2bc24b2cc4
1. Ne plus kill demo.py apres PLY saved: son viser/PointCloudViewer natif (camera frustums, per-frame confidence filtering, animation) donne une visu bcp plus propre que viser_ply.py standalone (XYZ+RGB seul). Cout: ~6GB VRAM par job done garde alive jusquau prochain pick_worker qui peut kill si besoin. 2. set_status clear auto le champ error quand status transitionne vers extracting/running/done/queued: sinon les dashboards montrent les erreurs historiques sur les jobs en cours de retry.
553 lines
22 KiB
Python
553 lines
22 KiB
Python
#!/usr/bin/env python3
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"""Dispatcher daemon: picks queued jobs/stitches and runs them on available workers.
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Env:
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COSMA_QC_DB : SQLite path (default /var/lib/cosma-qc/jobs.db)
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COSMA_QC_WORKERS : JSON list of workers [{host, ssh_alias, gpu, vram_mib,
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frames_dir, lingbot_path}]
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COSMA_QC_FPS : extraction fps (default 3)
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COSMA_QC_IMG_H : image height (default 294)
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COSMA_QC_IMG_W : image width (default 518)
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Jobs lifecycle:
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queued → extracting → running → done → [triggers per_auv stitch]
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↘ error
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Stitch lifecycle:
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queued → running → done → [triggers cross_auv stitch if all per_auv done]
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↘ error
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"""
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from __future__ import annotations
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import json
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import os
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import re
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import shlex
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import sqlite3
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import subprocess
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import sys
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import threading
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import time
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from contextlib import closing
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from datetime import datetime, timezone
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from pathlib import Path
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def _now_iso() -> str:
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return datetime.now(timezone.utc).isoformat(timespec="seconds")
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DB_PATH = Path(os.environ.get("COSMA_QC_DB", "/var/lib/cosma-qc/jobs.db"))
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FPS = int(os.environ.get("COSMA_QC_FPS", "3"))
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IMG_H = int(os.environ.get("COSMA_QC_IMG_H", "294"))
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IMG_W = int(os.environ.get("COSMA_QC_IMG_W", "518"))
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POLL_S = int(os.environ.get("COSMA_QC_POLL_S", "4"))
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STITCH_SCRIPT = Path(__file__).parent / "stitch.py"
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DEFAULT_WORKERS = [
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{
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"host": "192.168.0.87", "ssh_alias": "gpu", "gpu": "RTX 3060 12GB",
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"vram_mib": 11913,
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"frames_dir": "/home/floppyrj45/cosma-qc-frames",
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"lingbot_path": "/home/floppyrj45/ai-video/lingbot-map",
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"viser_port_base": 8100,
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},
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{
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"host": "192.168.0.84", "ssh_alias": "cosma-vm", "gpu": "RTX 3090 24GB",
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"vram_mib": 24576,
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"frames_dir": "/home/floppyrj45/cosma-qc-frames",
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"lingbot_path": "/home/floppyrj45/ai-video/lingbot-map",
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"viser_port_base": 8100,
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},
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]
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WORKERS = json.loads(os.environ.get("COSMA_QC_WORKERS", json.dumps(DEFAULT_WORKERS)))
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_worker_lock = threading.Lock()
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_reserved_vram = {w["host"]: 0 for w in WORKERS}
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def db() -> sqlite3.Connection:
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conn = sqlite3.connect(DB_PATH, isolation_level=None)
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conn.execute("PRAGMA journal_mode=WAL")
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conn.row_factory = sqlite3.Row
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return conn
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def ssh(alias: str, cmd: str, timeout: int = 30) -> tuple[int, str, str]:
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p = subprocess.run(
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["ssh", "-o", "BatchMode=yes", "-o", "ConnectTimeout=5", alias, cmd],
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capture_output=True, text=True, timeout=timeout,
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)
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return p.returncode, p.stdout, p.stderr
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def worker_free_vram_mib(worker: dict) -> int:
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rc, out, _ = ssh(worker["ssh_alias"], "nvidia-smi --query-gpu=memory.free --format=csv,noheader,nounits")
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try:
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return int(out.strip().splitlines()[0]) if rc == 0 else 0
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except Exception:
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return 0
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def pick_worker(estimated_vram_mib: int) -> dict | None:
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"""Pick worker with most effective free VRAM (actual free minus local reservations)
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and reserve the estimated VRAM. Returns None if none fit."""
