?

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 {}),
     )