642 lines
23 KiB
Python
642 lines
23 KiB
Python
from __future__ import annotations
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import json
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import math
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import os
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import re
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import shutil
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import subprocess
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import sys
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from datetime import datetime, timezone
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from pathlib import Path
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from typing import Any, Dict, List, Optional, Tuple
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from app.logging_config import format_json_pretty
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from app.settings import Settings
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from app.state import MeasureSnapshot
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from app.subprocess_run import run_subprocess_with_log
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from loguru import logger
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def _py_exe(settings: Settings) -> str:
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return settings.python_fish_measure or sys.executable
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def _predict_weigth_from_svo2_extra_args(settings: Settings) -> List[str]:
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"""Flags aligned with FishMeasure/predict_weigth_from_svo2.py CLI."""
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out: List[str] = []
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if settings.predict_filter_pointcloud:
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out.append("--filter-pointcloud")
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if settings.predict_use_density_filter:
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out.append("--use-density-filter")
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if settings.predict_use_clustering_filter:
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out.append("--use-clustering-filter")
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if (
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settings.predict_use_pointcloud_classifier
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and settings.predict_pointcloud_classifier
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and Path(settings.predict_pointcloud_classifier).is_file()
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):
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out.extend(
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[
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"--pointcloud-classifier",
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settings.predict_pointcloud_classifier,
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"--use-pointcloud-classifier",
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"--pointcloud-classifier-threshold",
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str(settings.predict_pointcloud_classifier_threshold),
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]
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)
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if settings.predict_use_flatness_filter:
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out.append("--use-flatness-filter")
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out.extend(["--flatness-threshold", str(settings.predict_flatness_threshold)])
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out.extend(["--weight-top-k", str(settings.measure_weight_top_k)])
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if settings.measure_weight_top_by_length:
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out.append("--weight-top-by-length")
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else:
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out.append("--no-weight-top-by-length")
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if settings.predict_fish_video_weight_overlay:
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out.extend(
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[
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"--fish-video-weight-overlay",
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"--minute-interval-sec",
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str(settings.predict_minute_interval_sec),
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]
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)
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if not settings.measure_reuse_existing_clouds:
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out.append("--no-reuse-existing-clouds")
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return out
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def run_measure_subprocess(svo_path: Path, settings: Settings) -> None:
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script = settings.fish_measure_root / "predict_weigth_from_svo2.py"
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if not script.is_file():
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raise FileNotFoundError(f"Missing FishMeasure script: {script}")
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settings.measure_output_root.mkdir(parents=True, exist_ok=True)
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cmd = [
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_py_exe(settings),
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str(script),
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"--svo",
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str(svo_path.resolve()),
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"--save-output",
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str(settings.measure_output_root.resolve()),
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"--yolo-model",
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settings.yolo_model,
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"--weight-checkpoint",
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settings.weight_checkpoint,
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"--conf",
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str(settings.predict_conf),
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"--imgsz",
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str(settings.predict_imgsz),
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"--sam-device",
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settings.sam_device,
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"--max-frames",
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str(settings.predict_max_frames),
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"--frame-stride",
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str(settings.predict_frame_stride),
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]
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cmd.extend(_predict_weigth_from_svo2_extra_args(settings))
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proc = run_subprocess_with_log(
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cmd,
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cwd=str(settings.fish_measure_root),
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env=os.environ.copy(),
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log_name="FishMeasure",
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stream_to_logger=False,
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)
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if proc.returncode != 0:
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err = proc.stdout or ""
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raise RuntimeError(
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f"predict_weigth_from_svo2.py failed ({proc.returncode}): {err[-4000:]}"
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)
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def _summary_entry_matches_svo(item: Dict[str, Any], svo_path: Path) -> bool:
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stem = svo_path.stem
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resolved = str(svo_path.resolve())
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svo_key = item.get("svo")
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if svo_key:
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try:
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if Path(str(svo_key)).resolve() == svo_path.resolve():
