Add pooled local AV baselines and research notes

summarize_local_baselines.py

@@ -0,0 +1,42 @@
+"""Print B0/B1 activity results in percent, with one explicit AP protocol."""
+
+import argparse
+import json
+from pathlib import Path
+import re
+import statistics
+
+
+def main():
+    parser = argparse.ArgumentParser(description=__doc__)
+    parser.add_argument("--root", type=Path, default=Path("results/easycom_local_b1"))
+    parser.add_argument("--protocol", choices=("causal_valid_only", "egospeak_full_timeline"), default="causal_valid_only")
+    args = parser.parse_args()
+    files = sorted(args.root.glob("*/metrics.json"))
+    if not files:
+        raise SystemExit(f"No */metrics.json in {args.root}")
+    print(f"Protocol: {args.protocol}; all AP/mAP numbers are percentages")
+    print(f"{'run':<23} {'0.2s mAP':>11} {'BG AP':>11} {'wearer AP':>11} {'others AP':>11} {'mean mAP':>11}")
+    groups = {}
+    for path in files:
+        metrics = json.loads(path.read_text())
+        score = metrics[args.protocol]
+        first = score["horizons"][0]
+        ap = first["class_ap"]
+        values = [100 * value for value in (first["map"], ap["background"],
+                  ap["camera_wearer_speaking"], ap["other_people_speaking"], score["mean_map"])]
+        name = path.parent.name
+        print(f"{name:<23}" + "".join(f" {v:11.5f}" for v in values))
+        group = re.sub(r"_seed\d+$", "", name)
+        groups.setdefault(group, []).append(values)
+    print("\nMean ± sample standard deviation (AP/mAP percentage points)")
+    for group, rows in sorted(groups.items()):
+        stats = []
+        for column in zip(*rows):
+            spread = f"{statistics.stdev(column):.5f}" if len(column) > 1 else "n/a"
+            stats.append(f"{statistics.mean(column):.5f} ± {spread}")
+        print(f"{group:<23}" + " | ".join(stats))
+
+
+if __name__ == "__main__":
+    main()