| """Rescore fixed detections across IoU and semantic acceptance thresholds.""" |
|
|
| from metrics.classification import compute_classification_metrics |
| from metrics.localisation import compute_localisation_metrics |
| from metrics.semantic import SemanticPolicy, compute_semantic_classification_metrics, compute_semantic_localisation_metrics |
|
|
| IOU_GRID = (0.10, 0.20, 0.30, 0.40, 0.50, 0.60, 0.70, 0.80, 0.90) |
| SEMANTIC_GRID = (0.50, 0.60, 0.65, 0.70, 0.75, 0.80, 0.85, 0.90, 0.95, 1.0) |
|
|
|
|
| def policy_at_threshold(payload: dict, threshold: float) -> SemanticPolicy: |
| if not 0 <= threshold <= 1: |
| raise ValueError("Semantic threshold must be between zero and one") |
| return SemanticPolicy.from_dict({**payload, "accepted_matrix": [ |
| [int(i == j or (threshold < 1 and value > threshold)) for j, value in enumerate(row)] |
| for i, row in enumerate(payload["cosine_matrix"]) |
| ]}) |
|
|
|
|
| def build_sensitivity(predictions, gold, policy_payload) -> dict: |
| clean = [r for r in predictions if r.parsed_cleanly] |
| exact_class = compute_classification_metrics(clean, gold)["summary"]["micro"] |
| exact_iou = [{"iou": t, **compute_localisation_metrics(clean, gold, t)["summary"]["micro"]} for t in IOU_GRID] |
| classifications, localisations = [], [] |
| for threshold in SEMANTIC_GRID: |
| policy = policy_at_threshold(policy_payload, threshold) |
| classification = compute_semantic_classification_metrics(clean, gold, policy) |
| classifications.append({"threshold": threshold, **classification["summary"]["micro"], "newly_credited": len(classification["credited_matches"])}) |
| for iou in IOU_GRID: |
| loc = compute_semantic_localisation_metrics(clean, gold, policy, iou) |
| localisations.append({"threshold": threshold, "iou": iou, **loc["summary"]["micro"], "newly_credited": len(loc["credited_matches"])}) |
| return { |
| "n_images": len(clean), "iou_grid": IOU_GRID, "semantic_grid": SEMANTIC_GRID, |
| "scoring_definition": "All retained detections are evaluated without confidence filtering, weighting, or ranking. Only the IoU and semantic acceptance rules change; exact class IDs at IoU >= 0.50 remain primary.", |
| "retention_caveat": "Results are conditional on saved predictions. Inference-time detector confidence filtering and score-ranked output caps can affect which detections were retained.", |
| "exact_classification": exact_class, "exact_iou": exact_iou, |
| "classification": classifications, "localisation": localisations, |
| } |
|
|