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return True
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except OSError:
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pass
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if str(svo_key) == resolved:
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return True
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if item.get("svo_name") == stem:
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return True
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return False
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def _load_weight_json(svo_path: Path, settings: Settings) -> Dict[str, Any]:
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"""读取 FishMeasure 合并结果。优先 per-SVO 的 weight_prediction.json；否则从 weight_predictions_summary.json 取匹配项（predict 脚本在权重步失败时仍 exit 0 只写 summary）。"""
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stem = svo_path.stem
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root = settings.measure_output_root
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candidate = root / stem / "weight_prediction.json"
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if candidate.is_file():
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with open(candidate, encoding="utf-8") as f:
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return json.load(f)
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summary_path = root / "weight_predictions_summary.json"
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if summary_path.is_file():
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with open(summary_path, encoding="utf-8") as f:
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summary_list: Any = json.load(f)
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if isinstance(summary_list, list):
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for item in reversed(summary_list):
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if not isinstance(item, dict):
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continue
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if not _summary_entry_matches_svo(item, svo_path):
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continue
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err = item.get("error")
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if err:
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raise RuntimeError(
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f"FishMeasure 权重步骤失败（{svo_path.name}）: {err}"
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)
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if item.get("per_cloud") or item.get("per_file") or item.get(
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"dgcnn_summary"
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):
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return item
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break
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combined_path = root / "weight_prediction.json"
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if combined_path.is_file():
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with open(combined_path, encoding="utf-8") as f:
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combined: Any = json.load(f)
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if isinstance(combined, dict) and combined.get("combined"):
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names = combined.get("svo_names") or []
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if stem in names:
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return combined
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raise FileNotFoundError(
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f"未找到测量结果 JSON：{candidate}（且 summary 中无本条 SVO 的成功记录）"
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)
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_TID_RE = re.compile(r"_tid(\d+)")
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def _parse_tid_from_ply_name(name: str) -> Optional[int]:
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"""与 FishMeasure/fish_video_weight_evaluation._parse_tid_from_ply_name 一致。"""
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m = _TID_RE.search(name)
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return int(m.group(1)) if m else None
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def _safe_media_prefix(stem: str) -> str:
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s = re.sub(r"[^\w.\-]+", "_", stem, flags=re.UNICODE).strip("._") or "svo"
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return s[:120]
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def _result_from_weight_prediction(data: Dict[str, Any]) -> List[Dict[str, Any]]:
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"""按 track_id 聚合：体重取 max(predicted_weight_g)，体长取达到 max 的那条 PLY 的 length_input (mm)。"""
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items = data.get("per_cloud") or data.get("per_file") or []
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if not isinstance(items, list):
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return []
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# tid -> (max_weight_g, length_mm at max weight)
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best: Dict[int, Tuple[float, float]] = {}
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for it in items:
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if not isinstance(it, dict):
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continue
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ply = it.get("ply")
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if not ply:
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continue
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tid = _parse_tid_from_ply_name(Path(str(ply)).name)
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if tid is None:
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continue
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try:
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wg = float(it.get("predicted_weight_g", float("nan")))
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except (TypeError, ValueError):
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continue
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if not math.isfinite(wg):
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continue
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try:
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ln = float(it.get("length_input", float("nan")))
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except (TypeError, ValueError):
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ln = float("nan")
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if tid not in best or wg > best[tid][0]:
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best[tid] = (wg, ln)
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out: List[Dict[str, Any]] = []
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for tid in sorted(best.keys()):
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wg, ln = best[tid]
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if not math.isfinite(ln):
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continue
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out.append({"id": tid, "weight": wg, "length": ln})
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return out
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def _find_preview_videos(output_dir: Path) -> Tuple[Optional[Path], Optional[Path]]:
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previews = sorted(output_dir.rglob("*preview*.mp4"))
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if len(previews) >= 2:
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return previews[0], previews[1]
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all_mp4 = sorted(output_dir.rglob("*.mp4"))
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if len(all_mp4) >= 2:
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return all_mp4[0], all_mp4[1]
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if len(all_mp4) == 1:
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return all_mp4[0], all_mp4[0]
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if len(previews) == 1:
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return previews[0], previews[0]
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return None, None
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def _split_sbs_video(src: Path, left_dst: Path, right_dst: Path) -> bool:
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"""Split a side-by-side stereo video (W x H where W == 2*H_single) into left/right halves.
