mirror of
https://github.com/wiltodelta/remove-ai-watermarks.git
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a46268f6eb
* Add cross-platform CI test matrix, PyPI classifiers CI: new test.yml runs lint (ubuntu) + a test matrix (ubuntu/macos/windows x py3.10/3.12, core+dev, GPU tests skip) on push to main and PRs, closing the gap where only the release publish.yml ran (ubuntu, no tests). Add PyPI classifiers (OS/Python/topic). README Tests badge, CLAUDE.md CI note. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * Make availability tests reflect installed deps, not assume gpu extra The new core+dev CI matrix has no diffusers, so the invisible-engine availability tests (asserting is_available() is True unconditionally) and the two mocked invisible CLI tests (whose command gates on is_available before the mock) failed. Assert availability == actual importability of torch+diffusers, and patch the CLI availability gate so the mocked-engine tests run regardless of the gpu extra. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
540 lines
21 KiB
Python
540 lines
21 KiB
Python
"""Tests for the CLI entry point."""
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from __future__ import annotations
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import json
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from typing import TYPE_CHECKING
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from unittest.mock import MagicMock, patch
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if TYPE_CHECKING:
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from pathlib import Path
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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 click.testing import CliRunner
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from PIL import Image
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from PIL.PngImagePlugin import PngInfo
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from remove_ai_watermarks.cli import main
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@pytest.fixture
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def runner():
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return CliRunner()
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@pytest.fixture
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def sample_png(tmp_path: Path) -> Path:
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"""Create a sample PNG for CLI testing."""
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# Seeded: an unseeded random corner can occasionally trip the Doubao
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# visible-mark detector, making `visible --mark auto` flaky.
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img = np.random.default_rng(0).integers(0, 255, (200, 200, 3), dtype=np.uint8)
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path = tmp_path / "input.png"
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cv2.imwrite(str(path), img)
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return path
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def _make_batch_dir(tmp_path: Path, count: int = 3) -> Path:
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"""Create a directory with test images for batch testing."""
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input_dir = tmp_path / "input"
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input_dir.mkdir()
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rng = np.random.default_rng(0)
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for i in range(count):
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img = rng.integers(0, 255, (100, 100, 3), dtype=np.uint8)
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cv2.imwrite(str(input_dir / f"img_{i}.png"), img)
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return input_dir
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def _make_batch_dir_with_metadata(tmp_path: Path, count: int = 3) -> Path:
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"""Create a directory with PNG images containing AI metadata."""
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input_dir = tmp_path / "input"
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input_dir.mkdir()
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for i in range(count):
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img = Image.new("RGB", (64, 64), color=(100 + i, 150, 200))
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pnginfo = PngInfo()
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pnginfo.add_text("parameters", f"Steps: 20, Sampler: Euler, img_{i}")
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pnginfo.add_text("prompt", "a test landscape")
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img.save(input_dir / f"img_{i}.png", pnginfo=pnginfo)
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return input_dir
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def _mock_invisible_engine():
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"""Create a mock InvisibleEngine that writes a copy of the input image."""
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def _mock_remove_watermark(image_path, output_path=None, **kwargs):
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out = output_path or image_path.with_stem(image_path.stem + "_clean")
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out.parent.mkdir(parents=True, exist_ok=True)
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img = Image.open(image_path)
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img.save(out)
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return out
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mock_engine = MagicMock()
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mock_engine.remove_watermark.side_effect = _mock_remove_watermark
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mock_cls = MagicMock(return_value=mock_engine)
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return mock_cls, mock_engine
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def _mock_invisible_engine_drops_alpha():
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"""Mock InvisibleEngine that mimics the real engine's BGR-only output path.
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The real diffusion-based engine reads with cv2.IMREAD_COLOR and writes a
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3-channel result. This mock simulates that so we can regression-test alpha
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preservation across the ``all`` pipeline.