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with _worker_lock:
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best = None
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for w in WORKERS:
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free = worker_free_vram_mib(w) - _reserved_vram.get(w["host"], 0)
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if free >= estimated_vram_mib and (best is None or free > best[0]):
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best = (free, w)
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if best:
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_reserved_vram[best[1]["host"]] = _reserved_vram.get(best[1]["host"], 0) + estimated_vram_mib
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return best[1]
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return None
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def release_worker(worker: dict, estimated_vram_mib: int):
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with _worker_lock:
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h = worker["host"]
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_reserved_vram[h] = max(0, _reserved_vram.get(h, 0) - estimated_vram_mib)
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def estimate_vram_mib(frame_count: int) -> int:
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# windowed mode + offload_to_cpu caps VRAM usage regardless of total frames.
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# Observed: ~3.5 GB model + ~1.5 GB working set for window_size=16. Safe budget: 6 GB.
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return 6000
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def set_status(job_id: int, **fields):
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# Auto-clear stale error text when the job moves into a live state so the dashboard
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# stops showing a previous failure alongside a fresh run.
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if fields.get("status") in ("extracting", "running", "done", "queued") and "error" not in fields:
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fields["error"] = None
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keys = list(fields.keys())
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vals = [fields[k] for k in keys]
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q = "UPDATE jobs SET " + ", ".join(f"{k}=?" for k in keys) + " WHERE id=?"
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with closing(db()) as conn:
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conn.execute(q, (*vals, job_id))
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def set_stitch_status(stitch_id: int, **fields):
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keys = list(fields.keys())
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vals = [fields[k] for k in keys]
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q = "UPDATE stitches SET " + ", ".join(f"{k}=?" for k in keys) + " WHERE id=?"
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with closing(db()) as conn:
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conn.execute(q, (*vals, stitch_id))
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def count_frames(worker: dict, frames_dir: str) -> int:
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rc, out, _ = ssh(worker["ssh_alias"], f"ls {shlex.quote(frames_dir)} 2>/dev/null | wc -l")
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try:
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return int(out.strip()) if rc == 0 else 0
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except Exception:
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return 0
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def scp_to_worker(local_path: str, worker: dict, remote_path: str):
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"""Copy a file to the worker.
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`local_path` may be either:
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- a path on the dispatcher host (standard scp from here)
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- "host:abs_path" — pulled by the worker directly from `host`
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(avoids routing bytes through the dispatcher).
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"""
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if ":" in local_path and not local_path.startswith("/"):
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src_host, src_path = local_path.split(":", 1)
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# Pull from source host directly on the worker
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pull_cmd = (
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f"scp -o BatchMode=yes {shlex.quote(src_host)}:{shlex.quote(src_path)} "
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f"{shlex.quote(remote_path)}"
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)
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rc, _, err = ssh(worker["ssh_alias"], pull_cmd, timeout=7200)
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if rc != 0:
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raise RuntimeError(f"remote scp ({src_host}→{worker['host']}) failed: {err[:200]}")
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return
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r = subprocess.run(
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["scp", "-o", "BatchMode=yes", local_path, f"{worker['ssh_alias']}:{remote_path}"],
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capture_output=True, timeout=1800,
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)
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if r.returncode != 0:
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raise RuntimeError(f"scp failed: {r.stderr.decode()[:200]}")
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def _path_basename(p: str) -> str:
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if ":" in p and not p.startswith("/"):
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return Path(p.split(":", 1)[1]).name
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return Path(p).name
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def video_duration_s(worker: dict, worker_src: str) -> float:
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_, out, _ = ssh(worker["ssh_alias"],
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f"ffprobe -v error -show_entries format=duration "
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f"-of csv=p=0 {shlex.quote(worker_src)} 2>/dev/null || echo 0")
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try:
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return float(out.strip())
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except Exception:
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return 0.0
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def do_extract(job: sqlite3.Row, worker: dict) -> str:
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videos = json.loads(job["video_paths"])
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frames_dir = f"{worker['frames_dir']}/job_{job['id']}"
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# Clean any frame_*.jpg from a prior run so count_frames reflects this extraction only
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# (retries/restarts otherwise inflate frame_count with duplicates).
