remove-ai-watermarks/tests/test_invisible_engine.py

"""Tests for the invisible watermark engine (unit tests, no GPU required)."""

from __future__ import annotations

from types import SimpleNamespace

from PIL import Image

from remove_ai_watermarks.invisible_engine import InvisibleEngine, _target_size, is_available


class TestIsAvailable:
    """Tests for dependency checking."""

    def test_returns_bool(self):
        result = is_available()
        assert isinstance(result, bool)

    def test_the_module_list_includes_the_face_stage_runtime(self):
        """diffsynth is part of the answer, not an optional upgrade.

        Both profiles repair faces with the DiffSynth Z-Image stage, so a
        torch+diffusers-only environment used to clear this gate and then die there.
        The discriminating guard -- that this gate and the remover's precondition
        BOTH close when any one module is missing -- lives in
        ``test_platform.py::TestAvailability``; comparing ``is_available()`` to a
        tuple derived from itself passes on every host and proves nothing.
        """
        from remove_ai_watermarks._internal.watermark_profiles import REMOVAL_MODULES

        assert "diffsynth" in REMOVAL_MODULES


class TestInvisibleEngineInit:
    """Tests for InvisibleEngine construction (no GPU required)."""

    def test_preload_forwards_global_only(self):
        engine = object.__new__(InvisibleEngine)
        engine._remover = SimpleNamespace(preload=lambda **kwargs: setattr(engine, "_preload_kwargs", kwargs))

        engine.preload(global_only=True)

        assert engine._preload_kwargs == {"global_only": True}


class TestNativeOutputSize:
    """Model-side latent-grid rounding must not change the public output size."""

    def test_no_polish_restores_native_non_multiple_of_eight_size(self, tmp_path):
        engine = object.__new__(InvisibleEngine)

        def _remove_watermark(image_path, output_path=None, **_kwargs):
            out = output_path or image_path.with_stem(image_path.stem + "_clean")
            # Model-side latent-grid rounding: 18px becomes 16px.
            Image.open(image_path).crop((0, 0, 24, 16)).save(out)
            return out

        engine._remover = SimpleNamespace(remove_watermark=_remove_watermark, model_profile="qwen-zimage")
        engine._progress_callback = None
        src = tmp_path / "src.png"
        out = tmp_path / "out.png"
        Image.new("RGB", (24, 18), (128, 128, 128)).save(src)

        engine.remove_watermark(src, out, adaptive_polish=False)

        assert Image.open(out).size == (24, 18)


class TestTargetSize:
    """Regression guard for the native-resolution decision (issues #10 / #15).

    max_resolution=0 must NOT downscale -- the forced downscale->upscale
    round-trip was the quality loss in #10, and downscaling at all let SynthID
    survive in #15 (the native SDXL pass at strength ~0.05 is what defeats it).
    """

    def test_native_default_no_downscale(self):
        # The default (0) means native resolution: no resize, regardless of size.
        assert _target_size(4096, 4096, 0) is None
        assert _target_size(123, 456, 0) is None

    def test_negative_cap_treated_as_native(self):
        assert _target_size(4096, 4096, -1) is None

    def test_cap_below_long_side_downscales(self):
        # 2000x1000, cap 1024 -> long side scaled to 1024, aspect preserved.
        assert _target_size(2000, 1000, 1024) == (1024, 512)

    def test_cap_uses_long_side_for_portrait(self):
        # Portrait: height is the long side, so it drives the ratio.
        assert _target_size(1000, 2000, 1024) == (512, 1024)

    def test_cap_at_or_above_long_side_no_downscale(self):
        # Already within the cap (and exactly equal) -> no resize.
        assert _target_size(800, 600, 1024) is None
        assert _target_size(1024, 768, 1024) is None

    def test_integer_truncation_matches_pil_call_site(self):
        # 1254x1254 (the gpt-image sample) capped at 1000: int(1254*1000/1254)=1000.
        assert _target_size(1254, 1254, 1000) == (1000, 1000)
        # Non-divisible ratio truncates toward zero like int() at the call site.
        assert _target_size(1000, 333, 500) == (500, 166)