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"""
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def _mock_remove_watermark(image_path, output_path=None, **kwargs):
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out = output_path or image_path.with_stem(image_path.stem + "_clean")
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out.parent.mkdir(parents=True, exist_ok=True)
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bgr = cv2.imread(str(image_path), cv2.IMREAD_COLOR)
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cv2.imwrite(str(out), bgr)
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return out
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mock_engine = MagicMock()
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mock_engine.remove_watermark.side_effect = _mock_remove_watermark
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mock_cls = MagicMock(return_value=mock_engine)
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return mock_cls, mock_engine
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class TestMainGroup:
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"""Tests for the top-level CLI group."""
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def test_help(self, runner):
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result = runner.invoke(main, ["--help"])
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assert result.exit_code == 0
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assert "Remove visible and invisible" in result.output
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def test_version(self, runner):
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result = runner.invoke(main, ["--version"])
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assert result.exit_code == 0
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assert "remove-ai-watermarks" in result.output
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assert "version" in result.output
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def test_no_command_shows_banner(self, runner):
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result = runner.invoke(main, [])
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assert result.exit_code == 0
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assert "Remove-AI-Watermarks" in result.output
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class TestVisibleCommand:
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"""Tests for the 'visible' subcommand."""
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def test_visible_help(self, runner):
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result = runner.invoke(main, ["visible", "--help"])
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assert result.exit_code == 0
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assert "visible AI watermark" in result.output
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assert "--mark" in result.output
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def test_visible_basic(self, runner, sample_png, tmp_path):
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output = tmp_path / "clean.png"
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result = runner.invoke(
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main,
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["visible", str(sample_png), "-o", str(output), "--no-detect"],
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)
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assert result.exit_code == 0
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assert output.exists()
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assert "Saved" in result.output
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def test_visible_default_output_name(self, runner, sample_png):
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result = runner.invoke(main, ["visible", str(sample_png), "--no-detect"])
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assert result.exit_code == 0
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expected = sample_png.with_stem(sample_png.stem + "_clean")
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assert expected.exists()
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def test_visible_no_inpaint(self, runner, sample_png, tmp_path):
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output = tmp_path / "clean.png"
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result = runner.invoke(
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main,
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[
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"visible",
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str(sample_png),
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"-o",
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str(output),
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"--no-inpaint",
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"--no-detect",
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],
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)
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assert result.exit_code == 0
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assert output.exists()
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def test_visible_no_detect(self, runner, sample_png, tmp_path):
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output = tmp_path / "clean.png"
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result = runner.invoke(
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main,
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["visible", str(sample_png), "-o", str(output), "--no-detect"],
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)
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assert result.exit_code == 0
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def test_visible_nonexistent_file(self, runner):
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result = runner.invoke(main, ["visible", "/nonexistent/file.png"])
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assert result.exit_code != 0
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def test_visible_preserves_rgba_transparency(self, runner, tmp_path):
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"""Visible removal on an RGBA PNG must keep the alpha channel,
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not silently flatten the image onto an opaque background.
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"""
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rgba = np.zeros((200, 200, 4), dtype=np.uint8)
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rgba[:, :, :3] = 200 # light grey foreground
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rgba[50:150, 50:150, 3] = 255 # opaque square in the middle, rest transparent
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src = tmp_path / "rgba_in.png"
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cv2.imwrite(str(src), rgba)
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output = tmp_path / "rgba_out.png"
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result = runner.invoke(
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main,
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["visible", str(src), "-o", str(output), "--no-detect"],
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)
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assert result.exit_code == 0, result.output
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assert output.exists()
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out = cv2.imread(str(output), cv2.IMREAD_UNCHANGED)
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assert out.ndim == 3, f"output is not 3D: shape={out.shape}"
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assert out.shape[2] == 4, f"output is not RGBA: shape={out.shape}"
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# The transparent corners must remain transparent.
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assert out[0, 0, 3] == 0
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assert out[199, 199, 3] == 0
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# The opaque centre remains opaque (the watermark region default is bottom-right,
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# which doesn't overlap the centre square at 200x200).
