界面优化

src/core/water_quality_inversion_pipeline_GUI.py

@@ -989,7 +989,12 @@ class WaterQualityInversionPipeline:
         if not GDAL_AVAILABLE:
             raise ImportError("GDAL未安装，无法保存影像文件")
         
-        height, width, n_bands = image_array.shape
+        # 兼容 (H,W) 和 (H,W,C) 两种 shape 格式
+        if image_array.ndim == 2:
+            height, width = image_array.shape
+            n_bands = 1
+        else:
+            height, width, n_bands = image_array.shape
         
         # 获取驱动
         driver = gdal.GetDriverByName('ENVI')
@@ -1100,11 +1105,8 @@ class WaterQualityInversionPipeline:
         Returns:
             numpy数组或None，1表示水域，0表示非水域
         """
-        # 获取图像尺寸
+        # 获取图像尺寸（统一从 shape 元组中提取前两个维度，兼容 (H,W)、(H,W,C)、(B,H,W) 等多种格式）
-        if isinstance(image_shape, np.ndarray):
+        img_height, img_width = image_shape[0], image_shape[1]
-            img_height, img_width = image_shape.shape[:2]
-        else:
-            img_height, img_width = image_shape
         
         if water_mask is None:
             # 如果water_mask为None，使用步骤1生成的dat格式掩膜
@@ -1362,6 +1364,19 @@ class WaterQualityInversionPipeline:
                     interpolated_bands.append(band_data)
                     continue
                 
+                # 兼容中文和各种格式
+                raw_interp = str(interpolation_method).lower()
+                if 'nearest' in raw_interp or '邻近' in raw_interp or '最邻近' in raw_interp:
+                    interpolation_method = 'nearest'
+                elif 'bilinear' in raw_interp or '线性' in raw_interp or '双线性' in raw_interp:
+                    interpolation_method = 'bilinear'
+                elif 'spline' in raw_interp or '样条' in raw_interp or 'rbf' in raw_interp:
+                    interpolation_method = 'spline'
+                elif 'kriging' in raw_interp or '克里金' in raw_interp:
+                    interpolation_method = 'kriging'
+                else:
+                    interpolation_method = 'nearest'
+
                 # 对需要插值的像素进行插值
                 if interpolation_method == 'nearest':
                     # 邻近插值
@@ -1591,6 +1606,18 @@ class WaterQualityInversionPipeline:
         
         step_start_time = time.time()
         try:
+            # 兼容中文和各种格式
+            raw_method = str(method).lower()
+            if 'kutser' in raw_method:
+                method = 'kutser'
+            elif 'goodman' in raw_method:
+                method = 'goodman'
+            elif 'hedley' in raw_method:
+                method = 'hedley'
+            elif 'sugar' in raw_method:
+                method = 'sugar'
+            # 其余方法（subtract_nir, regression_slope, oxygen_absorption）保持原值
+
             # 如果未启用，直接跳过处理并把原始影像路径作为后续流程输入
             if not enabled:
                 print("已设置跳过去除耀斑（enabled=False），将直接使用原始影像。")
@@ -1807,6 +1834,16 @@ class WaterQualityInversionPipeline:
                 del corrected_bands
                 
             elif method == "sugar":
+                # 强行转换暗号，兼容中文和各种格式
+                raw_method = str(sugar_glint_mask_method).lower()
+                if 'cdf' in raw_method or '累积' in raw_method:
+                    sugar_glint_mask_method = 'cdf'
+                elif 'otsu' in raw_method or '大津' in raw_method:
+                    sugar_glint_mask_method = 'otsu'
+                else:
+                    # 默认回退到 cdf 确保不崩溃
+                    sugar_glint_mask_method = 'cdf'
+
                 print(f"使用方法: SUGAR (迭代次数={sugar_iter}, 掩膜方法={sugar_glint_mask_method})")
                 
                 # 确定输出路径
@@ -3603,6 +3640,29 @@ class WaterQualityInversionPipeline:
         Returns:
             预处理后的CSV文件路径
         """
+        # 兼容中文和各种格式
+        raw_p = str(preprocess_method).lower()
+        if raw_p == 'none' or '无' in raw_p or '跳过' in raw_p:
+            preprocess_method = 'None'
+        elif raw_p == 'mms' or 'minmax' in raw_p or '最大最小' in raw_p:
+            preprocess_method = 'MMS'
+        elif raw_p == 'ss' or '标准' in raw_p or '标准化' in raw_p:
+            preprocess_method = 'SS'
+        elif raw_p == 'snv' or '标准正态' in raw_p:
+            preprocess_method = 'SNV'
+        elif raw_p == 'ma' or '移动' in raw_p:
+            preprocess_method = 'MA'
+        elif raw_p == 'sg' or 'savitzky' in raw_p or '平滑' in raw_p:
+            preprocess_method = 'SG'
+        elif raw_p == 'msc' or '多元散射' in raw_p:
+            preprocess_method = 'MSC'
+        elif raw_p == 'd1' or 'd2' or 'dt' or '导数' in raw_p:
+            preprocess_method = {'d1': 'D1', 'd2': 'D2', 'dt': 'DT'}.get(raw_p, raw_p.upper())
+        elif raw_p == 'ct' or '去趋势' in raw_p:
+            preprocess_method = 'CT'
+        else:
+            preprocess_method = preprocess_method  # 保持原值
+
         # 如果不需要预处理，直接返回原文件
         if preprocess_method == 'None':
             return csv_path

