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https://github.com/wiltodelta/remove-ai-watermarks.git
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334 lines
14 KiB
Python
334 lines
14 KiB
Python
"""Tests for the portable metadata record.
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The contract is one property: a verdict built from the record equals the verdict
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built from the file. Everything here exists to pin that, or to pin a placement the
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record could plausibly drop.
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"""
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from __future__ import annotations
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import json
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import struct
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import zlib
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from pathlib import Path
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import numpy as np
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import pytest
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from PIL import Image
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from remove_ai_watermarks.identify import (
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PROVENANCE_REPORT_SCHEMA_VERSION,
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ProvenanceReport,
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evidence_from_metadata_record,
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identify,
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identify_from_evidence,
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identify_metadata_record,
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)
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from remove_ai_watermarks.metadata_record import (
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HEAD_WINDOW,
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METADATA_RECORD_SCHEMA_VERSION,
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METADATA_RECORD_TYPE,
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collect_metadata_record,
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)
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FIXTURES = Path(__file__).resolve().parent.parent / "data" / "fixtures" / "provenance"
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COMPARED = ("is_ai_generated", "platform", "confidence", "ai_source_kind", "ai_from_metadata")
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def _verdict_via_record(path: Path) -> ProvenanceReport:
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"""The contractor's path: collect, serialize, judge -- without the file."""
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record = json.loads(json.dumps(collect_metadata_record(path)))
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return identify_metadata_record(record, path=path)
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def _assert_same_verdict(path: Path) -> None:
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via_record = _verdict_via_record(path)
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via_file = identify(path, check_visible=False, check_invisible=False)
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for field in COMPARED:
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assert getattr(via_record, field) == getattr(via_file, field), field
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assert sorted(s.name for s in via_record.signals) == sorted(s.name for s in via_file.signals)
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assert sorted(via_record.watermarks) == sorted(via_file.watermarks)
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def _noise_png(path: Path, size: tuple[int, int] = (700, 700)) -> Path:
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"""A PNG whose IDAT is incompressible, so the file exceeds the head window."""
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rng = np.random.default_rng(0)
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Image.fromarray(rng.integers(0, 255, (size[1], size[0], 3), dtype=np.uint8)).save(path)
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return path
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def _insert_png_chunk(path: Path, chunk_type: bytes, payload: bytes) -> None:
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"""Splice a chunk in just before IEND, i.e. AFTER the whole pixel stream."""
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data = path.read_bytes()
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end = data.rindex(b"IEND") - 4
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chunk = struct.pack(">I", len(payload)) + chunk_type + payload
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chunk += struct.pack(">I", zlib.crc32(chunk_type + payload) & 0xFFFFFFFF)
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path.write_bytes(data[:end] + chunk + data[end:])
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class TestRecordReproducesTheFileVerdict:
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"""The whole point of the record. Every tracked provenance fixture is compared,
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which covers C2PA, the China TC260 label, the xAI EXIF pair and the IPTC tag."""
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@pytest.mark.skipif(not FIXTURES.is_dir(), reason="provenance fixtures not present")
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@pytest.mark.parametrize("name", sorted(p.name for p in FIXTURES.iterdir()) if FIXTURES.is_dir() else [])
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def test_fixture(self, name: str):
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_assert_same_verdict(FIXTURES / name)
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@pytest.mark.skipif(not FIXTURES.is_dir(), reason="provenance fixtures not present")
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def test_the_fixtures_actually_exercise_several_signals(self):
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"""Guards the test above: if the fixture set ever narrows to one signal
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family, equality across it stops meaning much."""
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found = {
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signal.name
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for path in FIXTURES.iterdir()
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for signal in identify(path, check_visible=False, check_invisible=False).signals
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}
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assert len(found) >= 4, found
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class TestPlacementsTheRecordCouldDrop:
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def test_a_trailer_after_eoi_survives(self, tmp_path: Path):
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"""Samsung Galaxy AI appends its marker past the JPEG EOI, and the value it is
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gated on can sit further back still. A record that stopped at the last
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structural marker would report no signal at all."""
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path = tmp_path / "edited.jpg"
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Image.fromarray(np.zeros((64, 64, 3), dtype=np.uint8)).save(path, "JPEG")
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with path.open("ab") as handle:
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handle.write(b'PhotoEditor_Re_Edit_Data{"genAIType":17}')
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assert identify(path, check_visible=False, check_invisible=False).confidence == "medium"
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_assert_same_verdict(path)
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def test_a_metadata_chunk_past_the_head_window_survives(self, tmp_path: Path):
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"""A PNG encoder may put the label chunk after the pixels. The file is larger
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than the record's head window, so only the seek-past-IDAT reader finds it."""
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path = _noise_png(tmp_path / "late.png")
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assert path.stat().st_size > HEAD_WINDOW
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# An XMP packet in the namespaced TC260 form, which is how the label travels
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# when it is not a bare ``AIGC`` keyword chunk.