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ssh(worker["ssh_alias"], f"mkdir -p {shlex.quote(frames_dir)} && rm -f {shlex.quote(frames_dir)}/frame_*.jpg")
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idx = 0
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total_frames_est = 0 # will be computed after each scp
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for v in videos:
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vf = f"fps={FPS},scale={IMG_W}:{IMG_H}"
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pattern = f"{frames_dir}/frame_%06d.jpg"
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worker_src = f"{frames_dir}/src_{_path_basename(v)}"
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rc_check = ssh(worker["ssh_alias"], f"test -f {shlex.quote(worker_src)}")[0]
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if rc_check != 0:
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print(f" scp {_path_basename(v)} → {worker['host']}...")
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scp_to_worker(v, worker, worker_src)
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dur = video_duration_s(worker, worker_src)
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total_frames_est += max(1, int(dur * FPS))
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exit_file = f"/tmp/cosma-ffmpeg-{job['id']}-{idx}.exit"
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bg = (
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f"rm -f {shlex.quote(exit_file)}; "
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f"ffmpeg -hide_banner -loglevel error -i {shlex.quote(worker_src)} "
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f"-vf {shlex.quote(vf)} -start_number {idx} -q:v 4 {shlex.quote(pattern)} "
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f"</dev/null >/tmp/cosma-ffmpeg-{job['id']}.log 2>&1; "
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f"echo $? > {shlex.quote(exit_file)}"
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)
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ssh(worker["ssh_alias"], f"setsid bash -c {shlex.quote(bg)} >/dev/null 2>&1 &")
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while True:
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# Use -s (file exists AND size > 0) to avoid race: setsid bash writes the exit code
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# AFTER ffmpeg finishes; a plain -f can match a zero-byte placeholder mid-write.
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rc_done, _, _ = ssh(worker["ssh_alias"], f"test -s {shlex.quote(exit_file)}")
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current = count_frames(worker, frames_dir)
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pct = min(99, current * 100 // total_frames_est)
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set_status(job["id"], frame_count=current, progress=pct)
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if rc_done == 0:
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break
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time.sleep(5)
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_, code_str, _ = ssh(worker["ssh_alias"], f"cat {shlex.quote(exit_file)} 2>/dev/null || echo 1")
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rc = int(code_str.strip()) if code_str.strip().isdigit() else 1
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if rc != 0:
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_, err, _ = ssh(worker["ssh_alias"], f"cat /tmp/cosma-ffmpeg-{job['id']}.log 2>/dev/null | tail -5 || echo ''")
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raise RuntimeError(f"ffmpeg failed on {v}: {err[:200]}")
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idx = count_frames(worker, frames_dir)
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# Free MP4 cache immediately: thin pool on Proxmox host is tight and src_*.MP4
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# are 1-11 GB each. Frames are already extracted so worker_src is no longer needed.
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ssh(worker["ssh_alias"], f"rm -f {shlex.quote(worker_src)}")
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set_status(job["id"], frame_count=idx, progress=min(99, idx * 100 // total_frames_est))
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# Trim once per job so LVM thin pool on the host actually reclaims the freed blocks.
