cleanup: remove dead code and duplicate docs
- Remove session-ses_2f27.md (161KB raw session log) - Remove 49 ROOT_* duplicate files across REFERENCE/ - Remove 14 duplicate files between REFERENCE/ root and history/ - Remove asr_legacy.rs (dead code, replaced by asr.rs) - Remove src/core/worker/ (duplicate JobWorker) - Remove src/core/layers/ (empty directory) - Remove 4 .bak files in src/ - Remove 7 dead private methods in worker/processor.rs - Remove backup directory from git tracking
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Warren
182
scripts/trace_face_aggregator.py
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182
scripts/trace_face_aggregator.py
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#!/opt/homebrew/bin/python3.11
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"""
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Trace Face Aggregator - 獨立 Python 腳本
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由 Rust Worker (PythonExecutor) 排程執行
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功能: 讀取 face_detections 表 → 按 face_id 分組聚合 → 寫入 pre_chunks (source_type: trace_face)
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用法 (CLI):
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python3 scripts/trace_face_aggregator.py --file-uuid <uuid> [--fps <fps>]
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用法 (由 Rust 排程):
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executor.run("trace_face_aggregator.py", &["--file-uuid", uuid], Some(uuid), "TRACE_FACE", timeout)
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"""
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import sys
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import json
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import os
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import argparse
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import time
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sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
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from redis_publisher import RedisPublisher
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def get_pg_conn():
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import psycopg2
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db_url = os.getenv(
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"DATABASE_URL",
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"postgres://accusys@localhost:5432/momentry?options=-c%20search_path=dev",
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)
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return psycopg2.connect(db_url)
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def aggregate_traces(file_uuid: str, fps: float = 30.0) -> int:
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pub = RedisPublisher(file_uuid)
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pub.info("TRACE_FACE", f"Starting trace aggregation for {file_uuid}")
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conn = get_pg_conn()
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cur = conn.cursor()
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try:
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# 1. Count distinct face_ids
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cur.execute(
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"SELECT COUNT(DISTINCT face_id) FROM face_detections "
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"WHERE file_uuid = %s AND face_id IS NOT NULL",
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(file_uuid,),
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)
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distinct_count = cur.fetchone()[0]
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if distinct_count == 0:
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pub.info("TRACE_FACE", "No face detections found, skipping")
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return 0
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# 2. Get file_id from videos table
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cur.execute(
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"SELECT id, COALESCE(fps, %s) FROM videos WHERE file_uuid = %s",
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(fps, file_uuid),
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)
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row = cur.fetchone()
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if not row:
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pub.error(f"File {file_uuid} not found in videos table")
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return 0
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file_id, actual_fps = row[0], float(row[1])
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if actual_fps <= 0:
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actual_fps = fps
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# 3. Aggregate traces: group by face_id, compute start/end frame + max confidence
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cur.execute(
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"""
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SELECT
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face_id,
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MIN(frame_number) AS start_frame,
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MAX(frame_number) AS end_frame,
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MAX(confidence) AS max_conf
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FROM face_detections
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WHERE file_uuid = %s AND face_id IS NOT NULL
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GROUP BY face_id
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""",
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(file_uuid,),
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)
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traces = cur.fetchall()
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created = 0
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for face_id, start_frame, end_frame, max_conf in traces:
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# 4. Find representative frame (highest confidence)
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cur.execute(
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"""
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SELECT frame_number, bbox
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FROM face_detections
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WHERE file_uuid = %s AND face_id = %s AND confidence = %s
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LIMIT 1
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""",
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(file_uuid, face_id, max_conf),
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)
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rep_row = cur.fetchone()
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rep_frame = rep_row[0] if rep_row else start_frame
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rep_bbox = rep_row[1] if rep_row and rep_row[1] else {}
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raw_json = json.dumps({
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"face_id": face_id,
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"start_frame": int(start_frame),
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"end_frame": int(end_frame),
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"representative_frame": {
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"frame_number": int(rep_frame),
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"bbox": rep_bbox,
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},
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})
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start_time = float(start_frame) / actual_fps
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end_time = float(end_frame) / actual_fps
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# 5. Insert into pre_chunks (upsert)
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cur.execute(
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"""
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INSERT INTO pre_chunks
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(file_id, source_type, source_file, chunk_type,
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start_time, end_time, start_frame, end_frame,
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fps, raw_json, text_content, processed, chunk_id)
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VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s::jsonb, %s, %s, %s)
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ON CONFLICT (file_id, source_type, start_frame, end_frame)
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DO UPDATE SET
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end_frame = EXCLUDED.end_frame,
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end_time = EXCLUDED.end_time,
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raw_json = EXCLUDED.raw_json,
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fps = EXCLUDED.fps
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""",
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(
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file_id,
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"trace_face",
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None,
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"trace",
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start_time,
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end_time,
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int(start_frame),
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int(end_frame),
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actual_fps,
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raw_json,
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None,
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False,
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None,
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),
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)
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created += 1
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conn.commit()
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pub.info(
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"TRACE_FACE",
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f"Created {created} trace_face pre-chunks for {file_uuid}",
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)
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return created
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except Exception as e:
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conn.rollback()
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pub.error(f"Trace aggregation failed: {e}")
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raise
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finally:
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cur.close()
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conn.close()
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(description="Aggregate face detections into traces")
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parser.add_argument("--file-uuid", required=True, help="File UUID to process")
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parser.add_argument("--fps", type=float, default=30.0, help="Frames per second (optional)")
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parser.add_argument("--uuid", help="Generic UUID (passed by Rust executor, ignored)")
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args = parser.parse_args()
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uuid = args.file_uuid
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if args.uuid and not args.file_uuid:
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uuid = args.uuid
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start = time.time()
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count = aggregate_traces(uuid, args.fps)
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elapsed = time.time() - start
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print(
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json.dumps({
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"success": True,
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"file_uuid": uuid,
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"traces_generated": count,
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"duration_sec": round(elapsed, 2),
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})
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)
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