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label = json.dumps({"Label": "1", "ContentProducer": "001191110102MACQD9K64010000"})
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xmp = (
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b'<x:xmpmeta xmlns:x="adobe:ns:meta/"><rdf:RDF><rdf:Description '
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b'xmlns:TC260="http://www.tc260.org.cn/ns/AIGC/1.0/"><TC260:AIGC>'
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+ label.encode()
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+ b"</TC260:AIGC></rdf:Description></rdf:RDF></x:xmpmeta>"
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)
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_insert_png_chunk(path, b"iTXt", b"XML:com.adobe.xmp\x00\x00\x00\x00\x00" + xmp)
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assert "aigc" in {s.name for s in identify(path, check_visible=False, check_invisible=False).signals}
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_assert_same_verdict(path)
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def test_an_exif_pair_survives(self, tmp_path: Path):
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"""xAI is recognized from an (ImageDescription, Artist) PAIR, and both are read
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by tag NAME. A record carrying only raw bytes loses it."""
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import piexif
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path = tmp_path / "grok.jpg"
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Image.fromarray(np.zeros((64, 64, 3), dtype=np.uint8)).save(path, "JPEG")
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exif = {
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"0th": {
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piexif.ImageIFD.ImageDescription: b"Signature: " + b"A" * 80,
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piexif.ImageIFD.Artist: b"3f2504e0-4f89-11d3-9a0c-0305e82c3301",
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}
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}
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piexif.insert(piexif.dump(exif), str(path))
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assert "xai_signature" in {s.name for s in identify(path, check_visible=False, check_invisible=False).signals}
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_assert_same_verdict(path)
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class TestRecordShape:
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def test_the_record_survives_json(self, tmp_path: Path):
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record = collect_metadata_record(_noise_png(tmp_path / "plain.png"))
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assert json.loads(json.dumps(record, allow_nan=False))["container"] == "png"
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assert record["schema_version"] == METADATA_RECORD_SCHEMA_VERSION == 1
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assert record["record_type"] == METADATA_RECORD_TYPE == "provenance_metadata"
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@pytest.mark.parametrize("keep_version", [True, False])
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def test_transport_filename_is_not_evidence(self, tmp_path: Path, keep_version: bool):
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"""The path labels a record; detector tokens in it do not describe pixels."""
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path = tmp_path / "jumb-c2pa-OpenAI-trainedAlgorithmicMedia.jpg"
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Image.fromarray(np.zeros((64, 64, 3), dtype=np.uint8)).save(path, "JPEG")
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record = collect_metadata_record(path)
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if not keep_version:
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record.pop("schema_version")
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record.pop("record_type")
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report = identify_metadata_record(record, path=path)
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assert report.is_ai_generated is None
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assert report.platform is None
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assert report.confidence == "none"
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def test_pixels_are_not_carried(self, tmp_path: Path):
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"""The reason the record walks regions instead of shipping the head: a record
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that carried the pixel stream would be the size of the image."""
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path = _noise_png(tmp_path / "big.png", size=(1200, 1200))
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record = collect_metadata_record(path)
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idat = path.read_bytes()
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start = idat.index(b"IDAT") + 4
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assert idat[start : start + 512] not in json.dumps(record).encode()
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assert len(json.dumps(record)) < path.stat().st_size // 10
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def test_an_unreadable_container_still_yields_a_record(self, tmp_path: Path):
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path = tmp_path / "junk.bin"
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path.write_bytes(b"\x00\x01\x02not an image at all" * 100)
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record = collect_metadata_record(path)
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assert record["container"] == "unknown"
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assert json.dumps(record) # serializable, and no exception on the way here
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_assert_same_verdict(path)
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def test_a_missing_file_does_not_raise(self, tmp_path: Path):
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"""Collection runs over whatever a caller hands it, including a path that
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vanished between listing and reading."""