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Returns True if split succeeded, False otherwise (caller should fall back to copy).
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"""
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ffmpeg_path = _get_ffmpeg_path()
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ffprobe_path = str(Path(ffmpeg_path).parent / "ffprobe")
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probe = subprocess.run(
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[
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ffprobe_path, "-v", "quiet", "-print_format", "json",
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"-show_streams", str(src),
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],
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capture_output=True, text=True,
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)
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if probe.returncode != 0:
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return False
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import json as _json
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try:
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streams = _json.loads(probe.stdout).get("streams", [])
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vstream = next((s for s in streams if s.get("codec_type") == "video"), None)
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if vstream is None:
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return False
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w, h = int(vstream["width"]), int(vstream["height"])
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except Exception:
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return False
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half_w = w // 2
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if half_w < 1 or w < h:
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return False
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encoder, encoder_options, _ = _get_h264_encoder()
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for crop, dst in [
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(f"crop={half_w}:{h}:{half_w}:0", left_dst),
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(f"crop={half_w}:{h}:0:0", right_dst),
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]:
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cmd = [ffmpeg_path, "-y", "-i", str(src), "-vf", crop, "-an"]
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if encoder:
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cmd.extend(["-c:v", encoder, "-pix_fmt", "yuv420p", "-movflags", "+faststart"])
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cmd.extend(encoder_options)
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else:
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cmd.extend(["-q:v", "5"])
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cmd.append(str(dst))
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r = subprocess.run(cmd, capture_output=True, text=True)
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if r.returncode != 0:
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return False
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return True
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def _get_ffmpeg_path() -> str:
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"""获取可用的 ffmpeg 路径。优先使用项目配置的 ffmpeg。"""
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# 优先使用项目目录下的 ffmpeg
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project_ffmpeg = Path("/home/ubuntu/projects/FishServer/tools/ffmpeg/bin/ffmpeg")
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if project_ffmpeg.is_file():
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return str(project_ffmpeg)
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# 尝试系统路径
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system_paths = ["/usr/bin/ffmpeg", "/usr/local/bin/ffmpeg"]
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for path in system_paths:
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if Path(path).is_file():
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return path
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# 回退到 PATH 中的 ffmpeg
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return "ffmpeg"
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def _get_h264_encoder() -> tuple[str, list[str], str]:
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"""检测可用的H.264编码器，返回 (encoder_name, options, ffmpeg_path)。
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优先使用 libx264（纯软件，最可靠），硬件编码器需要实际测试才能确认可用。
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"""
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encoders_to_try = [
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("libx264", ["-preset", "fast", "-crf", "23"]),
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("h264_nvenc", ["-preset", "fast"]),
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("libopenh264", []),
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]
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ffmpeg_path = _get_ffmpeg_path()
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try:
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result = subprocess.run(
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[ffmpeg_path, "-encoders"],
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capture_output=True, text=True, timeout=10
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)
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encoders_output = result.stdout
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for encoder, options in encoders_to_try:
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if encoder in encoders_output:
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return encoder, options, ffmpeg_path
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except Exception:
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pass
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return "", [], ffmpeg_path
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def _get_x264_path() -> Optional[str]:
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"""检测系统上是否有可用的 x264 命令行工具。"""