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assert out[100, 100, 3] == 255
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def test_visible_clears_alpha_in_watermark_region(self, runner, tmp_path):
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"""When inpainting an RGBA image, the watermark region must be cleared
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in the alpha channel so the sparkle area becomes transparent, not opaque-black.
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"""
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rgba = np.full((200, 200, 4), 255, dtype=np.uint8) # fully opaque white
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src = tmp_path / "rgba_full.png"
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cv2.imwrite(str(src), rgba)
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output = tmp_path / "rgba_cleared.png"
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result = runner.invoke(
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main,
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["visible", str(src), "-o", str(output), "--no-detect"],
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)
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assert result.exit_code == 0, result.output
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out = cv2.imread(str(output), cv2.IMREAD_UNCHANGED)
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assert out.shape[2] == 4
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# Default sparkle position is in the bottom-right; alpha there must be 0.
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from remove_ai_watermarks.gemini_engine import get_watermark_config
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cfg = get_watermark_config(200, 200)
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px, py = cfg.get_position(200, 200)
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size = cfg.logo_size
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assert out[py + size // 2, px + size // 2, 3] == 0, "alpha in the watermark region was not cleared"
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def test_visible_rgb_input_stays_rgb(self, runner, sample_png, tmp_path):
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"""Regression: a plain RGB PNG must NOT gain a spurious alpha channel."""
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output = tmp_path / "rgb_out.png"
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result = runner.invoke(
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main,
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["visible", str(sample_png), "-o", str(output), "--no-detect"],
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)
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assert result.exit_code == 0, result.output
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out = cv2.imread(str(output), cv2.IMREAD_UNCHANGED)
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assert out.ndim == 3, f"output is not 3D: shape={out.shape}"
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assert out.shape[2] == 3, f"RGB input produced non-RGB output: shape={out.shape}"
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class TestInvisibleCommand:
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"""Tests for the 'invisible' subcommand."""
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def test_invisible_help(self, runner):
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result = runner.invoke(main, ["invisible", "--help"])
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assert result.exit_code == 0
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assert "invisible" in result.output.lower()
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def test_invisible_basic(self, runner, sample_png, tmp_path):
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mock_cls, mock_engine = _mock_invisible_engine()
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output = tmp_path / "clean.png"
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with (
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patch("remove_ai_watermarks.invisible_engine.is_available", return_value=True),
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patch("remove_ai_watermarks.cli.InvisibleEngine", mock_cls, create=True),
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patch("remove_ai_watermarks.invisible_engine.InvisibleEngine", mock_cls),
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):
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result = runner.invoke(
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main,
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["invisible", str(sample_png), "-o", str(output)],
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)
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assert result.exit_code == 0, result.output
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assert output.exists()
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mock_engine.remove_watermark.assert_called_once()
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def test_invisible_default_output(self, runner, sample_png):
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mock_cls, _mock_engine = _mock_invisible_engine()
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with (
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patch("remove_ai_watermarks.invisible_engine.is_available", return_value=True),
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patch("remove_ai_watermarks.cli.InvisibleEngine", mock_cls, create=True),
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patch("remove_ai_watermarks.invisible_engine.InvisibleEngine", mock_cls),
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):
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result = runner.invoke(main, ["invisible", str(sample_png)])
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assert result.exit_code == 0, result.output
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expected = sample_png.with_stem(sample_png.stem + "_clean")
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assert expected.exists()
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def test_invisible_nonexistent_file(self, runner):
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result = runner.invoke(main, ["invisible", "/nonexistent/file.png"])
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assert result.exit_code != 0
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class TestAllCommand:
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"""Tests for the 'all' subcommand (full pipeline)."""