src/gui/panels/report_generation_panel.py

@@ -195,13 +195,23 @@ class ReportGenerationPanel(QWidget):
             self.text_model_edit.setText(self.vision_model_edit.text())
             self.text_model_edit.blockSignals(False)
 
+    def _get_default_work_dir(self):
+        """获取 work_dir，优先用主窗口缓存的 work_dir"""
+        if self.main_window and hasattr(self.main_window, 'work_dir') and self.main_window.work_dir:
+            return str(self.main_window.work_dir)
+        return ""
+
     def browse_work_dir(self):
-        d = QFileDialog.getExistingDirectory(self, "选择工作目录")
+        default = self._get_default_work_dir()
+        d = QFileDialog.getExistingDirectory(self, "选择工作目录", default)
         if d:
             self.work_dir_edit.setText(d)
 
     def browse_output_dir(self):
-        d = QFileDialog.getExistingDirectory(self, "选择报告输出目录")
+        default = self._get_default_work_dir()
+        if default:
+            default = os.path.join(default, "14_visualization")
+        d = QFileDialog.getExistingDirectory(self, "选择报告输出目录", default)
         if d:
             self.output_dir_edit.setText(d)
 

src/gui/panels/step4_panel.py

@@ -168,7 +168,10 @@ class Step4Panel(QWidget):
 
         try:
             rows_to_preview = max(1, self.preview_rows_spin.value())
-            df = pd.read_csv(csv_path, nrows=rows_to_preview)
+            # dtype=object 确保所有列以字符串读取，避免空值/混合类型导致 dtype 报错
+            df = pd.read_csv(csv_path, nrows=rows_to_preview, dtype=object)
+            # fillna 在 PandasTableModel.__init__ 中已执行，此处再次防御性处理
+            df = df.fillna('')
             if df.empty:
                 self.reset_preview("CSV文件为空")
                 return

src/gui/panels/step5_panel.py

@@ -191,6 +191,15 @@ class Step5Panel(QWidget):
         else:
             self.output_file.set_path("")
 
+        # 5. 尝试从 Step4 界面读取已处理的水质参数 CSV 路径，自动填入本面板
+        main_window = self.window()
+        if main_window and hasattr(main_window, 'step4_panel'):
+            step4_output_path = main_window.step4_panel.output_file.get_path()
+            if step4_output_path:
+                existing_csv = self.csv_file.get_path()
+                if not existing_csv or not existing_csv.strip():
+                    self.csv_file.set_path(step4_output_path)
+
     def run_step(self):
         """独立运行步骤5"""
         # 验证输入

src/gui/panels/step6_5_panel.py

@@ -211,9 +211,52 @@ class Step6_5Panel(QWidget):
         if 'csv_path' in config:
             self.training_csv_file.set_path(config['csv_path'])
 
+    def update_from_config(self, work_dir=None, pipeline=None):
+        """从全局配置自动填充训练数据和输出路径
+
+        Args:
+            work_dir: 工作目录路径
+            pipeline: Pipeline 实例（未使用，保留接口兼容性）
+        """
+        if work_dir:
+            self.work_dir = work_dir
+        elif hasattr(self, 'work_dir') and self.work_dir:
+            pass
+        else:
+            self.work_dir = None
+
+        # 1. 尝试从 Step5 界面读取训练光谱 CSV 路径
+        main_window = self.window()
+        if main_window and hasattr(main_window, 'step5_panel'):
+            step5_output_path = main_window.step5_panel.output_file.get_path()
+            if step5_output_path:
+                existing = self.training_csv_file.get_path()
+                if not existing or not existing.strip():
+                    self.training_csv_file.set_path(step5_output_path)
+
+        # 2. 自动填充输出目录（8_Regression_Modeling）
+        if self.work_dir:
+            output_dir = os.path.join(self.work_dir, "8_Regression_Modeling")
+            os.makedirs(output_dir, exist_ok=True)
+            existing_out = self.output_dir.get_path()
+            if not existing_out or not existing_out.strip():
+                self.output_dir.set_path(output_dir)
+
+    def _get_default_work_dir(self):
+        """获取 work_dir，优先用 panel 自身缓存的，否则尝试从主窗口取"""
+        if hasattr(self, 'work_dir') and self.work_dir:
+            return str(self.work_dir)
+        mw = self.window()
+        if mw and hasattr(mw, 'work_dir') and mw.work_dir:
+            return str(mw.work_dir)
+        return ""
+
     def browse_output_dir(self):
         """浏览输出目录"""
-        dir_path = QFileDialog.getExistingDirectory(self, "选择输出模型目录", "")
+        default = self._get_default_work_dir()
+        if default:
+            default = os.path.join(default, "8_Regression_Modeling")
+        dir_path = QFileDialog.getExistingDirectory(self, "选择输出模型目录", default)
         if dir_path:
             self.output_dir.set_path(dir_path)
 

src/gui/panels/step6_75_panel.py

@@ -280,6 +280,37 @@ class Step6_75Panel(QWidget):
         if 'enabled' in config:
             self.enable_checkbox.setChecked(config['enabled'])
 
