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https://github.com/wiltodelta/remove-ai-watermarks.git
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3aea21e632
New samsung_engine.py mirrors the jimeng engine but anchors bottom-left; wired into watermark_registry, the CLI (--mark samsung / auto), and identify (visible_samsung, medium). visible_alpha_solve.py gains a corner=bl mode; samsung_alpha.png solved from @f-liva's flat captures. Calibrated for the Italian "Contenuti generati dall'AI" variant. Flat black/gray/white captures committed, real photos gitignored. Tests + docs. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
193 lines
8.1 KiB
Python
193 lines
8.1 KiB
Python
"""Tests for the Samsung Galaxy AI visible-watermark engine.
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No real Samsung sample is committed (the real-photo captures are gitignored, repo
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is public), so detection/removal is exercised against a watermark synthesized from
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the bundled alpha asset itself -- self-consistent and download-free. The mark is
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anchored bottom-LEFT (unlike the bottom-right Doubao/Jimeng marks).
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"""
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from __future__ import annotations
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import cv2
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import numpy as np
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import pytest
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from remove_ai_watermarks.samsung_engine import (
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_ALPHA_HEIGHT_FRAC,
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_ALPHA_LOGO_BGR,
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_ALPHA_MARGIN_BOTTOM_FRAC,
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_ALPHA_MARGIN_LEFT_FRAC,
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_ALPHA_NATIVE_WIDTH,
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_ALPHA_WIDTH_FRAC,
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DETECT_NCC_THRESHOLD,
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SamsungEngine,
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_alpha_template,
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_glyph_silhouette,
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_template_match_score,
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)
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def _compose(w: int, h: int, bg: float = 100.0):
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"""Composite the real alpha (scaled to width ``w``) onto a flat bg by the
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engine's fixed bottom-left geometry. Returns ``(watermarked_uint8, mark_bool_mask)``."""
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img = np.full((h, w, 3), bg, np.float32)
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at = _alpha_template()
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gw, gh = int(_ALPHA_WIDTH_FRAC * w), int(_ALPHA_HEIGHT_FRAC * w)
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ax = int(_ALPHA_MARGIN_LEFT_FRAC * w)
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ay = h - int(_ALPHA_MARGIN_BOTTOM_FRAC * w) - gh
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amap = np.zeros((h, w), np.float32)
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amap[ay : ay + gh, ax : ax + gw] = cv2.resize(at, (gw, gh))
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a3 = amap[:, :, None]
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wm = (a3 * np.array(_ALPHA_LOGO_BGR, np.float32) + (1 - a3) * img).clip(0, 255).astype(np.uint8)
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return wm, amap > 0.15
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class TestLocate:
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def test_box_anchored_bottom_left(self):
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eng = SamsungEngine()
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img = np.zeros((1448, 1086, 3), np.uint8)
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loc = eng.locate(img)
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assert loc.x < int(1086 * 0.03) # hugs the left edge
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assert 1448 - (loc.y + loc.h) < int(1086 * 0.03) # hugs the bottom
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def test_box_scales_with_width(self):
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eng = SamsungEngine()
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small = eng.locate(np.zeros((1024, 1024, 3), np.uint8))
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large = eng.locate(np.zeros((2048, 2048, 3), np.uint8))
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assert large.w == pytest.approx(small.w * 2, rel=0.1)
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class TestDetect:
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def test_clean_gradient_not_detected(self):
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eng = SamsungEngine()
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ramp = np.tile(np.linspace(0, 255, 1086, dtype=np.uint8), (1086, 1))
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img = cv2.cvtColor(ramp, cv2.COLOR_GRAY2BGR)
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assert not eng.detect(img).detected
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def test_solid_blob_corner_not_detected(self):
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"""A bright blob is not the glyph shape -> low correlation, not detected."""
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eng = SamsungEngine()
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img = np.zeros((1086, 1086, 3), np.uint8)
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x, y, bw, bh = eng.locate(img).bbox
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img[y + bh // 4 : y + bh * 3 // 4, x : x + bw // 2] = 200
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assert not eng.detect(img).detected
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def test_silhouette_loads(self):
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sil = _glyph_silhouette()
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assert sil is not None
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assert set(np.unique(sil)).issubset({0, 255})
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def test_match_score_shape_sensitive(self):
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"""The glyph silhouette correlates with itself, not with a filled block."""
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sil = _glyph_silhouette()
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h, w = sil.shape
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box = np.zeros((h + 8, int(w / _ALPHA_WIDTH_FRAC * 0.2) + w), np.uint8)
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box[4 : 4 + h, 4 : 4 + w] = sil
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assert _template_match_score(box, _ALPHA_NATIVE_WIDTH) >= DETECT_NCC_THRESHOLD
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solid = np.full_like(box, 255)
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assert _template_match_score(solid, _ALPHA_NATIVE_WIDTH) < DETECT_NCC_THRESHOLD
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def test_synthetic_mark_detected(self):
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"""A watermark composed from the real alpha is detected at its threshold."""