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for path in ["/usr/bin/x264", "/usr/local/bin/x264", "x264"]:
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if path == "x264":
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try:
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result = subprocess.run(["which", "x264"], capture_output=True, text=True, timeout=5)
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if result.returncode == 0 and result.stdout.strip():
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return result.stdout.strip()
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except Exception:
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pass
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elif Path(path).is_file():
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return path
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return None
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def _transcode_with_x264(src: Path, dst: Path) -> bool:
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"""使用 x264 命令行工具将视频转码为 H.264。
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这是当 ffmpeg 的 H.264 编码器都不可用时（如 libopenh264 版本不匹配）的最后备选方案。
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通过 ffmpeg 提取原始 YUV 帧，然后用 x264 编码。
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"""
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import tempfile
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import shutil
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x264_path = _get_x264_path()
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ffmpeg_path = _get_ffmpeg_path()
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if not x264_path:
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logger.debug("[FishMeasure] x264 not available")
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return False
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# 首先用 ffprobe 获取视频信息
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try:
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probe = subprocess.run(
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["ffprobe", "-v", "quiet", "-print_format", "json", "-show_streams", str(src)],
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capture_output=True, text=True, timeout=10
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)
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import json as _json
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streams = _json.loads(probe.stdout).get("streams", [])
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vstream = next((s for s in streams if s.get("codec_type") == "video"), None)
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if not vstream:
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return False
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width = int(vstream["width"])
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height = int(vstream["height"])
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fps_str = vstream.get("r_frame_rate", "25/1")
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# 解析 fps (可能是 "30/1" 或 "30000/1001" 格式)
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if "/" in fps_str:
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num, den = map(int, fps_str.split("/"))
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fps = num / den if den != 0 else 25.0
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else:
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fps = float(fps_str)
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except Exception as e:
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logger.debug("[FishMeasure] x264 probe failed: {}", str(e))
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return False
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tmp_yuv = None
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try:
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# 创建临时 YUV 文件
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with tempfile.NamedTemporaryFile(suffix=".yuv", delete=False) as f:
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tmp_yuv = Path(f.name)
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# 步骤1: 用 ffmpeg 提取 YUV 原始帧
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extract_cmd = [
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ffmpeg_path, "-y", "-i", str(src),
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"-f", "rawvideo",
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"-pix_fmt", "yuv420p",
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str(tmp_yuv)
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]
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result = subprocess.run(extract_cmd, capture_output=True, text=True, timeout=300)
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if result.returncode != 0:
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logger.debug("[FishMeasure] x264: YUV extraction failed: {}", result.stderr[-200:] if result.stderr else "unknown")
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return False
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# 步骤2: 用 x264 编码
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# x264 需要特定格式的输入参数
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encode_cmd = [
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x264_path,
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"--input-res", f"{width}x{height}",
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"--fps", str(fps),
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"--preset", "fast",
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"--crf", "23",
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"--output-csp", "i420",
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"-o", str(dst),
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str(tmp_yuv)
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]
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result = subprocess.run(encode_cmd, capture_output=True, text=True, timeout=600)
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if result.returncode == 0 and dst.is_file():
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logger.info("[FishMeasure] x264 transcoding SUCCESS: {} ({} bytes)", dst.name, dst.stat().st_size)