+    def update_from_config(self, work_dir=None, pipeline=None):
+        """从全局配置自动填充训练数据和输出路径
+
+        Args:
+            work_dir: 工作目录路径
+            pipeline: Pipeline 实例（未使用，保留接口兼容性）
+        """
+        if work_dir:
+            self.work_dir = work_dir
+        elif hasattr(self, 'work_dir') and self.work_dir:
+            pass
+        else:
+            self.work_dir = None
+
+        # 1. 尝试从 Step5 界面读取训练光谱 CSV 路径
+        main_window = self.window()
+        if main_window and hasattr(main_window, 'step5_panel'):
+            step5_output_path = main_window.step5_panel.output_file.get_path()
+            if step5_output_path:
+                existing = self.csv_file.get_path()
+                if not existing or not existing.strip():
+                    self.csv_file.set_path(step5_output_path)
+
+        # 2. 自动填充输出目录（9_Custom_Regression_Modeling）
+        if self.work_dir:
+            output_dir = os.path.join(self.work_dir, "9_Custom_Regression_Modeling")
+            os.makedirs(output_dir, exist_ok=True)
+            existing_out = self.output_dir.text().strip()
+            if not existing_out:
+                self.output_dir.setText(output_dir)
+
     def run_step(self):
         """独立运行步骤6.75"""
         csv_path = self.csv_file.get_path()

src/gui/panels/step6_panel.py

@@ -42,15 +42,15 @@ class Step6Panel(QWidget):
         layout.addWidget(self.ml_page)
 
         # 输出文件路径
-        self.output_dir = FileSelectWidget(
+        self.output_path = FileSelectWidget(
-            "输出模型目录:",
+            "输出文件:",
-            "Directories;;All Files (*.*)"
+            "CSV Files (*.csv);;All Files (*.*)",
+            mode="save"
         )
-        self.output_dir.line_edit.setPlaceholderText("models_output")
+        self.output_path.line_edit.setPlaceholderText("自动生成，或手动指定输出文件路径...")
-        # 修改浏览按钮为选择目录
+        self.output_path.browse_btn.clicked.disconnect()
-        self.output_dir.browse_btn.clicked.disconnect()
+        self.output_path.browse_btn.clicked.connect(self.browse_output_path)
-        self.output_dir.browse_btn.clicked.connect(self.browse_output_dir)
+        layout.addWidget(self.output_path)
-        layout.addWidget(self.output_dir)
 
         # 启用步骤
         self.enable_checkbox = QCheckBox("启用此步骤")
@@ -198,11 +198,38 @@ class Step6Panel(QWidget):
         for checkbox in checkboxes_dict.values():
             checkbox.setChecked(checked)
 
-    def browse_output_dir(self):
+    def _get_default_work_dir(self):
-        """浏览输出目录"""
+        """获取 work_dir，优先用 panel 自身缓存的，否则尝试从主窗口取"""
-        dir_path = QFileDialog.getExistingDirectory(self, "选择输出模型目录", "")
+        if hasattr(self, 'work_dir') and self.work_dir:
-        if dir_path:
+            return str(self.work_dir)
-            self.output_dir.set_path(dir_path)
+        mw = self.window()
+        if mw and hasattr(mw, 'work_dir') and mw.work_dir:
+            return str(mw.work_dir)
+        return ""
+
+    def browse_output_path(self):
+        """浏览输出文件路径（保存对话框）"""
+        current = self.output_path.get_path().strip()
+        if current:
+            initial_dir = os.path.dirname(current)
+            initial_file = os.path.basename(current)
+        else:
+            initial_dir = ""
+            initial_file = ""
+
+        if not initial_dir or not os.path.isdir(initial_dir):
+            # 默认定位到 indices 目录
+            work_dir = self._get_default_work_dir()
+            initial_dir = os.path.join(work_dir, "6_water_quality_indices") if work_dir else ""
+            if initial_dir and not os.path.isdir(initial_dir):
+                os.makedirs(initial_dir, exist_ok=True)
+
+        file_path, _ = QFileDialog.getSaveFileName(
+            self, "保存输出文件", os.path.join(initial_dir, initial_file) if initial_file else initial_dir,
+            "CSV Files (*.csv);;All Files (*.*)"
+        )
+        if file_path:
+            self.output_path.set_path(file_path)
 
