feat(fish_api): SQLite 快照投递、日志与 watch 空闲告警

- 新增 SQLite：measure/health 快照、delivery_cursor 单消费者 pop；clear/start_fresh 可清空库
- biomass GET 仅返回约定 data 字段，X-Fish-Biomass-New 表示是否有新快照；poller 读响应头
- loguru 桥接 uvicorn，子进程 stdout 流式输出；format_json_pretty 与算法摘要日志
- measure/action watch 无新任务时限流 WARNING；watch_idle 共用逻辑
- 依赖 loguru；新增 db、logging_config、subprocess_run、watch_idle、启动脚本

FishMeasure: 更新 fish_video_weight_evaluation 与 predict_weigth_from_svo2；移除未用 refbox/segmentation 脚本
Made-with: Cursor

fish_api/app/services/measure.py

@@ -7,16 +7,61 @@ import subprocess
 import sys
 from datetime import date, datetime, timezone
 from pathlib import Path
-from typing import Any, Dict, Optional, Tuple
+from typing import Any, Dict, List, Optional, Tuple
 
+from app.logging_config import format_json_pretty
 from app.settings import Settings
 from app.state import MeasureSnapshot
+from app.subprocess_run import run_subprocess_with_log
+from loguru import logger
 
 
 def _py_exe(settings: Settings) -> str:
     return settings.python_fish_measure or sys.executable
 
 
+def _predict_weigth_from_svo2_extra_args(settings: Settings) -> List[str]:
+    """Flags aligned with FishMeasure/predict_weigth_from_svo2.py CLI."""
+    out: List[str] = []
+    if settings.predict_filter_pointcloud:
+        out.append("--filter-pointcloud")
+    if settings.predict_use_density_filter:
+        out.append("--use-density-filter")
+    if settings.predict_use_clustering_filter:
+        out.append("--use-clustering-filter")
+    if (
+        settings.predict_use_pointcloud_classifier
+        and settings.predict_pointcloud_classifier
+        and Path(settings.predict_pointcloud_classifier).is_file()
+    ):
+        out.extend(
+            [
+                "--pointcloud-classifier",
+                settings.predict_pointcloud_classifier,
+                "--use-pointcloud-classifier",
+                "--pointcloud-classifier-threshold",
+                str(settings.predict_pointcloud_classifier_threshold),
+            ]
+        )
+    if settings.predict_use_flatness_filter:
+        out.append("--use-flatness-filter")
+        out.extend(["--flatness-threshold", str(settings.predict_flatness_threshold)])
+    out.extend(["--weight-top-k", str(settings.measure_weight_top_k)])
+    if settings.measure_weight_top_by_length:
+        out.append("--weight-top-by-length")
+    else:
+        out.append("--no-weight-top-by-length")
+    if settings.predict_fish_video_weight_overlay:
+        out.extend(
+            [
+                "--fish-video-weight-overlay",
+                "--minute-interval-sec",
+                str(settings.predict_minute_interval_sec),
+            ]
+        )
+    return out
+
+
 def run_measure_subprocess(svo_path: Path, settings: Settings) -> None:
     script = settings.fish_measure_root / "predict_weigth_from_svo2.py"
     if not script.is_file():
@@ -46,16 +91,16 @@ def run_measure_subprocess(svo_path: Path, settings: Settings) -> None:
         "--frame-stride",
         str(settings.predict_frame_stride),
     ]
+    cmd.extend(_predict_weigth_from_svo2_extra_args(settings))
 
-    proc = subprocess.run(
+    proc = run_subprocess_with_log(
         cmd,
         cwd=str(settings.fish_measure_root),
         env=os.environ.copy(),
-        capture_output=True,
-        text=True,
+        log_name="FishMeasure",
     )
     if proc.returncode != 0:
-        err = (proc.stderr or "") + (proc.stdout or "")
+        err = proc.stdout or ""
         raise RuntimeError(
             f"predict_weigth_from_svo2.py failed ({proc.returncode}): {err[-4000:]}"
         )
@@ -171,9 +216,28 @@ def build_measure_snapshot(svo_path: Path, settings: Settings) -> MeasureSnapsho
         "date": today,
     }
 
+    logger.info(
+        "[FishMeasure] parsed {}\navg_length_mm={} avg_weight_g={}\nweight_summary:\n{}",
+        svo_path.name,
+        length_mm,
+        weight_g,
+        format_json_pretty(summary if summary else {}),
+    )
+    logger.info(
+        "[FishMeasure] API result_item:\n{}",
+        format_json_pretty(result_item),
+    )
+
     out_dir = Path(data.get("output_dir", settings.measure_output_root / svo_path.stem))
     lv, rv = _find_preview_videos(out_dir)
     v_left, v_right = _publish_media(lv, rv, settings)
+    logger.info(
+        "[FishMeasure] media preview_paths={} {} | published_left={} published_right={}",
+        lv,
+        rv,
+        v_left or "(none)",
+        v_right or "(none)",
+    )
 
     return MeasureSnapshot(
         result=[result_item],
@@ -187,5 +251,8 @@ def build_measure_snapshot(svo_path: Path, settings: Settings) -> MeasureSnapsho
 
 
 def run_full_measure(svo_path: Path, settings: Settings) -> MeasureSnapshot:
+    logger.info("[FishMeasure] start svo={}", svo_path.resolve())
     run_measure_subprocess(svo_path, settings)
-    return build_measure_snapshot(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