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return True
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else:
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stderr = result.stderr[-300:] if result.stderr else "Unknown error"
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logger.warning("[FishMeasure] x264 transcoding FAILED: {}", stderr)
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if dst.exists():
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dst.unlink()
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return False
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except Exception as e:
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logger.warning("[FishMeasure] x264 transcoding exception: {}", str(e))
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if dst.exists():
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dst.unlink()
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return False
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finally:
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if tmp_yuv and tmp_yuv.exists():
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tmp_yuv.unlink()
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def _transcode_fallback(src: Path, dst: Path) -> bool:
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"""备选转码方案：提取帧为图像序列，然后用ffmpeg编码为H.264。
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这种方法避免编码器直接读取 mp4v 文件的兼容性问题。
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"""
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import tempfile
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import shutil
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encoder, encoder_options, ffmpeg_path = _get_h264_encoder()
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if not encoder:
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return False
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tmp_dir = tempfile.mkdtemp()
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try:
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# 步骤1: 提取帧为 jpg 序列
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frames_pattern = f"{tmp_dir}/frame_%04d.jpg"
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extract_cmd = [
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ffmpeg_path, "-y", "-i", str(src),
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"-q:v", "2", # 高质量
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frames_pattern
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]
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result = subprocess.run(extract_cmd, capture_output=True, text=True, timeout=60)
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if result.returncode != 0:
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logger.debug("[FishMeasure] Fallback: frame extraction failed: {}", result.stderr[-200:] if result.stderr else "unknown")
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return False
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# 步骤2: 从帧编码为 H.264 MP4
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encode_cmd = [
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ffmpeg_path, "-y",
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"-i", frames_pattern,
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"-c:v", encoder,
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"-pix_fmt", "yuv420p",
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"-movflags", "+faststart",
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"-an",
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]
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encode_cmd.extend(encoder_options)
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encode_cmd.append(str(dst))
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|
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result = subprocess.run(encode_cmd, capture_output=True, text=True, timeout=120)
|
||
|
||
if result.returncode == 0 and dst.is_file():
|
||
logger.info("[FishMeasure] Fallback transcoding SUCCESS: {} ({} bytes)", dst.name, dst.stat().st_size)
|
||
return True
|
||
else:
|
||
stderr = result.stderr[-300:] if result.stderr else "Unknown error"
|
||
logger.warning("[FishMeasure] Fallback transcoding FAILED: {}", stderr)
|
||
if dst.exists():
|
||
dst.unlink()
|
||
return False
|
||
except Exception as e:
|
||
logger.warning("[FishMeasure] Fallback transcoding exception: {}", str(e))
|
||
if dst.exists():
|
||
dst.unlink()
|
||
return False
|
||
finally:
|
||
# 清理临时目录
|
||
shutil.rmtree(tmp_dir, ignore_errors=True)
|
||
|
||
|
||
def _transcode_to_h264(src: Path, dst: Path) -> bool:
|
||
"""使用 ffmpeg 将视频转码为 H.264 (浏览器兼容格式)。
|
||
|
||
尝试多种H.264编码器，包括软件编码和硬件加速编码。
|
||
如果直接转码失败，依次尝试备选方案：
|
||
1. 提取帧重新编码
|
||
2. 使用 x264 命令行工具（当 ffmpeg 的 H.264 编码器都不可用时）
|
||
"""
|
||
encoder, encoder_options, ffmpeg_path = _get_h264_encoder()
|
||
|
||
# 如果有可用的 ffmpeg H.264 编码器，先尝试直接转码
|
||
if encoder:
|
||
try:
|
||
# 基础参数
|
||
cmd = [
|
||
ffmpeg_path, "-y", "-i", str(src),
|
||
"-c:v", encoder,
|
||
"-pix_fmt", "yuv420p", # 确保兼容性
|
||
"-movflags", "+faststart", # 优化网络播放（moov前置）
|
||
"-an", # 去除音频
|
||
]
|
||
cmd.extend(encoder_options)
|
||
cmd.append(str(dst))
|
||
|
||
logger.info("[FishMeasure] Transcoding with {} using {}: {} -> {}", encoder, ffmpeg_path, src.name, dst.name)
|
||
result = subprocess.run(
|
||
cmd, capture_output=True, text=True, timeout=300
|
||
)
|
||
|
||
if result.returncode == 0 and dst.is_file():
|
||
logger.info("[FishMeasure] Transcoding SUCCESS: {} ({} bytes)", dst.name, dst.stat().st_size)
|
||
return True
|
||
else:
|
||
stderr = result.stderr[-500:] if result.stderr else "Unknown error"
|
||
logger.warning("[FishMeasure] Direct transcoding FAILED, trying fallback: {}", stderr)
|
||
# 尝试备选方案1: 提取帧重新编码
|
||
if _transcode_fallback(src, dst):
|
||
return True
|
||
# 备选方案1失败，尝试 x264
|
||
logger.info("[FishMeasure] Fallback failed, trying x264...")
|
||
return _transcode_with_x264(src, dst)
|
||
except Exception as e:
|
||
logger.warning("[FishMeasure] Transcoding exception: {}", str(e))
|
||
if _transcode_fallback(src, dst):
|
||
return True
|
||
return _transcode_with_x264(src, dst)
|
||
else:
|
||
# 没有可用的 ffmpeg H.264 编码器，直接尝试 x264
|
||
logger.warning("[FishMeasure] No H.264 encoder available in ffmpeg, trying x264...")