     def get_config(self):
         """获取配置"""
@@ -229,7 +256,9 @@ class Step6Panel(QWidget):
         training_csv_path = self.training_csv_file.get_path()
         if training_csv_path:
             config['training_csv_path'] = training_csv_path
-        # 注意：step6_train_models 不接受 output_dir 参数，输出目录由 pipeline 内部根据 work_dir 生成
+        output_path = self.output_path.get_path()
+        if output_path:
+            config['output_path'] = output_path
         return config
 
     def set_config(self, config):
@@ -252,8 +281,8 @@ class Step6Panel(QWidget):
                 checkbox.setChecked(method in methods)
         if 'training_csv_path' in config:
             self.training_csv_file.set_path(config['training_csv_path'])
-        if 'output_dir' in config:
+        if 'output_path' in config:
-            self.output_dir.set_path(config['output_dir'])
+            self.output_path.set_path(config['output_path'])
 
     def update_from_config(self, work_dir=None, pipeline=None):
         """从全局配置自动填充训练数据和输出路径
@@ -288,13 +317,22 @@ class Step6Panel(QWidget):
                 if step5_csv:
                     self.training_csv_file.set_path(step5_csv)
 
-        # 2. 自动填充输出目录（基于工作目录）
+        # 2. 自动填充输出文件路径（基于工作目录和输入文件名）
+        # 输入是 training_spectra.csv → 输出 {work_dir}/6_water_quality_indices/training_spectra_indices.csv
+        # 输入是 sampling_spectra.csv   → 输出 {work_dir}/6_water_quality_indices/sampling_spectra_indices.csv
         if self.work_dir:
-            output_dir = os.path.join(self.work_dir, "7_Supervised_Model_Training")
+            indices_dir = os.path.join(self.work_dir, "6_water_quality_indices")
-            os.makedirs(output_dir, exist_ok=True)
+            os.makedirs(indices_dir, exist_ok=True)
-            self.output_dir.set_path(output_dir.replace('\\', '/'))
+            training_csv = self.training_csv_file.get_path()
+            if training_csv:
+                basename = os.path.splitext(os.path.basename(training_csv))[0]
+                output_file = f"{basename}_indices.csv"
+            else:
+                output_file = "water_quality_indices.csv"
+            output_path = os.path.join(indices_dir, output_file).replace('\\', '/')
+            self.output_path.set_path(output_path)
         else:
-            self.output_dir.set_path("")
+            self.output_path.set_path("")
 
     def run_step(self):
         """独立运行步骤6"""

src/gui/panels/step8_5_panel.py

@@ -4,6 +4,9 @@
 Step8_5 面板 - 非经验模型预测
 """
 
+import os
+from pathlib import Path
+
 from PyQt5.QtWidgets import (
     QWidget, QVBoxLayout, QGroupBox, QFormLayout,
     QPushButton, QCheckBox, QComboBox, QLineEdit, QMessageBox,
@@ -79,15 +82,70 @@ class Step8_5Panel(QWidget):
         layout.addStretch()
         self.setLayout(layout)
 
+    def update_from_config(self, work_dir=None, pipeline=None):
+        """从全局配置自动填充采样光谱和回归模型目录
+
+        Args:
+            work_dir: 工作目录路径
+            pipeline: Pipeline 实例（未使用，保留接口兼容性）
+        """
+        if work_dir:
+            self.work_dir = work_dir
+        elif hasattr(self, 'work_dir') and self.work_dir:
+            pass
+        else:
+            self.work_dir = None
+
+        main_window = self.window()
+
+        # 1. 尝试从 Step7 界面读取全湖采样点 CSV 路径
+        if main_window and hasattr(main_window, 'step7_panel'):
+            step7_output_path = main_window.step7_panel.output_file.get_path()
+            if step7_output_path:
+                existing = self.sampling_csv_file.get_path()
+                if not existing or not existing.strip():
+                    self.sampling_csv_file.set_path(step7_output_path)
+
+        # 2. 尝试从 Step6.5 界面读取回归模型目录
+        if main_window and hasattr(main_window, 'step6_5_panel'):
+            step6_5_models_dir = main_window.step6_5_panel.output_dir.get_path()
+            if step6_5_models_dir:
+                existing_models = self.models_dir_file.get_path()
+                if not existing_models or not existing_models.strip():
+                    self.models_dir_file.set_path(step6_5_models_dir)
+
+        # 3. 自动填充输出路径（非经验模型预测目录）
+        if self.work_dir:
+            output_dir = os.path.join(self.work_dir, "11_12_13_predictions/Non_Empirical_Prediction")
+            os.makedirs(output_dir, exist_ok=True)
+            existing_out = self.output_file.get_path()
+            if not existing_out or not existing_out.strip():
+                self.output_file.set_path(output_dir)
+
+    def _get_default_work_dir(self):
+        """获取 work_dir，优先用 panel 自身缓存的，否则尝试从主窗口取"""
+        if hasattr(self, 'work_dir') and self.work_dir:
+            return str(self.work_dir)
+        mw = self.window()
+        if mw and hasattr(mw, 'work_dir') and mw.work_dir:
+            return str(mw.work_dir)
+        return ""
+
     def browse_models_dir(self):
         """浏览模型目录"""
-        dir_path = QFileDialog.getExistingDirectory(self, "选择模型目录", "")
+        default = self._get_default_work_dir()
+        if default:
+            default = os.path.join(default, "8_Regression_Modeling")
+        dir_path = QFileDialog.getExistingDirectory(self, "选择模型目录", default)
         if dir_path:
             self.models_dir_file.set_path(dir_path)
 
