feat: update Python processors and add utility scripts

- Update ASR, face, OCR, pose processors - Add release pre-flight check script - Add synonym generation, chunk processing scripts - Add face recognition, stamp search utilities
2026-04-30 15:07:49 +08:00
parent f4697396e4
commit 8f05a7c188
256 changed files with 60505 additions and 299 deletions
@@ -0,0 +1,141 @@
+#!/usr/bin/python3.11
+"""
+ASR x Face Combination Statistics
+For each ASR segment, count unique faces (person_ids) appearing during that segment.
+Then aggregate: how many segments have 1 face, 2 faces, 3 faces, etc.
+"""
+
+import json
+import os
+from collections import defaultdict
+
+UUID = "384b0ff44aaaa1f1"
+BASE_DIR = f"output/{UUID}"
+
+
+def load_json(filepath):
+    with open(filepath, "r") as f:
+        return json.load(f)
+
+
+def build_asr_face_stats():
+    print(f"📊 Building ASR x Face combination statistics for {UUID}...")
+
+    # Load data
+    asr_data = load_json(os.path.join(BASE_DIR, f"{UUID}.asr.json"))
+    face_data = load_json(os.path.join(BASE_DIR, f"{UUID}.face_clustered.json"))
+
+    segments = asr_data.get("segments", [])
+    face_frames = face_data.get("frames", [])
+
+    # Build face lookup: timestamp -> set of person_ids
+    face_by_time = {}
+    for frame in face_frames:
+        ts = frame.get("timestamp", 0)
+        faces = frame.get("faces", [])
+        pids = set()
+        for f in faces:
+            pid = f.get("person_id")
+            if pid:
+                pids.add(pid)
+        face_by_time[ts] = pids
+
+    # Get sorted timestamps for efficient lookup
+    sorted_times = sorted(face_by_time.keys())
+
+    def get_faces_in_range(start, end):
+        """Get all unique person_ids appearing in a time range."""
+        all_pids = set()
+        for ts in sorted_times:
+            if start <= ts <= end:
+                all_pids.update(face_by_time[ts])
+        return all_pids
+
+    # Analyze each ASR segment
+    face_count_dist = defaultdict(int)
+    segment_details = []
+
+    for seg in segments:
+        start = seg.get("start", 0)
+        end = seg.get("end", 0)
+        text = seg.get("text", "")
+
+        pids = get_faces_in_range(start, end)
+        face_count = len(pids)
+
+        face_count_dist[face_count] += 1
+        segment_details.append(
+            {
+                "start": start,
+                "end": end,
+                "text": text[:80],
+                "face_count": face_count,
+                "person_ids": list(pids)[:5],  # Top 5
+            }
+        )
+
+    return dict(face_count_dist), segment_details, len(segments)
+
+
+def print_stats(dist, total_segments):
+    print("\n" + "=" * 60)
+    print("📈 ASR x Face Combination Statistics")
+    print("=" * 60)
+
+    print(f"\nTotal ASR segments: {total_segments}")
+    print(f"\n{'Face Count':<12} {'Segments':>10} {'Percentage':>12}")
+    print("-" * 40)
+
+    sorted_dist = sorted(dist.items(), key=lambda x: x[0])
+    for fc, count in sorted_dist:
+        pct = count / total_segments * 100
+        print(f"  {fc:>2} faces      {count:>8}   {pct:>6.1f}%")
+
+    # Summary
+    total_faces_sum = sum(fc * count for fc, count in dist.items())
+    avg_faces = total_faces_sum / total_segments if total_segments > 0 else 0
+    max_faces = max(dist.keys()) if dist else 0
+
+    print(f"\n📊 Summary:")
+    print(f"   Average faces per segment: {avg_faces:.1f}")
+    print(f"   Max faces in a segment:    {max_faces}")
+    print(
+        f"   Segments with 0 faces:     {dist.get(0, 0)} ({dist.get(0, 0) / total_segments * 100:.1f}%)"
+    )
+    print(
+        f"   Segments with 1 face:      {dist.get(1, 0)} ({dist.get(1, 0) / total_segments * 100:.1f}%)"
+    )
+    print(
+        f"   Segments with 2+ faces:    {total_segments - dist.get(0, 0) - dist.get(1, 0)}"
+    )
+
+    # Show some example segments
+    print(f"\n🔍 Example Segments:")
+    print(f"   0 faces:")
+    examples = [s for s in segment_details if s["face_count"] == 0][:3]
+    for ex in examples:
+        print(f"     [{ex['start']:.0f}s-{ex['end']:.0f}s] {ex['text']}...")
+
+    print(f"   1 face:")
+    examples = [s for s in segment_details if s["face_count"] == 1][:3]
+    for ex in examples:
+        print(
+            f"     [{ex['start']:.0f}s-{ex['end']:.0f}s] {ex['person_ids'][0]}: {ex['text']}..."
+        )
+
+    print(f"   3 faces:")
+    examples = [s for s in segment_details if s["face_count"] == 3][:3]
+    for ex in examples:
+        pids = ", ".join(ex["person_ids"])
+        print(f"     [{ex['start']:.0f}s-{ex['end']:.0f}s] [{pids}] {ex['text']}...")
+
+
+if __name__ == "__main__":
+    dist, segment_details, total = build_asr_face_stats()
+    print_stats(dist, total)
+
+    # Save
+    output_path = os.path.join(BASE_DIR, "asr_face_stats.json")
+    with open(output_path, "w") as f:
+        json.dump({"distribution": dist, "segments": segment_details}, f, indent=2)
+    print(f"\n💾 Saved: {output_path}")