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03fb460f77
Corpus images were gitignored (local-only). The negatives were reviewed and cleared for publishing, so the labeled set is now committed (regular git, 65 MB across 25 files) -- making the removal regression set reproducible and CI-able. Corpus: - Track data/synthid_corpus/images/ (pos 9, neg 15, cleaned 1); keep only the synthetic refs/ calibration fills gitignored. - Reconcile manifest.csv to the on-disk files: 117 -> 25 rows (92 dangling rows for removed images pruned; dedup left one cleaned output, f6dd47a5). - Rewrite the corpus README layout/policy (images committed; review every image for private content before adding -- public repo, permanent history). Test fixtures: - Remove data/samples/not-ai-1/2/3 (personal iPhone photos, incl. GPS EXIF). - Add the clean_photo conftest fixture serving a verified-negative image from the corpus neg/ set; repoint the three "non-AI / clean photo" tests onto it (skips if the corpus is absent). Metadata-source coverage (close the last sub-variant gaps): - c2pa digitalSourceType: algorithmicMedia (procedural, not flagged AI) and compositeWithTrainedAlgorithmicMedia (AI + SynthID proxy). - exif_generator: EXIF Artist and ImageDescription fields (Software/Make/XMP CreatorTool were already covered). All 8 metadata-source kinds are now tested at both the unit and identify() level. 313 tests pass. CLAUDE.md updated (corpus tracked, clean_photo fixture). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
80 lines
2.5 KiB
Python
80 lines
2.5 KiB
Python
"""Shared fixtures for remove-ai-watermarks test suite."""
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from __future__ import annotations
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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 PIL import Image
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from PIL.PngImagePlugin import PngInfo
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CORPUS_NEG_DIR = Path(__file__).resolve().parent.parent / "data" / "synthid_corpus" / "images" / "neg"
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@pytest.fixture
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def clean_photo() -> Path:
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"""A verified-negative real photo from the corpus neg/ set.
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Used by the "non-AI image" assertions (no SynthID, verdict unknown). These
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are real photos with no AI provenance, the ground truth for "must not false-
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positive". Skips if the corpus is not checked out.
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"""
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files = sorted(CORPUS_NEG_DIR.glob("*")) if CORPUS_NEG_DIR.exists() else []
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if not files:
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pytest.skip("no corpus neg/ images present")
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return files[0]
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@pytest.fixture
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def tmp_image_path(tmp_path: Path) -> Path:
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"""Create a minimal 200x200 test PNG image and return its path."""
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img = np.random.randint(0, 255, (200, 200, 3), dtype=np.uint8)
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path = tmp_path / "test_image.png"
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cv2.imwrite(str(path), img)
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return path
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@pytest.fixture
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def tmp_large_image_path(tmp_path: Path) -> Path:
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"""Create a 1200x1200 test PNG image (triggers large watermark branch)."""
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img = np.random.randint(0, 255, (1200, 1200, 3), dtype=np.uint8)
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path = tmp_path / "test_large.png"
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cv2.imwrite(str(path), img)
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return path
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@pytest.fixture
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def tmp_jpeg_path(tmp_path: Path) -> Path:
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"""Create a minimal JPEG test image."""
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img = np.random.randint(0, 255, (100, 100, 3), dtype=np.uint8)
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path = tmp_path / "test_image.jpg"
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cv2.imwrite(str(path), img)
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return path
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@pytest.fixture
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def tmp_png_with_ai_metadata(tmp_path: Path) -> Path:
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"""Create a PNG with AI-related metadata keys."""
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img = Image.new("RGB", (64, 64), color=(128, 128, 128))
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pnginfo = PngInfo()
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pnginfo.add_text("parameters", "Steps: 20, Sampler: Euler, CFG scale: 7")
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pnginfo.add_text("prompt", "a beautiful landscape")
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pnginfo.add_text("Author", "Test Author")
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path = tmp_path / "ai_metadata.png"
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img.save(path, pnginfo=pnginfo)
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return path
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@pytest.fixture
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def tmp_clean_png(tmp_path: Path) -> Path:
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"""Create a PNG with no AI metadata."""
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img = Image.new("RGB", (64, 64), color=(200, 100, 50))
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pnginfo = PngInfo()
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pnginfo.add_text("Author", "Human Artist")
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pnginfo.add_text("Title", "Test Artwork")
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path = tmp_path / "clean.png"
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img.save(path, pnginfo=pnginfo)
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return path
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