     def browse_output_dir(self):
         """浏览输出目录"""
-        dir_path = QFileDialog.getExistingDirectory(self, "选择输出文件夹", "")
+        default = self._get_default_work_dir()
+        if default:
+            default = os.path.join(default, "11_12_13_predictions/Non_Empirical_Prediction")
+        dir_path = QFileDialog.getExistingDirectory(self, "选择输出文件夹", default)
         if dir_path:
             self.output_file.set_path(dir_path)
 

src/gui/panels/step8_75_panel.py

@@ -4,6 +4,8 @@
 Step8_75 面板 - 自定义回归预测
 """
 
+import os
+
 from PyQt5.QtWidgets import (
     QWidget, QVBoxLayout, QGroupBox,
     QPushButton, QCheckBox, QMessageBox, QFileDialog,
@@ -73,15 +75,70 @@ class Step8_75Panel(QWidget):
         layout.addStretch()
         self.setLayout(layout)
 
+    def update_from_config(self, work_dir=None, pipeline=None):
+        """从全局配置自动填充采样光谱和自定义回归模型目录
+
+        Args:
+            work_dir: 工作目录路径
+            pipeline: Pipeline 实例（未使用，保留接口兼容性）
+        """
+        if work_dir:
+            self.work_dir = work_dir
+        elif hasattr(self, 'work_dir') and self.work_dir:
+            pass
+        else:
+            self.work_dir = None
+
+        main_window = self.window()
+
+        # 1. 尝试从 Step7 界面读取全湖采样点 CSV 路径
+        if main_window and hasattr(main_window, 'step7_panel'):
+            step7_output_path = main_window.step7_panel.output_file.get_path()
+            if step7_output_path:
+                existing = self.sampling_csv_file.get_path()
+                if not existing or not existing.strip():
+                    self.sampling_csv_file.set_path(step7_output_path)
+
+        # 2. 尝试从 Step6.75 界面读取自定义回归模型目录
+        if main_window and hasattr(main_window, 'step6_75_panel'):
+            step6_75_models_dir = main_window.step6_75_panel.output_dir.text().strip()
+            if step6_75_models_dir:
+                existing_models = self.regression_models_dir.get_path()
+                if not existing_models or not existing_models.strip():
+                    self.regression_models_dir.set_path(step6_75_models_dir)
+
+        # 3. 自动填充输出目录（自定义回归预测目录）
+        if self.work_dir:
+            output_dir = os.path.join(self.work_dir, "11_12_13_predictions/Custom_Regression_Prediction")
+            os.makedirs(output_dir, exist_ok=True)
+            existing_out = self.output_dir_widget.get_path()
+            if not existing_out or not existing_out.strip():
+                self.output_dir_widget.set_path(output_dir)
+
+    def _get_default_work_dir(self):
+        """获取 work_dir，优先用 panel 自身缓存的，否则尝试从主窗口取"""
+        if hasattr(self, 'work_dir') and self.work_dir:
+            return str(self.work_dir)
+        mw = self.window()
+        if mw and hasattr(mw, 'work_dir') and mw.work_dir:
+            return str(mw.work_dir)
+        return ""
+
     def browse_regression_models_dir(self):
         """浏览回归模型目录"""
-        dir_path = QFileDialog.getExistingDirectory(self, "选择回归模型目录", "")
+        default = self._get_default_work_dir()
+        if default:
+            default = os.path.join(default, "9_Custom_Regression_Modeling")
+        dir_path = QFileDialog.getExistingDirectory(self, "选择回归模型目录", default)
         if dir_path:
             self.regression_models_dir.set_path(dir_path)
 
     def browse_output_dir(self):
         """浏览输出目录"""
-        dir_path = QFileDialog.getExistingDirectory(self, "选择输出目录", "")
+        default = self._get_default_work_dir()
+        if default:
+            default = os.path.join(default, "11_12_13_predictions/Custom_Regression_Prediction")
+        dir_path = QFileDialog.getExistingDirectory(self, "选择输出目录", default)
         if dir_path:
             self.output_dir_widget.set_path(dir_path)
 

src/gui/panels/step8_panel.py

@@ -4,6 +4,9 @@
 Step8 面板 - 机器学习预测
 """
 