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def test_all_help(self, runner):
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result = runner.invoke(main, ["all", "--help"])
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assert result.exit_code == 0
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assert "visible" in result.output.lower()
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def test_all_basic(self, runner, sample_png, tmp_path):
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mock_cls, _mock_engine = _mock_invisible_engine()
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output = tmp_path / "clean.png"
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with (
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patch("remove_ai_watermarks.cli.InvisibleEngine", mock_cls, create=True),
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patch("remove_ai_watermarks.invisible_engine.InvisibleEngine", mock_cls),
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):
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result = runner.invoke(
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main,
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["all", str(sample_png), "-o", str(output)],
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)
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assert result.exit_code == 0, result.output
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assert output.exists()
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def test_all_nonexistent_file(self, runner):
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result = runner.invoke(main, ["all", "/nonexistent/file.png"])
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assert result.exit_code != 0
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def test_all_preserves_rgba_across_invisible_step(self, runner, tmp_path):
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"""Regression: ``all`` must keep transparency even when the invisible
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step writes a 3-channel result (as the real diffusion engine does).
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"""
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rgba = np.zeros((200, 200, 4), dtype=np.uint8)
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rgba[:, :, :3] = 200
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rgba[50:150, 50:150, 3] = 255 # opaque square; corners transparent
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src = tmp_path / "rgba_in.png"
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cv2.imwrite(str(src), rgba)
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output = tmp_path / "rgba_out.png"
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mock_cls, _engine = _mock_invisible_engine_drops_alpha()
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with (
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patch("remove_ai_watermarks.cli.InvisibleEngine", mock_cls, create=True),
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patch("remove_ai_watermarks.invisible_engine.InvisibleEngine", mock_cls),
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patch("remove_ai_watermarks.cli.invisible_available", return_value=True, create=True),
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patch("remove_ai_watermarks.invisible_engine.is_available", return_value=True),
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):
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result = runner.invoke(main, ["all", str(src), "-o", str(output)])
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assert result.exit_code == 0, result.output
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out = cv2.imread(str(output), cv2.IMREAD_UNCHANGED)
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assert out.ndim == 3, f"output not 3D: shape={out.shape}"
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assert out.shape[2] == 4, f"output is not RGBA: shape={out.shape}"
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assert out[0, 0, 3] == 0
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assert out[100, 100, 3] == 255
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class TestMetadataCommand:
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"""Tests for the 'metadata' subcommand."""
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def test_metadata_help(self, runner):
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result = runner.invoke(main, ["metadata", "--help"])
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assert result.exit_code == 0
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def test_metadata_check_clean(self, runner, tmp_clean_png):
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result = runner.invoke(main, ["metadata", str(tmp_clean_png), "--check"])
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assert result.exit_code == 0
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assert "No AI metadata" in result.output
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def test_metadata_check_ai(self, runner, tmp_png_with_ai_metadata):
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result = runner.invoke(main, ["metadata", str(tmp_png_with_ai_metadata), "--check"])
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assert result.exit_code == 0
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assert "AI metadata detected" in result.output
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def test_metadata_remove(self, runner, tmp_png_with_ai_metadata, tmp_path):
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output = tmp_path / "stripped.png"
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result = runner.invoke(
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main,
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[
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"metadata",
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str(tmp_png_with_ai_metadata),
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"--remove",
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"-o",
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str(output),
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],
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)
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assert result.exit_code == 0
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assert "stripped" in result.output
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class TestIdentifyCommand:
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"""Tests for the 'identify' subcommand."""
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def test_identify_help(self, runner):
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result = runner.invoke(main, ["identify", "--help"])
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assert result.exit_code == 0
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def test_identify_clean_png(self, runner, tmp_clean_png):
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result = runner.invoke(main, ["identify", str(tmp_clean_png), "--no-visible"])
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assert result.exit_code == 0
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assert "unknown" in result.output
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def test_identify_unknown_explains_why(self, runner, tmp_clean_png):
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# An unknown verdict must explain itself inline (issue #22: users read a bare
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# "unknown" as the tool being broken) rather than only in the caveats section.
