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| """ISP per-stage quality/throughput + augmentation lineage & leakage guard.""" | |
| from sensorflow.vitis.augment import generate_batch, list_augmentations | |
| from sensorflow.vitis.isp import run_isp | |
| class TestIsp: | |
| def test_per_stage_psnr_sanity(self, vitis_root): | |
| run = run_isp(n_frames=2, width_bits=12, include_previews=False) | |
| assert [e["stage"] for e in run["stage_report"]] == \ | |
| ["bad_pixel_correction", "demosaic", "hdr_tone_map", "gain", | |
| "denoise", "resize"] | |
| for e in run["stage_report"]: | |
| assert 20.0 < e["psnr_db"] <= 99.0, e | |
| assert 0.5 < e["ssim"] <= 1.0, e | |
| # Higher precision must not be worse than lower precision. | |
| lo = run_isp(n_frames=2, width_bits=8, include_previews=False) | |
| assert min(e["psnr_db"] for e in run["stage_report"]) > \ | |
| min(e["psnr_db"] for e in lo["stage_report"]) | |
| def test_throughput_labeled_modeled(self, vitis_root): | |
| run = run_isp(n_frames=1, include_previews=False) | |
| t = run["throughput"] | |
| assert t["modeled_not_measured"] is True | |
| assert t["measured_cpu_ms_per_frame"] > 0 | |
| assert t["modeled_fpga_fps_pipelined"] > 0 | |
| for e in run["stage_report"]: | |
| assert e["modeled_not_measured"] is True | |
| def test_previews_and_persistence(self, vitis_root): | |
| run = run_isp(n_frames=1, include_previews=True) | |
| assert run["previews"][0]["stages"][0]["reference_png"].startswith( | |
| "data:image/png;base64,") | |
| assert (vitis_root / "isp" / f"{run['run_id']}.json").exists() | |
| class TestAugment: | |
| def test_lineage_completeness_and_eval_only_flag(self, vitis_root): | |
| batch = generate_batch(n_variants=5, include_thumbnails=False) | |
| assert len(batch["variants"]) == 5 | |
| for v in batch["variants"]: | |
| lin = v["lineage"] | |
| for key in ("batch_id", "source_frame_id", "source_sequence_id", | |
| "recipe", "seed", "backend", "backend_config"): | |
| assert key in lin, f"lineage missing {key}" | |
| assert lin["recipe"] and all("aug" in s and "params" in s | |
| for s in lin["recipe"]) | |
| # Leakage guard: evaluation-only by default, never training data. | |
| assert v["evaluation_only"] is True | |
| assert v["training_eligible"] is False | |
| assert v["recommended_dataset_destination"] == \ | |
| "REGRESSION_EVALUATION_SET" | |
| assert v["gt_boxes"], "variants must inherit GT" | |
| def test_deterministic_given_seed(self, vitis_root): | |
| a = generate_batch(n_variants=3, seed=99, include_thumbnails=False) | |
| b = generate_batch(n_variants=3, seed=99, include_thumbnails=False) | |
| assert [v["lineage"]["seed"] for v in a["variants"]] == \ | |
| [v["lineage"]["seed"] for v in b["variants"]] | |
| def test_unknown_recipe_rejected(self, vitis_root): | |
| import pytest | |
| with pytest.raises(ValueError): | |
| generate_batch(recipes=[{"aug": "sharknado"}], n_variants=1) | |
| def test_raremine_hook_skipped_for_test_batches(self, vitis_root): | |
| # Test batches run under a redirected vitis root; routing into | |
| # raremine's real candidate store must be skipped so tests never | |
| # touch shared state. Real persisted batches route when raremine | |
| # is importable (verified manually via the live API). | |
| batch = generate_batch(n_variants=4, include_thumbnails=False) | |
| hook = batch["raremine_hook"] | |
| assert "available" in hook and "routed_candidates" in hook | |
| assert hook["routed_candidates"] == 0 | |
| assert "ephemeral/test" in hook["note"] | |
| def test_registry_listing(self): | |
| names = {a["name"] for a in list_augmentations()} | |
| assert {"sensor_noise", "low_light", "hdr_extreme", "lens_distortion", | |
| "chromatic_aberration", "motion_blur", "glare"} <= names | |