+import os
+from pathlib import Path
+
 from PyQt5.QtWidgets import (
     QWidget, QVBoxLayout, QGroupBox, QFormLayout,
     QPushButton, QCheckBox, QComboBox, QLineEdit, QMessageBox,
@@ -76,9 +79,61 @@ class Step8Panel(QWidget):
         layout.addStretch()
         self.setLayout(layout)
 
+    def update_from_config(self, work_dir=None, pipeline=None):
+        """从全局配置自动填充采样光谱和模型目录
+
+        Args:
+            work_dir: 工作目录路径
+            pipeline: Pipeline 实例（未使用，保留接口兼容性）
+        """
+        if work_dir:
+            self.work_dir = work_dir
+        elif hasattr(self, 'work_dir') and self.work_dir:
+            pass
+        else:
+            self.work_dir = None
+
+        main_window = self.window()
+
+        # 1. 尝试从 Step7 界面读取全湖采样点 CSV 路径
+        if main_window and hasattr(main_window, 'step7_panel'):
+            step7_output_path = main_window.step7_panel.output_file.get_path()
+            if step7_output_path:
+                existing = self.sampling_csv_file.get_path()
+                if not existing or not existing.strip():
+                    self.sampling_csv_file.set_path(step7_output_path)
+
+        # 2. 尝试从 Step6 界面读取监督模型目录
+        if main_window and hasattr(main_window, 'step6_panel'):
+            step6_models_dir = main_window.step6_panel.output_dir.get_path()
+            if step6_models_dir:
+                existing_models = self.models_dir_file.get_path()
+                if not existing_models or not existing_models.strip():
+                    self.models_dir_file.set_path(step6_models_dir)
+
+        # 3. 自动填充输出路径（机器学习预测目录）
+        if self.work_dir:
+            output_dir = os.path.join(self.work_dir, "11_12_13_predictions/Machine_Learning_Prediction")
+            os.makedirs(output_dir, exist_ok=True)
+            existing_out = self.output_file.get_path()
+            if not existing_out or not existing_out.strip():
+                self.output_file.set_path(output_dir)
+
+    def _get_default_work_dir(self):
+        """获取 work_dir，优先用 panel 自身缓存的，否则尝试从主窗口取"""
+        if hasattr(self, 'work_dir') and self.work_dir:
+            return str(self.work_dir)
+        mw = self.window()
+        if mw and hasattr(mw, 'work_dir') and mw.work_dir:
+            return str(mw.work_dir)
+        return ""
+
     def browse_models_dir(self):
         """浏览模型目录"""
-        dir_path = QFileDialog.getExistingDirectory(self, "选择模型目录", "")
+        default = self._get_default_work_dir()
+        if default:
+            default = os.path.join(default, "7_Supervised_Model_Training")
+        dir_path = QFileDialog.getExistingDirectory(self, "选择模型目录", default)
         if dir_path:
             self.models_dir_file.set_path(dir_path)
 

src/gui/panels/step9_panel.py

@@ -101,12 +101,9 @@ class Step9Panel(QWidget):
         mode_row = QHBoxLayout()
         self.mode_single_rb = QRadioButton("单个 CSV 文件")
         self.mode_folder_rb = QRadioButton("文件夹批量")
-        self.mode_single_rb.setChecked(True)
         self._mode_group = QButtonGroup(self)
         self._mode_group.addButton(self.mode_single_rb, 0)
         self._mode_group.addButton(self.mode_folder_rb, 1)
-        self.mode_single_rb.toggled.connect(self._on_step9_mode_changed)
-        self.mode_folder_rb.toggled.connect(self._on_step9_mode_changed)
         mode_row.addWidget(self.mode_single_rb)
         mode_row.addWidget(self.mode_folder_rb)
         mode_row.addStretch()
@@ -192,16 +189,36 @@ class Step9Panel(QWidget):
 
         layout.addStretch()
         self.setLayout(layout)
-        self._on_step9_mode_changed()
 
-    def _on_step9_mode_changed(self):
+        # 信号绑定与初始状态
+        self.mode_single_rb.toggled.connect(self._toggle_input_mode)
+        self.mode_folder_rb.toggled.connect(self._toggle_input_mode)
+        self.mode_single_rb.setChecked(True)  # 默认选中"单个 CSV"
+        self._toggle_input_mode()             # 根据默认值设置初始显示状态
+
+    def _toggle_input_mode(self):
+        """槽函数：根据单选框状态动态显示/隐藏对应的输入组件。"""
         folder_mode = self.mode_folder_rb.isChecked()
-        self.prediction_csv_file.setEnabled(not folder_mode)
+        # 单个 CSV 模式：显示单文件选择，隐藏文件夹选择
-        self._folder_row_widget.setEnabled(folder_mode)
+        self.prediction_csv_file.setVisible(not folder_mode)
-        self.recursive_csv_cb.setEnabled(folder_mode)
+        # 文件夹批量模式：显示文件夹选择 + 递归选项，隐藏单文件选择
+        self._folder_row_widget.setVisible(folder_mode)
+        self.recursive_csv_cb.setVisible(folder_mode)
+
+    def _get_default_work_dir(self):
+        """获取 work_dir，优先用 panel 自身缓存的，否则尝试从主窗口取"""
+        if hasattr(self, 'work_dir') and self.work_dir:
+            return str(self.work_dir)
+        mw = self.window()
+        if mw and hasattr(mw, 'work_dir') and mw.work_dir:
+            return str(mw.work_dir)
+        return ""
 