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eng = SamsungEngine()
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wm, _mark = _compose(_ALPHA_NATIVE_WIDTH, int(_ALPHA_NATIVE_WIDTH * 1.33))
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det = eng.detect(wm)
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assert det.detected
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assert det.confidence >= DETECT_NCC_THRESHOLD
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class TestReverseAlpha:
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def test_alpha_asset_loads(self):
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at = _alpha_template()
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assert at is not None
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assert at.dtype.kind == "f"
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assert float(at.min()) >= 0.0
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assert float(at.max()) <= 1.0
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def test_logo_is_white(self):
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assert _ALPHA_LOGO_BGR == (255.0, 255.0, 255.0)
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def test_available_whenever_asset_present(self):
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eng = SamsungEngine()
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assert eng.reverse_alpha_available(np.zeros((1086, 1086, 3), np.uint8))
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assert eng.reverse_alpha_available(np.zeros((4054, 2958, 3), np.uint8))
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assert not eng.reverse_alpha_available(np.zeros((0, 0, 3), np.uint8))
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def test_removes_synthetic_mark(self):
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"""Reverse-alpha + residual inpaint clears the composed mark (re-detect no
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longer fires)."""
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eng = SamsungEngine()
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wm, _mark = _compose(_ALPHA_NATIVE_WIDTH, int(_ALPHA_NATIVE_WIDTH * 1.33))
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assert eng.detect(wm).detected
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out = eng.remove_watermark_reverse_alpha(wm)
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assert not eng.detect(out).detected
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@pytest.mark.parametrize(
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("w", "h", "max_err"),
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[
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(_ALPHA_NATIVE_WIDTH, int(_ALPHA_NATIVE_WIDTH * 1.33), 5.0), # captured width
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(2958, 4054, 10.0), # real-photo width (~2.7x native) -> NCC alignment generalizes
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],
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)
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def test_recovers_flat_background(self, w, h, max_err):
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eng = SamsungEngine()
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wm, mark = _compose(w, h)
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assert float(np.abs(wm.astype(np.float32)[mark] - 100.0).mean()) > 15 # mark visible
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out = eng.remove_watermark_reverse_alpha(wm).astype(np.float32)
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assert float(np.abs(out[mark] - 100.0).mean()) < max_err
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def test_far_region_untouched(self):
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"""The residual inpaint only touches the bottom-left footprint; the
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opposite (top-right) corner stays pixel-identical."""
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eng = SamsungEngine()
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wm, _mark = _compose(_ALPHA_NATIVE_WIDTH, int(_ALPHA_NATIVE_WIDTH * 1.33))
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out = eng.remove_watermark_reverse_alpha(wm)
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h, w = wm.shape[:2]
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assert np.array_equal(wm[: h // 2, w // 2 :], out[: h // 2, w // 2 :])
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def test_recovers_shifted_mark_on_texture(self):
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"""A real mark is re-rasterized a few px off its fixed slot, so removal must
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NCC-align to it (a too-tight locate box would let a corner-ward shift escape
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the search and leave a readable outline). Composes the real alpha SHIFTED on
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a known texture and asserts the texture is recovered."""
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eng = SamsungEngine()
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w, h = _ALPHA_NATIVE_WIDTH, int(_ALPHA_NATIVE_WIDTH * 1.33)
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at = _alpha_template()
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gw, gh = int(_ALPHA_WIDTH_FRAC * w), int(_ALPHA_HEIGHT_FRAC * w)
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ax = max(0, int(_ALPHA_MARGIN_LEFT_FRAC * w) + 9) # shift right of the fixed slot
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ay = h - int(_ALPHA_MARGIN_BOTTOM_FRAC * w) - gh - 7 # shift up
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amap = np.zeros((h, w), np.float32)
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amap[ay : ay + gh, ax : ax + gw] = cv2.resize(at, (gw, gh))
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a3 = amap[:, :, None]
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yy, xx = np.mgrid[0:h, 0:w].astype(np.float32)
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base = 120 + 40 * np.sin(xx / 90.0) + 30 * np.cos(yy / 70.0)
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bg = np.clip(np.stack([base, base * 0.95, base * 1.05], axis=-1), 0, 255)
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wm = (a3 * np.array(_ALPHA_LOGO_BGR, np.float32) + (1 - a3) * bg).clip(0, 255).astype(np.uint8)
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mark = amap > 0.15
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assert float(np.abs(wm.astype(np.float32)[mark] - bg[mark]).mean()) > 20 # mark clearly visible
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out = eng.remove_watermark_reverse_alpha(wm).astype(np.float32)
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assert float(np.abs(out[mark] - bg[mark]).mean()) < 10.0 # texture recovered, no outline
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class TestDegenerateAndChannelInputs:
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"""Removal must not crash on degenerate sizes or non-3-channel inputs."""
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@pytest.mark.parametrize(("w", "h"), [(2048, 1), (1, 2048), (2048, 8)])
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def test_wide_short_does_not_raise(self, w, h):
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eng = SamsungEngine()
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img = np.zeros((h, w, 3), np.uint8)
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out = eng.remove_watermark_reverse_alpha(img)
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assert out.shape == img.shape
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def test_grayscale_2d_does_not_raise(self):
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eng = SamsungEngine()
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gray = np.zeros((1448, 1086), np.uint8)
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out = eng.remove_watermark_reverse_alpha(gray)
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assert out.shape == (1448, 1086, 3)
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def test_bgra_4channel_does_not_raise(self):
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eng = SamsungEngine()
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bgra = np.zeros((1448, 1086, 4), np.uint8)
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out = eng.remove_watermark_reverse_alpha(bgra)
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assert out.shape == (1448, 1086, 3)
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