| """Tests for scripts/prepare_test_data.py — split ratios, reproducibility, CSV format, pairs.""" |
| import csv |
| from pathlib import Path |
|
|
| from scripts.make_sample_images import make_image |
| from scripts.prepare_test_data import prepare |
|
|
|
|
| def _make_dataset_dir(tmp: Path, layout: dict[str, int]) -> Path: |
| """layout: {folder_name: image_count}. Writes real JPEGs.""" |
| root = tmp / "input" |
| for folder, count in layout.items(): |
| d = root / folder |
| d.mkdir(parents=True) |
| for i in range(count): |
| (d / f"img{i}.jpg").write_bytes(make_image(hash((folder, i)) % 1000)) |
| return root |
|
|
|
|
| def _read(path: Path) -> list[dict]: |
| with path.open(newline="", encoding="utf-8") as fh: |
| return list(csv.DictReader(fh)) |
|
|
|
|
| def test_default_holdout_split(tmp_path): |
| root = _make_dataset_dir(tmp_path, {"dogA": 3, "dogB": 6}) |
| out = tmp_path / "out" |
| prepare(root, out, holdout=None, seed=1) |
|
|
| known = _read(out / "known_dogs.csv") |
| found = _read(out / "found_dogs.csv") |
| by_folder = lambda rows, f: [r for r in rows if r["folder"] == f] |
|
|
| |
| assert len(by_folder(found, "dogA")) == 1 |
| assert len(by_folder(known, "dogA")) == 2 |
| assert len(by_folder(found, "dogB")) == 2 |
| assert len(by_folder(known, "dogB")) == 4 |
|
|
|
|
| def test_explicit_holdout(tmp_path): |
| root = _make_dataset_dir(tmp_path, {"dogB": 6}) |
| out = tmp_path / "out" |
| prepare(root, out, holdout=1, seed=1) |
| assert len(_read(out / "found_dogs.csv")) == 1 |
| assert len(_read(out / "known_dogs.csv")) == 5 |
|
|
|
|
| def test_reproducible_with_same_seed(tmp_path): |
| root = _make_dataset_dir(tmp_path, {"dogA": 4, "dogB": 5}) |
| out1, out2 = tmp_path / "o1", tmp_path / "o2" |
| prepare(root, out1, holdout=None, seed=7) |
| prepare(root, out2, holdout=None, seed=7) |
| for fname in ("known_dogs.csv", "found_dogs.csv", "pairs.csv"): |
| assert (out1 / fname).read_text() == (out2 / fname).read_text() |
|
|
|
|
| def test_csv_columns_match_loader_contract(tmp_path): |
| root = _make_dataset_dir(tmp_path, {"dogA": 2}) |
| out = tmp_path / "out" |
| prepare(root, out, holdout=1, seed=1) |
| known_cols = _read(out / "known_dogs.csv")[0].keys() |
| found_cols = _read(out / "found_dogs.csv")[0].keys() |
| assert set(known_cols) == { |
| "folder", "image_file", "dog_name", "color", "size", "description", |
| "zip", "owner_name", "owner_email", "owner_phone", |
| } |
| assert set(found_cols) == { |
| "folder", "image_file", "description", "color", "size", "found_zip", |
| "current_location", "finder_name", "finder_email", "finder_phone", |
| } |
|
|
|
|
| def test_found_zip_equals_known_zip(tmp_path): |
| root = _make_dataset_dir(tmp_path, {"dogA": 3}) |
| out = tmp_path / "out" |
| prepare(root, out, holdout=1, seed=3) |
| known_zip = _read(out / "known_dogs.csv")[0]["zip"] |
| found_zip = _read(out / "found_dogs.csv")[0]["found_zip"] |
| assert known_zip == found_zip |
|
|
|
|
| def test_pairs_link_known_and_found(tmp_path): |
| root = _make_dataset_dir(tmp_path, {"dogA": 4}) |
| out = tmp_path / "out" |
| prepare(root, out, holdout=1, seed=5) |
| pairs = _read(out / "pairs.csv") |
| assert len(pairs) == 1 |
| row = pairs[0] |
| known_imgs = set(row["known_images"].split(";")) |
| found_imgs = set(row["found_images"].split(";")) |
| assert len(found_imgs) == 1 |
| assert len(known_imgs) == 3 |
| assert known_imgs.isdisjoint(found_imgs) |
| assert known_imgs | found_imgs == {"img0.jpg", "img1.jpg", "img2.jpg", "img3.jpg"} |
|
|
|
|
| def test_skips_empty_folder(tmp_path): |
| root = _make_dataset_dir(tmp_path, {"dogA": 2}) |
| (root / "empty_dog").mkdir() |
| out = tmp_path / "out" |
| result = prepare(root, out, holdout=1, seed=1) |
| assert "empty_dog" in result["skipped_folders"] |
| assert result["dogs"] == 1 |
|
|