     def browse_prediction_csv_dir(self):
-        d = QFileDialog.getExistingDirectory(self, "选择预测结果 CSV 所在文件夹")
+        default = self._get_default_work_dir()
+        if default:
+            default = os.path.join(default, "11_12_13_predictions")
+        d = QFileDialog.getExistingDirectory(self, "选择预测结果 CSV 所在文件夹", default)
         if d:
             self.prediction_csv_dir_edit.setText(d)
 
@@ -281,9 +298,68 @@ class Step9Panel(QWidget):
             if p.parent and str(p.parent) != '.':
                 self.output_dir.set_path(str(p.parent))
 
+    def update_from_config(self, work_dir=None, pipeline=None):
+        """从全局配置自动填充预测结果目录
+
+        优先使用 Step8（机器学习预测）的输出目录作为待预测 CSV 目录；
+        其次回退到 Step8.5（回归预测）或 Step8.75（自定义回归预测）的输出目录。
+
+        Args:
+            work_dir: 工作目录路径
+            pipeline: Pipeline 实例（未使用，保留接口兼容性）
+        """
+        if work_dir:
+            self.work_dir = work_dir
+        elif hasattr(self, 'work_dir') and self.work_dir:
+            pass
+        else:
+            self.work_dir = None
+
+        main_window = self.window()
+        if not main_window:
+            return
+
+        # 1. 尝试从 Step8 界面读取机器学习预测输出目录（优先）
+        pred_dir = None
+        if hasattr(main_window, 'step8_panel'):
+            step8_output = main_window.step8_panel.output_file.get_path()
+            if step8_output:
+                pred_dir = str(Path(step8_output).parent)
+
+        # 2. 备选：从 Step8.5 界面读取非经验预测输出目录
+        if not pred_dir and hasattr(main_window, 'step8_5_panel'):
+            step8_5_output = main_window.step8_5_panel.output_file.get_path()
+            if step8_5_output:
+                pred_dir = str(Path(step8_5_output).parent)
+
+        # 3. 备选：从 Step8.75 界面读取自定义回归预测输出目录
+        if not pred_dir and hasattr(main_window, 'step8_75_panel'):
+            step8_75_output = main_window.step8_75_panel.output_dir_widget.get_path()
+            if step8_75_output:
+                pred_dir = step8_75_output
+
+        # 自动填入"预测CSV目录"（文件夹批量模式）
+        if pred_dir:
+            existing_dir = (self.prediction_csv_dir_edit.text() or "").strip()
+            if not existing_dir:
+                self.prediction_csv_dir_edit.setText(pred_dir)
+                # 切换到文件夹批量模式
+                self.mode_folder_rb.setChecked(True)
+
+        # 4. 自动填充输出目录（14_visualization）
+        if self.work_dir:
+            output_dir = os.path.join(self.work_dir, "14_visualization")
+            os.makedirs(output_dir, exist_ok=True)
+            existing_out = self.output_dir.get_path()
+            if not existing_out or not existing_out.strip():
+                self.output_dir.set_path(output_dir)
+
     def browse_output_dir(self):
         """浏览输出目录"""
-        dir_path = QFileDialog.getExistingDirectory(self, "选择输出模型目录", "")
+        default = self._get_default_work_dir()
+        if default:
+            default = os.path.join(default, "14_visualization")
+        dir_path = QFileDialog.getExistingDirectory(self, "选择输出分布图目录", default)
         if dir_path:
             self.output_dir.set_path(dir_path)
 

src/gui/panels/visualization_panel.py

@@ -1215,9 +1215,19 @@ class VisualizationPanel(QWidget):
         if work_dir:
             QTimer.singleShot(100, self.scan_work_directory)
 
