From 89b67fbd34179d4e33444265e88a6b0768801125 Mon Sep 17 00:00:00 2001 From: duxin Date: Tue, 28 Jul 2026 14:59:11 +0800 Subject: [PATCH] =?UTF-8?q?fix:=20ML=20Pipeline=20=E7=BC=BA=E5=A4=B1?= =?UTF-8?q?=E5=80=BC=E5=A1=AB=E5=85=85=20+=20=E6=8E=A8=E7=90=86=E7=AB=AF?= =?UTF-8?q?=E5=A4=96=E9=83=A8=E6=A8=A1=E5=9E=8B=20dict=20=E5=85=BC?= =?UTF-8?q?=E5=AE=B9?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit - 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/core/modeling/modeling_batch.py | 2 ++ src/core/prediction/inference_batch.py | 12 +++++++++--- src/gui/panels/step9_ml_predict_panel.py | 7 ++++--- 3 files changed, 15 insertions(+), 6 deletions(-) diff --git a/src/core/modeling/modeling_batch.py b/src/core/modeling/modeling_batch.py index ceac44d..58e5b86 100644 --- a/src/core/modeling/modeling_batch.py +++ b/src/core/modeling/modeling_batch.py @@ -20,6 +20,7 @@ from sklearn.ensemble import GradientBoostingRegressor, AdaBoostRegressor, Extra from sklearn.tree import DecisionTreeRegressor from sklearn.neural_network import MLPRegressor from sklearn.pipeline import Pipeline +from sklearn.impute import SimpleImputer from joblib import parallel_backend # 第三方模型导入 # try: @@ -611,6 +612,7 @@ class WaterQualityModelingBatch: # ============ 关键：把预处理器塞进 Pipeline ============ preproc = get_preprocessing_transformer(preprocess_method) pipeline = Pipeline([ + ('imputer', SimpleImputer(strategy='median')), ('preproc', preproc), ('model', base_model), ]) diff --git a/src/core/prediction/inference_batch.py b/src/core/prediction/inference_batch.py index d4b1c68..b392bc0 100644 --- a/src/core/prediction/inference_batch.py +++ b/src/core/prediction/inference_batch.py @@ -48,9 +48,15 @@ class WaterQualityInference: # 规范化 loaded_model_data：始终为 dict，确保 ['model'] 访问不崩溃 if external_model is not None: - # 外部传入的是裸模型对象 → 包装为 dict，统一后续 .get('model') 访问 - self.loaded_model_data = {'model': external_model, 'preprocess_method': 'None'} - print(f" 外部模型已规范化: type={type(external_model).__name__}") + # ★ 外部模型可能是完整 dict（含 model + metadata + train_wavelengths）， + # 也可能是裸 Pipeline 对象（旧版兼容） + if isinstance(external_model, dict) and 'model' in external_model: + self.loaded_model_data = external_model + print(f" 外部模型已规范化: dict (含 metadata)") + else: + self.loaded_model_data = {'model': external_model, + 'preprocess_method': 'None'} + print(f" 外部模型已规范化: type={type(external_model).__name__}") else: self.loaded_model_data = None diff --git a/src/gui/panels/step9_ml_predict_panel.py b/src/gui/panels/step9_ml_predict_panel.py index 0b5daf3..dfe7217 100644 --- a/src/gui/panels/step9_ml_predict_panel.py +++ b/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}")