fix: ML Pipeline 缺失值填充 + 推理端外部模型 dict 兼容

- modeling_batch: Pipeline 首步新增 SimpleImputer(median) 填充 NaN
- inference_batch: 外部模型支持完整 dict（含 metadata/train_wavelengths），
  兼容旧版裸 Pipeline 对象
- step9_ml_predict_panel: 模型加载保留完整 dict 而非仅 model 对象，
  确保推理端可从 train_wavelengths 做光谱重采样

src/gui/panels/step9_ml_predict_panel.py

@@ -253,13 +253,14 @@ class Step9MlPredictPanel(QWidget):
                 try:
                     loaded = joblib.load(joblib_path)
                     if isinstance(loaded, dict) and "model" in loaded:
-                        model_obj = loaded["model"]
+                        # ★ 保留完整 dict（含 metadata / train_wavelengths），
+                        #   推理端需要 train_wavelengths 做光谱重采样
+                        models_found[subdir_name] = loaded
                     elif hasattr(loaded, "predict"):
-                        model_obj = loaded
+                        models_found[subdir_name] = loaded
                     else:
                         errors.append(f"{subdir_name}: 无法识别的格式 {type(loaded).__name__}")
                         continue
-                    models_found[subdir_name] = model_obj
                 except Exception as e:
                     errors.append(f"{subdir_name}: {type(e).__name__}: {e}")