mirror of
https://github.com/wiltodelta/remove-ai-watermarks.git
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107 lines
4.0 KiB
Python
107 lines
4.0 KiB
Python
"""Contracts for the portable OpenAI/Google source-pattern runtime."""
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from __future__ import annotations
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from hashlib import sha256
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from typing import TYPE_CHECKING
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import numpy as np
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import pytest
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from PIL import Image, PngImagePlugin
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from remove_ai_watermarks import source_classify_v2 as model
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if TYPE_CHECKING:
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from pathlib import Path
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def _synthetic_weights(path: Path, *, gate: float) -> None:
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zero_mean = np.zeros((256, 256, 3), dtype=np.complex64)
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zero_precision = np.zeros((256, 256, 3), dtype=np.float32)
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unit = np.zeros((992, 992), dtype=np.float32)
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unit[0, 0] = 1
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fields: dict[str, np.ndarray] = {"schema": np.asarray(model.MODEL_SCHEMA)}
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for name in model._FILTER_NAMES:
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fields[f"{name}_mean"] = zero_mean
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fields[f"{name}_precision"] = zero_precision
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for route in model.ROUTES:
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fields[f"openai_{route}_unit"] = unit
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limits = dict.fromkeys(model._THRESHOLD_NAMES, 1.0)
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limits["r183_openai_gate"] = gate
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limits.update({f"r163_{group}": -0.5 for group in model.GROUPS})
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fields.update({f"threshold_{name}": np.asarray(value, dtype=np.float64) for name, value in limits.items()})
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np.savez_compressed(path, **fields)
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def test_r163_gate_changes_real_prediction(tmp_path: Path, monkeypatch: pytest.MonkeyPatch) -> None:
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image = tmp_path / "photo.png"
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Image.new("RGB", (512, 512), (80, 110, 145)).save(image)
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blocked = tmp_path / "blocked.npz"
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allowed = tmp_path / "allowed.npz"
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_synthetic_weights(blocked, gate=0.5)
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_synthetic_weights(allowed, gate=-0.5)
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def predict(path: Path) -> model.ImageSourceClassification:
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monkeypatch.setenv(model.WEIGHTS_ENV, str(path))
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monkeypatch.setattr(model, "MODEL_SHA256", sha256(path.read_bytes()).hexdigest())
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return model.classify_image_source(image)
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no_gate = predict(blocked)
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with_gate = predict(allowed)
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assert no_gate.label == "unknown"
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assert no_gate.reason == "abstained"
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assert with_gate.label == "openai"
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assert with_gate.reason == "classified"
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assert with_gate.watermark_truth == "unknown"
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def test_top_level_api_is_lazy_and_points_to_new_runtime() -> None:
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import remove_ai_watermarks as raiw
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assert raiw.classify_image_source is model.classify_image_source
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assert raiw.ImageSourceClassification is model.ImageSourceClassification
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assert model.PROVIDERS == ("openai", "google")
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assert len(model.WEIGHTS_REVISION) == 40
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assert all(character in "0123456789abcdef" for character in model.WEIGHTS_REVISION)
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def test_metadata_does_not_change_pixel_decision(tmp_path: Path, monkeypatch: pytest.MonkeyPatch) -> None:
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weights = tmp_path / model.MODEL_FILE
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_synthetic_weights(weights, gate=-0.5)
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monkeypatch.setenv(model.WEIGHTS_ENV, str(weights))
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monkeypatch.setattr(model, "MODEL_SHA256", sha256(weights.read_bytes()).hexdigest())
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pixels = Image.new("RGB", (512, 512), (80, 110, 145))
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clean = tmp_path / "clean.png"
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tagged = tmp_path / "tagged.png"
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pixels.save(clean)
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metadata = PngImagePlugin.PngInfo()
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metadata.add_text("Comment", "arbitrary metadata")
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pixels.save(tagged, pnginfo=metadata)
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first = model.classify_image_source(clean)
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second = model.classify_image_source(tagged)
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assert first.label == second.label == "openai"
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assert first.scores == second.scores
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def test_rejects_wrong_artifact_hash(tmp_path: Path) -> None:
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weights = tmp_path / model.MODEL_FILE
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_synthetic_weights(weights, gate=0.5)
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with pytest.raises(ValueError, match="SHA-256 mismatch"):
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model._load_model(weights, "0" * 64)
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def test_small_image_abstains_without_watermark_claim(tmp_path: Path, monkeypatch: pytest.MonkeyPatch) -> None:
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monkeypatch.setattr(model, "_model_path", lambda: pytest.fail("small image loaded weights"))
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image = tmp_path / "small.png"
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Image.new("RGB", (128, 128), "white").save(image)
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result = model.classify_image_source(image)
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assert result.label == "unknown"
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assert result.reason == "feature_unavailable"
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assert result.watermark_truth == "unknown"
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