [0,1]), or None.""" return _text_mark_engine.load_alpha_template(_CONFIG.asset_name) def _glyph_silhouette() -> NDArray[Any] | None: """Binary "千问AI生成" silhouette (255 = glyph) from the alpha map, or None.""" return _text_mark_engine.glyph_silhouette(_CONFIG.asset_name) def _template_match_score(box_mask: NDArray[Any], scale_base: int) -> float: """TM_CCOEFF_NORMED of the Qwen glyph silhouette against ``box_mask``.""" return _text_mark_engine.template_match_score(box_mask, scale_base, _CONFIG) class QwenEngine(TextMarkEngine): """Detect/localize the visible Qwen "千问AI生成" watermark (locate -> mask; mask feeds the fill).""" def __init__(self) -> None: super().__init__(_CONFIG) def load_image_bgr(path: str | Path) -> NDArray[Any]: """Read an image as BGR ndarray (helper for scripts/tests).""" from remove_ai_watermarks import image_io img = image_io.imread(path) if img is None: raise FileNotFoundError(f"Failed to read image: {path}") return img