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ssh(worker["ssh_alias"], "sudo fstrim / 2>/dev/null || fstrim / 2>/dev/null", timeout=60)
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return frames_dir
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def do_reconstruct(job: sqlite3.Row, worker: dict, frames_dir: str) -> tuple[str, str, str]:
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port = worker["viser_port_base"] + job["id"]
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log = f"/tmp/cosma-qc-job-{job['id']}.log"
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ckpt = f"{worker['lingbot_path']}/checkpoints/lingbot-map/lingbot-map-long.pt"
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ply_path = f"{frames_dir}/reconstruction.ply"
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# Adaptive stride to fit CPU RAM: load_fn stacks full image tensor ~3.15 MB/frame @ 512x512x3 fp32.
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# .87 has 23 GB RAM, .84 has 62 GB. Keep effective frame count ~4k to stay safe.
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frame_count = job["frame_count"] or 0
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ram_gb = 23 if worker["host"] == "192.168.0.87" else 62
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ram_budget_gb = ram_gb * 0.45 # leave headroom for model + OS + cuda pinned buffers
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stride = 1
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while frame_count * 3.15 / 1024 / stride > ram_budget_gb:
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stride += 1
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# demo.py starts a viser web server after saving the PLY and never exits.
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# Wrap it: launch in bg, wait for "PLY saved" marker in the log, kill, exit 0.
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# Match on the unique job frames_dir to identify our demo.py among all children/threads.
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marker = shlex.quote(frames_dir)
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cmd = (
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f"cd {shlex.quote(worker['lingbot_path'])} && source .venv/bin/activate && "
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f"setsid python3 demo.py --model_path {shlex.quote(ckpt)} "
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f"--image_folder {shlex.quote(frames_dir)} --port {port} "
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f"--stride {stride} --use_sdpa --mode windowed --window_size 16 --overlap_size 2 --offload_to_cpu "
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f"--save_ply {shlex.quote(ply_path)} > {log} 2>&1 & "
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f"DEMO_PID=$!; "
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f"for i in $(seq 1 3600); do "
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f" if ! kill -0 $DEMO_PID 2>/dev/null; then wait $DEMO_PID; exit $?; fi; "
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f" if grep -q 'PLY saved:' {log} 2>/dev/null; then "
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# Keep demo.py alive so its viser/PointCloudViewer (with camera frustums, per-frame
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# confidence filtering, animation) stays reachable. Standalone viser_ply.py only has
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# XYZ+RGB which gives a poor-looking cloud. The worker eats ~6GB VRAM per alive demo.py
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# until pick_worker can no longer fit a new job; _cleanup_stale_demos reaps the oldest.
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f" exit 0; "
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f" fi; "
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f" sleep 3; "
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f"done; "
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f"pkill -KILL -f \"demo.py.*{frames_dir}\" 2>/dev/null; exit 124"
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)
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rc, _, err = ssh(worker["ssh_alias"], cmd, timeout=3 * 3600)
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# Accept rc==0 OR PLY file exists with non-zero size (kill -TERM may return non-zero)
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ply_rc, ply_size, _ = ssh(worker["ssh_alias"], f"stat -c %s {shlex.quote(ply_path)} 2>/dev/null || echo 0")
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try:
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ply_ok = int(ply_size.strip()) > 0
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except ValueError:
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ply_ok = False
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if not ply_ok:
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tail = ssh(worker["ssh_alias"], f"tail -30 {log}")[1]
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raise RuntimeError(f"demo.py failed (rc={rc}): {err[:200]}\n---\n{tail[:800]}")
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viser_url = f"http://{worker['host']}:{port}"
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return viser_url, log, ply_path
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def _maybe_create_per_auv_stitch(job_id: int):
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with closing(db()) as conn:
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job = conn.execute("SELECT * FROM jobs WHERE id=?", (job_id,)).fetchone()
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if not job:
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return
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acq_id, auv = job["acquisition_id"], job["auv"]
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total = conn.execute(
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"SELECT COUNT(*) FROM jobs WHERE acquisition_id=? AND auv=?", (acq_id, auv)
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).fetchone()[0]
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done = conn.execute(
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"SELECT COUNT(*) FROM jobs WHERE acquisition_id=? AND auv=? AND status='done'", (acq_id, auv)
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).fetchone()[0]
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if total == 0 or done < total:
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return
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existing = conn.execute(
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"SELECT id FROM stitches WHERE acquisition_id=? AND level='per_auv' AND auv=?", (acq_id, auv)