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result = runner.invoke(main, ["identify", str(tmp_clean_png), "--no-visible"])
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assert result.exit_code == 0
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assert "No locally-readable AI signal found" in result.output
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assert "not the same as 'clean'" in result.output
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def test_identify_ai_png_reports_platform(self, runner, tmp_png_with_ai_metadata):
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result = runner.invoke(main, ["identify", str(tmp_png_with_ai_metadata), "--no-visible"])
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assert result.exit_code == 0
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assert "AI-generated" in result.output
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assert "Stable Diffusion" in result.output
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def test_identify_json_is_valid(self, runner, tmp_png_with_ai_metadata):
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result = runner.invoke(main, ["identify", str(tmp_png_with_ai_metadata), "--no-visible", "--json"])
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assert result.exit_code == 0
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payload = json.loads(result.output)
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assert payload["is_ai_generated"] is True
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assert payload["confidence"] == "high"
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def test_identify_nonexistent_file(self, runner):
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result = runner.invoke(main, ["identify", "/nonexistent/file.png"])
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assert result.exit_code != 0
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class TestBatchCommand:
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"""Tests for the 'batch' subcommand."""
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def test_batch_help(self, runner):
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result = runner.invoke(main, ["batch", "--help"])
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assert result.exit_code == 0
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def test_batch_empty_dir(self, runner, tmp_path):
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empty_dir = tmp_path / "empty"
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empty_dir.mkdir()
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result = runner.invoke(main, ["batch", str(empty_dir)])
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assert result.exit_code == 0
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assert "No supported images" in result.output
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def test_batch_visible_mode(self, runner, tmp_path):
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input_dir = _make_batch_dir(tmp_path)
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output_dir = tmp_path / "output"
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result = runner.invoke(
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main,
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["batch", str(input_dir), "-o", str(output_dir), "--mode", "visible"],
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)
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assert result.exit_code == 0
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assert "3 processed" in result.output
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assert output_dir.exists()
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assert len(list(output_dir.glob("*.png"))) == 3
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def test_batch_metadata_mode(self, runner, tmp_path):
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input_dir = _make_batch_dir_with_metadata(tmp_path)
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output_dir = tmp_path / "output"
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result = runner.invoke(
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main,
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["batch", str(input_dir), "-o", str(output_dir), "--mode", "metadata"],
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)
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assert result.exit_code == 0
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assert "3 processed" in result.output
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assert output_dir.exists()
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assert len(list(output_dir.glob("*.png"))) == 3
|
|
# Verify AI metadata was stripped
|
|
for out_img in output_dir.glob("*.png"):
|
|
with Image.open(out_img) as img:
|
|
assert "parameters" not in img.info
|
|
|
|
def test_batch_invisible_mode(self, runner, tmp_path):
|
|
input_dir = _make_batch_dir(tmp_path)
|
|
output_dir = tmp_path / "output"
|
|
mock_cls, _mock_engine = _mock_invisible_engine()
|
|
with (
|
|
patch("remove_ai_watermarks.cli.InvisibleEngine", mock_cls, create=True),
|
|
patch("remove_ai_watermarks.invisible_engine.InvisibleEngine", mock_cls),
|
|
patch("remove_ai_watermarks.cli.invisible_available", return_value=True, create=True),
|
|
patch("remove_ai_watermarks.invisible_engine.is_available", return_value=True),
|
|
):
|
|
result = runner.invoke(
|
|
main,
|
|
["batch", str(input_dir), "-o", str(output_dir), "--mode", "invisible"],
|
|
)
|
|
assert result.exit_code == 0, result.output
|
|
assert "3 processed" in result.output
|
|
|
|
def test_batch_all_mode(self, runner, tmp_path):
|
|
input_dir = _make_batch_dir(tmp_path)
|
|
output_dir = tmp_path / "output"
|
|
mock_cls, _mock_engine = _mock_invisible_engine()
|
|
with (
|
|
patch("remove_ai_watermarks.cli.InvisibleEngine", mock_cls, create=True),
|
|
patch("remove_ai_watermarks.invisible_engine.InvisibleEngine", mock_cls),
|
|
patch("remove_ai_watermarks.cli.invisible_available", return_value=True, create=True),
|
|
patch("remove_ai_watermarks.invisible_engine.is_available", return_value=True),
|
|
):
|
|
result = runner.invoke(
|
|
main,
|
|
["batch", str(input_dir), "-o", str(output_dir), "--mode", "all"],
|
|
)
|
|
assert result.exit_code == 0, result.output
|
|
assert "3 processed" in result.output
|
|
|
|
def test_batch_all_mode_preserves_rgba(self, runner, tmp_path):
|
|
"""Regression: batch ``all`` must keep transparency across the
|
|
alpha-dropping invisible step (mirrors test_all_preserves_rgba_...).
