| """Real-artifact sanity. Skipped unless the checkpoint is present. | |
| When the user drops their trained best_model.pt at the canonical path, this | |
| test runs automatically — catches class-order or input-shape drift. | |
| """ | |
| from __future__ import annotations | |
| from pathlib import Path | |
| import numpy as np | |
| import pytest | |
| from PIL import Image | |
| from src.models import mri_dl_2d | |
| REAL_CKPT = Path("data/processed/mri_dl_2d/best_model.pt") | |
| def test_real_checkpoint_loads_and_predicts(tmp_path): | |
| model = mri_dl_2d.load(REAL_CKPT) | |
| arr = (np.random.RandomState(0).rand(170, 170, 3) * 255).astype(np.uint8) | |
| img = tmp_path / "scan.png" | |
| Image.fromarray(arr).save(str(img)) | |
| result = mri_dl_2d.predict_image(model, img) | |
| assert result["label_text"] in mri_dl_2d.CLASS_TO_IDX | |
| s = sum(p["probability"] for p in result["probabilities"]) | |
| assert abs(s - 1.0) < 1e-5 | |