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).fetchone()
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if existing:
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return
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job_ids = [r["id"] for r in conn.execute(
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"SELECT id FROM jobs WHERE acquisition_id=? AND auv=?", (acq_id, auv)
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).fetchall()]
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conn.execute(
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"INSERT INTO stitches (acquisition_id, level, auv, input_job_ids) VALUES (?,?,?,?)",
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(acq_id, "per_auv", auv, json.dumps(job_ids))
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)
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print(f" → Stitch per_auv créé pour {auv} acq#{acq_id}")
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def _maybe_create_cross_auv_stitch(stitch_id: int):
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with closing(db()) as conn:
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st = conn.execute("SELECT * FROM stitches WHERE id=?", (stitch_id,)).fetchone()
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if not st:
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return
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acq_id = st["acquisition_id"]
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n_auvs = conn.execute(
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"SELECT COUNT(DISTINCT auv) FROM jobs WHERE acquisition_id=?", (acq_id,)
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).fetchone()[0]
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if n_auvs < 2:
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return
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total_per_auv = conn.execute(
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"SELECT COUNT(*) FROM stitches WHERE acquisition_id=? AND level='per_auv'", (acq_id,)
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).fetchone()[0]
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done_per_auv = conn.execute(
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"SELECT COUNT(*) FROM stitches WHERE acquisition_id=? AND level='per_auv' AND status='done'", (acq_id,)
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).fetchone()[0]
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if total_per_auv == 0 or done_per_auv < n_auvs:
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return
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existing = conn.execute(
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"SELECT id FROM stitches WHERE acquisition_id=? AND level='cross_auv'", (acq_id,)
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).fetchone()
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if existing:
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return
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stitch_ids = [r["id"] for r in conn.execute(
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"SELECT id FROM stitches WHERE acquisition_id=? AND level='per_auv'", (acq_id,)
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).fetchall()]
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conn.execute(
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"INSERT INTO stitches (acquisition_id, level, input_stitch_ids, input_job_ids) VALUES (?,?,?,?)",
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(acq_id, "cross_auv", json.dumps(stitch_ids), "[]")
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)
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print(f" → Stitch cross_auv créé pour acq#{acq_id}")
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def deploy_stitch_script(worker: dict):
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subprocess.run(
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["scp", str(STITCH_SCRIPT), f"{worker['ssh_alias']}:/tmp/cosma-stitch.py"],
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capture_output=True, timeout=30
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)
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def run_one_stitch(stitch: sqlite3.Row):
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stitch_id = stitch["id"]
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worker = pick_worker(2000)
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if not worker:
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worker = WORKERS[0]
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with closing(db()) as conn:
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if stitch["level"] == "per_auv":
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job_ids = json.loads(stitch["input_job_ids"] or "[]")
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if job_ids:
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rows = conn.execute(
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f"SELECT ply_path FROM jobs WHERE id IN ({','.join('?'*len(job_ids))})",
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job_ids
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).fetchall()
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else:
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rows = []
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ply_paths = [r["ply_path"] for r in rows if r["ply_path"]]
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else:
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stitch_ids = json.loads(stitch["input_stitch_ids"] or "[]")
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if stitch_ids:
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rows = conn.execute(
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f"SELECT output_ply FROM stitches WHERE id IN ({','.join('?'*len(stitch_ids))})",
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stitch_ids
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).fetchall()
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else:
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rows = []
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ply_paths = [r["output_ply"] for r in rows if r["output_ply"]]
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if len(ply_paths) == 0:
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set_stitch_status(stitch_id, status="error",
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error="Aucun PLY disponible",
|
|
finished_at=_now_iso())
|
|
return
|
|
|
|
out_ply = f"{worker['frames_dir']}/stitch_{stitch_id}.ply"