|
|
"""
|
|
input_dir = tmp_path / "input"
|
|
input_dir.mkdir()
|
|
rgba = np.zeros((200, 200, 4), dtype=np.uint8)
|
|
rgba[:, :, :3] = 200
|
|
rgba[50:150, 50:150, 3] = 255
|
|
cv2.imwrite(str(input_dir / "rgba.png"), rgba)
|
|
|
|
output_dir = tmp_path / "output"
|
|
mock_cls, _engine = _mock_invisible_engine_drops_alpha()
|
|
with (
|
|
patch("remove_ai_watermarks.cli.InvisibleEngine", mock_cls, create=True),
|
|
patch("remove_ai_watermarks.invisible_engine.InvisibleEngine", mock_cls),
|
|
patch("remove_ai_watermarks.cli.invisible_available", return_value=True, create=True),
|
|
patch("remove_ai_watermarks.invisible_engine.is_available", return_value=True),
|
|
):
|
|
result = runner.invoke(
|
|
main,
|
|
["batch", str(input_dir), "-o", str(output_dir), "--mode", "all"],
|
|
)
|
|
assert result.exit_code == 0, result.output
|
|
|
|
out = cv2.imread(str(output_dir / "rgba.png"), cv2.IMREAD_UNCHANGED)
|
|
assert out.ndim == 3, f"output not 3D: shape={out.shape}"
|
|
assert out.shape[2] == 4, f"output is not RGBA: shape={out.shape}"
|
|
assert out[0, 0, 3] == 0
|
|
assert out[100, 100, 3] == 255
|
|
|
|
def test_batch_default_output_dir(self, runner, tmp_path):
|
|
input_dir = _make_batch_dir(tmp_path)
|
|
result = runner.invoke(
|
|
main,
|
|
["batch", str(input_dir), "--mode", "visible"],
|
|
)
|
|
assert result.exit_code == 0
|
|
expected_dir = tmp_path / "input_clean"
|
|
assert expected_dir.exists()
|
|
|
|
|
|
class TestGpuHintMarkup:
|
|
"""The GPU-extra install hint must survive rich markup (the ``[gpu]`` token
|
|
is otherwise parsed as a style tag and silently dropped)."""
|
|
|
|
def test_invisible_install_hint_keeps_gpu_extra(self, runner, sample_png):
|
|
with patch("remove_ai_watermarks.invisible_engine.is_available", return_value=False):
|
|
result = runner.invoke(main, ["invisible", str(sample_png)])
|
|
assert result.exit_code != 0
|
|
assert "remove-ai-watermarks[gpu]" in result.output
|
|
|
|
def test_all_install_hint_keeps_gpu_extra(self, runner, sample_png):
|
|
# The `all` pipeline skips the invisible step with a warning that carries
|
|
# the same hint; it must keep the [gpu] extra too.
|
|
with patch("remove_ai_watermarks.invisible_engine.is_available", return_value=False):
|
|
result = runner.invoke(main, ["all", str(sample_png)])
|
|
assert "remove-ai-watermarks[gpu]" in result.output
|