?

fish_api/app/services/action.py

@@ -74,6 +74,7 @@ def run_action_subprocess(mp4_path: Path, settings: Settings) -> str:
             cwd=str(settings.fish_action_root),
             env=os.environ.copy(),
             log_name="FishAction",
+            stream_to_logger=False,
         )
         if proc.returncode != 0:
             err = proc.stdout or ""
@@ -87,7 +88,7 @@ def run_action_subprocess(mp4_path: Path, settings: Settings) -> str:
         if not rows:
             raise RuntimeError("Empty prediction JSON")
         pred_en = str(rows[0].get("pred_3class", "")).strip().lower()
-        logger.info(
+        logger.debug(
             "[FishAction] prediction row:\n{}",
             format_json_pretty(rows[0]),
         )

fish_api/app/services/measure.py

@@ -102,6 +102,7 @@ def run_measure_subprocess(svo_path: Path, settings: Settings) -> None:
         cwd=str(settings.fish_measure_root),
         env=os.environ.copy(),
         log_name="FishMeasure",
+        stream_to_logger=False,
     )
     if proc.returncode != 0:
         err = proc.stdout or ""
@@ -581,28 +582,28 @@ def build_measure_snapshot(svo_path: Path, settings: Settings) -> MeasureSnapsho
     data = _load_weight_json(svo_path, settings)
     summary = data.get("dgcnn_summary") or data.get("weight_summary") or {}
 
-    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")
+    result = _result_from_weight_prediction(data)
 
-    result: List[Dict[str, Any]] = []
-    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
+    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 {}\navg_weight_g(top5)={} avg_length_mm(top5)={}\nresult:\n{}\ndgcnn_summary:\n{}",
+        "[FishMeasure] parsed {}\nresult ({} fish):\n{}\ndgcnn_summary:\n{}",
         svo_path.name,
-        weight_g,
-        length_mm,
+        len(result),
         format_json_pretty(result),
         format_json_pretty(summary if summary else {}),
     )

fish_api/app/subprocess_run.py

@@ -1,4 +1,4 @@
-"""子进程运行并把 stdout/stderr 流式写入 loguru，便于查看 FishMeasure / FishAction 中间输出。"""
+"""子进程运行并把 stdout/stderr 合并；可选将逐行输出写入 loguru（测量/行为推理可关闭以减少日志）。"""
 
 from __future__ import annotations
 
@@ -15,10 +15,12 @@ def run_subprocess_with_log(
     cwd: str,
     env: Optional[Dict[str, str]] = None,
     log_name: str,
+    stream_to_logger: bool = True,
 ) -> subprocess.CompletedProcess[str]:
-    """运行子进程，合并 stderr 到 stdout，按行输出到 loguru。
+    """运行子进程，合并 stderr 到 stdout，可选按行输出到 loguru。
 
     返回 CompletedProcess，stdout 为完整输出，便于失败时拼进异常信息。
+    ``stream_to_logger=False`` 时不把子进程逐行写入日志（仍完整收集 stdout）。
     """
     proc = subprocess.Popen(
         cmd,
@@ -33,9 +35,10 @@ def run_subprocess_with_log(
     if proc.stdout is not None:
         for line in proc.stdout:
             lines.append(line)
-            s = line.rstrip()
-            if s:
-                logger.info("[{}] {}", log_name, s)
+            if stream_to_logger:
+                s = line.rstrip()
+                if s:
+                    logger.info("[{}] {}", log_name, s)
     rc = proc.wait()
     out = "".join(lines)
     return subprocess.CompletedProcess(cmd, rc, out, "")