|
|
|
|
# Single PLY — no alignment needed, pass through directly.
|
|
if len(ply_paths) == 1:
|
|
rc, _, err = ssh(worker["ssh_alias"], f"cp {shlex.quote(ply_paths[0])} {shlex.quote(out_ply)}")
|
|
if rc != 0:
|
|
set_stitch_status(stitch_id, status="error", error=f"cp failed: {err[:200]}", finished_at=_now_iso())
|
|
return
|
|
set_stitch_status(stitch_id, status="done", output_ply=out_ply, finished_at=_now_iso())
|
|
print(f" → stitch #{stitch_id} passthrough (1 PLY) → {out_ply}")
|
|
_maybe_create_cross_auv_stitch(stitch_id)
|
|
return
|
|
deploy_stitch_script(worker)
|
|
|
|
cmd = (
|
|
f"source {shlex.quote(worker['lingbot_path'])}/.venv/bin/activate && "
|
|
f"python3 /tmp/cosma-stitch.py {shlex.quote(out_ply)} "
|
|
+ " ".join(shlex.quote(p) for p in ply_paths)
|
|
+ f" > /tmp/cosma-stitch-{stitch_id}.log 2>&1"
|
|
)
|
|
|
|
set_stitch_status(stitch_id, status="running", worker_host=worker["host"], started_at=_now_iso())
|
|
try:
|
|
rc, _, err = ssh(worker["ssh_alias"], cmd, timeout=4 * 3600)
|
|
except Exception as e:
|
|
set_stitch_status(stitch_id, status="error", error=str(e)[:500], finished_at=_now_iso())
|
|
return
|
|
|
|
if rc == 0:
|
|
set_stitch_status(stitch_id, status="done", output_ply=out_ply, finished_at=_now_iso())
|
|
_maybe_create_cross_auv_stitch(stitch_id)
|
|
else:
|
|
tail = ssh(worker["ssh_alias"], f"tail -20 /tmp/cosma-stitch-{stitch_id}.log")[1]
|
|
set_stitch_status(stitch_id, status="error",
|
|
error=f"{err[:200]}\n{tail[:600]}",
|
|
finished_at=_now_iso())
|
|
|
|
|
|
def run_one(job: sqlite3.Row) -> bool:
|
|
"""Returns True if a worker was picked and work started."""
|
|
job_id = job["id"]
|
|
estimated = estimate_vram_mib(job["frame_count"] or 150)
|
|
worker = pick_worker(estimated)
|
|
if not worker:
|
|
# release claim so the job can be re-tried by main loop
|
|
set_status(job_id, status="queued")
|
|
return False
|
|
set_status(job_id, status="extracting", worker_host=worker["host"], started_at=_now_iso())
|
|
try:
|
|
frames_dir = do_extract(job, worker)
|
|
frame_count = count_frames(worker, frames_dir)
|
|
set_status(job_id, frames_dir=frames_dir, frame_count=frame_count,
|
|
status="running", progress=0)
|
|
viser_url, log, ply_path = do_reconstruct(job, worker, frames_dir)
|
|
set_status(job_id, status="done", viser_url=viser_url, ply_path=ply_path,
|
|
progress=100, log_tail=log, finished_at=_now_iso())
|
|
_maybe_create_per_auv_stitch(job_id)
|
|
except Exception as e:
|
|
set_status(job_id, status="error", error=str(e)[:2000], finished_at=_now_iso())
|
|
finally:
|
|
release_worker(worker, estimated)
|
|
return True
|
|
|
|
|
|
def pop_queued() -> sqlite3.Row | None:
|
|
"""Atomic claim: grab a queued job and mark it 'claimed' to prevent double-dispatch."""