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record = collect_metadata_record(tmp_path / "gone.png")
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assert record["container"] == "unknown"
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assert record["metadata_base64"] == ""
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assert record["status"] == "error"
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assert record["issues"] == [{"stage": "source", "code": "unavailable"}]
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def test_unknown_record_schema_is_rejected(self, tmp_path: Path):
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path = _noise_png(tmp_path / "plain.png")
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record = collect_metadata_record(path)
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record["schema_version"] = 2
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with pytest.raises(ValueError, match="Unsupported provenance metadata schema"):
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identify_metadata_record(record, path=path)
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@pytest.mark.parametrize("schema_version", [True, 1.0, "1", None])
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def test_native_record_schema_requires_the_integer_one(self, tmp_path: Path, schema_version: object):
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path = _noise_png(tmp_path / "plain.png")
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record = collect_metadata_record(path)
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record["schema_version"] = schema_version
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with pytest.raises(ValueError, match="Unsupported provenance metadata schema"):
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identify_metadata_record(record, path=path)
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@pytest.mark.parametrize("status", [None, "partial", "unknown", True])
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def test_native_record_requires_complete_collection_status(self, tmp_path: Path, status: object):
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path = _noise_png(tmp_path / "plain.png")
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record = collect_metadata_record(path)
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if status is None:
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record.pop("status")
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else:
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record["status"] = status
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with pytest.raises(ValueError, match="collection status"):
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identify_metadata_record(record, path=path)
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@pytest.mark.parametrize("schema_version", [2, True, 1.0])
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def test_collection_rejects_unsupported_output_schema_before_reading(self, tmp_path: Path, schema_version: object):
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with pytest.raises(ValueError, match="Unsupported provenance metadata schema"):
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collect_metadata_record(
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tmp_path / "missing.png",
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schema_version=schema_version, # type: ignore[arg-type]
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)
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def test_broad_forensic_record_is_not_detector_input(self, tmp_path: Path):
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path = _noise_png(tmp_path / "plain.png")
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with pytest.raises(ValueError, match="Unsupported metadata record type"):
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identify_metadata_record(
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{"record_type": "forensic_metadata", "schema_version": 1},
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path=path,
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)
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def test_failed_collection_cannot_be_judged_as_an_unknown_image(self, tmp_path: Path):
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path = tmp_path / "missing.png"
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with pytest.raises(ValueError, match="collection failed"):
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identify_metadata_record(collect_metadata_record(path), path=path)
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class TestReportTransport:
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def test_report_contract_is_versioned_json_and_omits_local_path(self, tmp_path: Path):
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path = _noise_png(tmp_path / "plain.png")
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payload = identify_metadata_record(collect_metadata_record(path), path=path).to_dict()
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assert payload["schema_version"] == PROVENANCE_REPORT_SCHEMA_VERSION == 1
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assert "path" not in payload
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assert json.loads(json.dumps(payload, allow_nan=False)) == payload
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@pytest.mark.parametrize("schema_version", [2, True, 1.0])
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def test_report_rejects_unsupported_output_schema(self, tmp_path: Path, schema_version: object):
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path = _noise_png(tmp_path / "plain.png")
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report = identify_metadata_record(collect_metadata_record(path), path=path)
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with pytest.raises(ValueError, match="Unsupported provenance report schema"):
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report.to_dict(schema_version=schema_version) # type: ignore[arg-type]
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def test_convenience_entry_point_matches_explicit_sequence(self, tmp_path: Path):
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path = _noise_png(tmp_path / "plain.png")
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record = collect_metadata_record(path)
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explicit = identify_from_evidence(evidence_from_metadata_record(record, path=path))
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convenience = identify_metadata_record(record, path=path)
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assert convenience == explicit
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def test_a_webp_record_matches(tmp_path: Path):
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"""RIFF has its own walk; a chunk kept or dropped wrongly shows up here."""
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path = tmp_path / "image.webp"
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Image.fromarray(np.zeros((64, 64, 3), dtype=np.uint8)).save(path, "WEBP", xmp=b"<x:xmpmeta>plain</x:xmpmeta>")
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assert collect_metadata_record(path)["container"] == "webp"
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_assert_same_verdict(path)
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def test_a_webp_record_collects_metadata_after_a_large_frame(tmp_path: Path):
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"""The RIFF walker seeks past coded pixels instead of stopping at the head window."""
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path = tmp_path / "late.webp"
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rng = np.random.default_rng(7)
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pixels = rng.integers(0, 255, (900, 900, 3), dtype=np.uint8)
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xmp = b"<x:xmpmeta><photoshop:DigitalSourceType>trainedAlgorithmicMedia</photoshop:DigitalSourceType></x:xmpmeta>"
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Image.fromarray(pixels).save(path, "WEBP", lossless=True, xmp=xmp)
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assert path.stat().st_size > HEAD_WINDOW
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_assert_same_verdict(path)
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def test_a_webp_record_does_not_carry_animation_frame_pixels(tmp_path: Path):
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"""ANMF is a coded-frame container, not a metadata chunk."""
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from remove_ai_watermarks.metadata_record import _riff_regions
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frame = b"jumb c2pa OpenAI trainedAlgorithmicMedia" * 20
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riff = b"RIFF" + (4 + 8 + len(frame)).to_bytes(4, "little") + b"WEBP"
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riff += b"ANMF" + len(frame).to_bytes(4, "little") + frame
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assert frame not in _riff_regions(riff)
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def test_an_invalid_short_riff_size_does_not_turn_the_container_into_a_trailer(tmp_path: Path):
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from remove_ai_watermarks.metadata_record import _trailer
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path = tmp_path / "invalid.webp"
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path.write_bytes(b"RIFF\x00\x00\x00\x00WEBPjumb c2pa trainedAlgorithmicMedia")
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assert _trailer(path, "webp") == b""
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def test_the_record_never_reopens_the_source(tmp_path: Path, monkeypatch):
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"""The reason the record exists: the verdict must run where the file is not."""
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path = FIXTURES / "chatgpt-1.png" if (FIXTURES / "chatgpt-1.png").exists() else _noise_png(tmp_path / "x.png")
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record = json.loads(json.dumps(collect_metadata_record(path)))
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def fail_if_called(*args, **kwargs):
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raise AssertionError("the record path must not open the source file")
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monkeypatch.setattr("builtins.open", fail_if_called)
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monkeypatch.setattr(Path, "open", fail_if_called)
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monkeypatch.setattr(Image, "open", fail_if_called)
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report = identify_from_evidence(evidence_from_metadata_record(record, path=path))
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assert isinstance(report, ProvenanceReport)
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