    def test_extreme_aspect_ratio_clamps_short_side_to_one(self):
        # 5000x3 capped at 1024: int(3 * 1024/5000) = 0 would crash resize();
        # the short side must clamp to 1, never 0.
        assert _target_size(5000, 3, 1024) == (1024, 1)
        assert _target_size(3, 5000, 1024) == (1, 1024)

    def test_a_small_input_is_left_at_native_size(self):
        """No minimum-resolution floor: only the cap can move geometry."""
        assert _target_size(381, 512, 0) is None
        assert _target_size(381, 512, 4096) is None


class TestEngineConstructsWithoutAModelId:
    """Plain construction must reach the remover, and must not name a model.

    The engine used to take a ``model_id`` and substitute the SDXL default for None.
    Once the remover tightened its "you may not override the fixed stack" check to
    ``is not None``, that substitution made EVERY construction raise -- and no test
    saw it, because the library tests build WatermarkRemover directly while the engine
    tests mock it. A deployed Modal worker caught it instead. The parameter is gone on
    both sides now, so guard the property that broke: a default construction reaches
    the remover, carrying no model at all.
    """

    def test_default_construction_names_no_model(self):
        from unittest.mock import patch

        import remove_ai_watermarks.invisible_engine as engine_module

        with patch("remove_ai_watermarks._internal.watermark_remover.WatermarkRemover") as remover:
            engine_module.InvisibleEngine(pipeline="qwen-zimage")
        assert remover.call_count == 1
        assert "model_id" not in remover.call_args.kwargs

    def test_a_model_id_is_not_accepted(self):
        import pytest

        import remove_ai_watermarks.invisible_engine as engine_module

        with pytest.raises(TypeError):
            engine_module.InvisibleEngine(model_id="org/custom", pipeline="qwen-zimage")  # type: ignore[call-arg]


class TestEngineResolvesThePolishPerProfile:
    """The engine, not the CLI, turns an unset adaptive_polish into the profile default.

    This is the change that stopped a library caller and a CLI caller on one profile
    from producing different pixels, and it had no test: rebinding
    ``resolve_adaptive_polish`` to ``bool(value)`` -- exactly the pre-commit behaviour --
    left the whole suite green.
    """

    @staticmethod
    def _engine(profile: str):
        from unittest.mock import MagicMock

        engine = object.__new__(InvisibleEngine)
        engine._progress_callback = None
        engine._remover = MagicMock(model_profile=profile)
        return engine

    def _polish_used(self, profile: str, requested, tmp_path, monkeypatch) -> bool:
        seen: list[bool] = []
        monkeypatch.setattr(
            "remove_ai_watermarks.humanizer.adaptive_polish",
            lambda out, ref, seed=None: (seen.append(True), out)[1],
        )
        src = tmp_path / f"{profile}_{requested}.png"
        Image.new("RGB", (32, 32), (90, 120, 150)).save(src)
        engine = self._engine(profile)
        engine._remover.remove_watermark.side_effect = lambda **kw: (
            Image.open(kw["image_path"]).save(kw["output_path"]),
            kw["output_path"],
        )[1]
        engine.remove_watermark(src, tmp_path / f"out_{profile}_{requested}.png", adaptive_polish=requested)
        return bool(seen)

    def test_unset_follows_the_profile_not_the_signature_default(self, tmp_path, monkeypatch):
        assert self._polish_used("qwen-zimage", None, tmp_path, monkeypatch) is False
        assert self._polish_used("sdxl-zimage", None, tmp_path, monkeypatch) is True

    def test_an_explicit_value_still_wins_on_both_profiles(self, tmp_path, monkeypatch):
        assert self._polish_used("qwen-zimage", True, tmp_path, monkeypatch) is True
        assert self._polish_used("sdxl-zimage", False, tmp_path, monkeypatch) is False