|
|
with closing(db()) as conn:
|
|
try:
|
|
conn.execute("BEGIN IMMEDIATE")
|
|
row = conn.execute(
|
|
"SELECT * FROM jobs WHERE status='queued' ORDER BY created_at LIMIT 1"
|
|
).fetchone()
|
|
if row:
|
|
conn.execute("UPDATE jobs SET status='claimed' WHERE id=?", (row["id"],))
|
|
conn.execute("COMMIT")
|
|
except Exception:
|
|
conn.execute("ROLLBACK")
|
|
return None
|
|
return row
|
|
|
|
|
|
def pop_queued_stitch() -> sqlite3.Row | None:
|
|
with closing(db()) as conn:
|
|
try:
|
|
conn.execute("BEGIN IMMEDIATE")
|
|
row = conn.execute(
|
|
"SELECT * FROM stitches WHERE status='queued' ORDER BY created_at LIMIT 1"
|
|
).fetchone()
|
|
if row:
|
|
conn.execute("UPDATE stitches SET status='claimed' WHERE id=?", (row["id"],))
|
|
conn.execute("COMMIT")
|
|
except Exception:
|
|
conn.execute("ROLLBACK")
|
|
return None
|
|
return row
|
|
|
|
|
|
def write_heartbeat():
|
|
hb = DB_PATH.parent / "dispatcher.heartbeat"
|
|
try:
|
|
hb.write_text(_now_iso())
|
|
except Exception:
|
|
pass
|
|
|
|
|
|
_heartbeat_stop = threading.Event()
|
|
|
|
|
|
def _heartbeat_loop():
|
|
while not _heartbeat_stop.is_set():
|
|
write_heartbeat()
|
|
_heartbeat_stop.wait(5)
|
|
|
|
|
|
def _run_one_thread(job: sqlite3.Row):
|
|
try:
|
|
if not run_one(job):
|
|
print(f" ↳ job #{job['id']}: pas de worker dispo, remis en queued")
|
|
except Exception as e:
|
|
set_status(job["id"], status="error", error=f"run_one thread crashed: {str(e)[:1500]}",
|
|
finished_at=_now_iso())
|
|
|
|
|
|
def main():
|
|
print(f"cosma-qc dispatcher · DB={DB_PATH} · workers={[w['host'] for w in WORKERS]}")
|
|
threading.Thread(target=_heartbeat_loop, daemon=True).start()
|
|
active: set[threading.Thread] = set()
|
|
max_parallel = max(1, len(WORKERS))
|
|
while True:
|
|
# drain finished threads
|
|
active = {t for t in active if t.is_alive()}
|
|
if len(active) < max_parallel:
|
|
job = pop_queued()
|
|
if job:
|
|
print(f"→ job #{job['id']} ({job['auv']}/{job['gopro_serial']}/{job['segment_label']}) [active={len(active) + 1}]")
|
|
t = threading.Thread(target=_run_one_thread, args=(job,), daemon=False)
|
|
t.start()
|
|
active.add(t)
|
|
# brief pause so the thread can reserve its worker before we pop another
|
|
time.sleep(0.5)
|
|
continue
|
|
stitch = pop_queued_stitch()
|
|
if stitch:
|
|
label = f"{stitch['level']} {stitch['auv'] or ''} acq#{stitch['acquisition_id']}"
|
|
print(f"→ stitch #{stitch['id']} ({label})")
|
|
run_one_stitch(stitch)
|
|
continue
|
|
time.sleep(POLL_S)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
try:
|
|
main()
|
|
except KeyboardInterrupt:
|
|
sys.exit(0)
|