|
||
return _transcode_with_x264(src, dst)
|
||
|
||
|
||
def _publish_media(
|
||
left: Optional[Path],
|
||
right: Optional[Path],
|
||
settings: Settings,
|
||
file_prefix: str,
|
||
) -> Tuple[str, str]:
|
||
settings.media_root.mkdir(parents=True, exist_ok=True)
|
||
safe_p = _safe_media_prefix(file_prefix)
|
||
left_dst = settings.media_root / f"{safe_p}_left.mp4"
|
||
right_dst = settings.media_root / f"{safe_p}_right.mp4"
|
||
base = settings.public_base_url.rstrip("/")
|
||
|
||
if left is not None and left == right and left.is_file():
|
||
if _split_sbs_video(left, left_dst, right_dst):
|
||
return (
|
||
f"{base}/media/{left_dst.name}",
|
||
f"{base}/media/{right_dst.name}",
|
||
)
|
||
|
||
def publish(src: Optional[Path], dst: Path) -> str:
|
||
if src is None or not src.is_file():
|
||
return ""
|
||
# 尝试转码为 H.264，如果失败则直接复制原文件
|
||
if _transcode_to_h264(src, dst):
|
||
logger.info("[FishMeasure] transcoded to H.264: {} -> {}", src.name, dst.name)
|
||
else:
|
||
# 转码失败，直接复制原文件
|
||
shutil.copy2(src, dst)
|
||
logger.warning("[FishMeasure] copied without transcoding: {} -> {}", src.name, dst.name)
|
||
return f"{base}/media/{dst.name}"
|
||
|
||
vl = publish(left, left_dst)
|
||
vr = publish(right, right_dst)
|
||
return vl, vr
|
||
|
||
|
||
def build_measure_snapshot(svo_path: Path, settings: Settings) -> MeasureSnapshot:
|
||
data = _load_weight_json(svo_path, settings)
|
||
summary = data.get("dgcnn_summary") or data.get("weight_summary") or {}
|
||
|
||
result = _result_from_weight_prediction(data)
|
||
|
||
if not result:
|
||
weight_g = summary.get("avg_predicted_weight_g")
|
||
length_mm = summary.get("avg_length_input_topk")
|
||
if weight_g is None:
|
||
weight_g = data.get("avg_predicted_weight_g")
|
||
if length_mm is None:
|
||
length_mm = summary.get("avg_length_input") or data.get("avg_length_input")
|
||
if weight_g is not None and length_mm is not None:
|
||
try:
|
||
w = float(weight_g)
|
||
l = float(length_mm)
|
||
if math.isfinite(w) and math.isfinite(l):
|
||
result = [{"id": 1, "weight": w, "length": l}]
|
||
except (TypeError, ValueError):
|
||
pass
|
||
|
||
logger.info(
|
||
"[FishMeasure] parsed {}\nresult ({} fish):\n{}\ndgcnn_summary:\n{}",
|
||
svo_path.name,
|
||
len(result),
|
||
format_json_pretty(result),
|
||
format_json_pretty(summary if summary else {}),
|
||
)
|
||
|
||
out_dir = Path(data.get("output_dir", settings.measure_output_root / svo_path.stem))
|
||
lv, rv = _find_preview_videos(out_dir)
|
||
prefix = (
|
||
f"{datetime.now(timezone.utc).strftime('%Y%m%dT%H%M%S')}_{svo_path.stem}"
|
||
)
|
||
v_left, v_right = _publish_media(lv, rv, settings, prefix)
|
||
logger.info(
|
||
"[FishMeasure] media preview_paths={} {} | published_left={} published_right={}",
|
||
lv,
|
||
rv,
|
||
v_left or "(none)",
|
||
v_right or "(none)",
|
||
)
|
||
|
||
return MeasureSnapshot(
|
||
result=result,
|
||
video_left=v_left,
|
||
video_right=v_right,
|
||
updated_at=datetime.now(timezone.utc),
|
||
raw_prediction_path=str(
|
||
settings.measure_output_root / svo_path.stem / "weight_prediction.json"
|
||
),
|
||
)
|
||
|
||
|
||
def run_full_measure(svo_path: Path, settings: Settings) -> MeasureSnapshot:
|
||
logger.info("[FishMeasure] start svo={}", svo_path.resolve())
|
||
run_measure_subprocess(svo_path, settings)
|
||
snap = build_measure_snapshot(svo_path, settings)
|
||
logger.info("[FishMeasure] done svo={} result_len={}", svo_path.name, len(snap.result))
|
||
return snap
|