+    def _get_default_work_dir(self):
+        """获取 work_dir，优先用 panel 自身缓存的，否则尝试从主窗口取"""
+        if hasattr(self, 'work_dir') and self.work_dir:
+            return str(self.work_dir)
+        mw = self.window()
+        if mw and hasattr(mw, 'work_dir') and mw.work_dir:
+            return str(mw.work_dir)
+        return ""
+
     def browse_work_dir(self):
         """浏览工作目录"""
-        dir_path = QFileDialog.getExistingDirectory(self, "选择工作目录")
+        default = self._get_default_work_dir()
+        dir_path = QFileDialog.getExistingDirectory(self, "选择工作目录", default)
         if dir_path:
             self.work_dir = dir_path
             self.work_dir_edit.setText(dir_path)
@@ -1225,7 +1235,8 @@ class VisualizationPanel(QWidget):
 
     def browse_img_dir(self):
         """手动浏览图像目录"""
-        dir_path = QFileDialog.getExistingDirectory(self, "选择图像目录")
+        default = self._get_default_work_dir()
+        dir_path = QFileDialog.getExistingDirectory(self, "选择图像目录", default)
         if dir_path:
             self.img_dir_edit.setText(dir_path)
             self.image_tree.scan_directory(dir_path)

src/gui/water_quality_gui.py

@@ -1475,7 +1475,7 @@ class WaterQualityGUI(QMainWindow):
         
     def init_ui(self):
         """初始化UI"""
-        self.setWindowTitle("水质参数反演分析系统 v1.0")
+        self.setWindowTitle("水质参数反演分析系统 v1.1")
 
         # 获取屏幕可用区域（排除任务栏）
         screen_geometry = QApplication.primaryScreen().availableGeometry()
@@ -1658,48 +1658,66 @@ class WaterQualityGUI(QMainWindow):
     
     def create_banner_widget(self):
         """创建横幅区域 - 支持自适应等比缩放"""
+        # 横幅标题文字（方便后续直接修改版本号）
+        self._APP_TITLE = "Mega Water V1.1"
+
         # 创建横幅容器
         banner_widget = QWidget()
         banner_layout = QHBoxLayout()
         banner_layout.setContentsMargins(0, 0, 0, 0)
         banner_layout.setSpacing(0)
-        # 不设置居中对齐，让横幅填满整个容器
 
-        # 创建横幅标签 - 完全跟随窗口等比缩放，填满整个区域
+        # ===== 底图层 =====
         self.banner_label = QLabel()
-        # 最小高度保证：当窗口很小时至少显示 38px 高 (200px 宽 / 5.25)
+        self.banner_label.setMinimumHeight(140)
-        self.banner_label.setMinimumHeight(int(200 / 5.25))   # ≈ 38px
-        # 使用 Expanding 策略让标签填满可用空间
         self.banner_label.setSizePolicy(QSizePolicy.Expanding, QSizePolicy.Fixed)
         self.banner_label.setScaledContents(False)
-        # 清除 QLabel 默认的 margin 和 padding，消除右侧空白
         self.banner_label.setStyleSheet("margin: 0px; padding: 0px; border: none;")
 
-        # 保存原始pixmap用于后续缩放
+        # 强制 banner_widget 展开填充 toolbar 全部宽度（清除 addWidget 的默认居中行为）
+        banner_widget.setSizePolicy(QSizePolicy.Expanding, QSizePolicy.Fixed)
+        banner_widget.setMinimumWidth(0)  # 确保可以被 layout 压缩/扩展到任意宽度
+        banner_widget.setStyleSheet("margin: 0px; padding: 0px; border: none;")
+
+        # 纯净底图路径（无水印文字）
         if hasattr(sys, '_MEIPASS'):
-            banner_path = os.path.join(sys._MEIPASS, 'data', 'icons', 'Mega Water 1.0.png')
+            banner_path = os.path.join(sys._MEIPASS, 'data', 'icons', 'Mega Water 1.0.jpg')
         else:
-            banner_path = str(Path(__file__).parent.parent.parent / "data" / "icons" / "Mega Water 1.0.png")
+            banner_path = str(Path(__file__).parent.parent.parent / "data" / "icons" / "Mega Water 1.0.jpg")
         self.banner_pixmap = QPixmap(banner_path)
 
         if not self.banner_pixmap.isNull():
-            # 延迟执行，确保窗口已初始化
             QTimer.singleShot(50, self.update_banner_image)
         else:
-            # 如果图片加载失败，显示占位符
+            self.banner_label.setText("背景图加载失败")
-            self.banner_label.setText("水质参数反演分析系统")
             self.banner_label.setStyleSheet("""
                 QLabel {
-                    background: qlineargradient(x1:0, y1:0, x2:1, y2:0, 
+                    background: qlineargradient(x1:0, y1:0, x2:1, y2:0,
                                               stop:0 #0078d4, stop:1 #00a0e9);
-                    color: white;
+                    color: white; font-size: 26px; font-weight: bold;
-                    font-size: 26px;
-                    font-weight: bold;
                     border-bottom: 3px solid #005a9e;
                 }
             """)
 
         banner_layout.addWidget(self.banner_label)
+
+        # ===== 文字叠加层 =====
+        # 注意这里：第二个参数改成了 self.banner_label，直接附着在底图上！
+        self.banner_title_label = QLabel(self._APP_TITLE, self.banner_label)
+        self.banner_title_label.setStyleSheet("""
+            QLabel {
+                background: transparent;
+                color: white;
+                font-size: 48px;  /* 显著增大字号 */
+                font-weight: normal; /* 取消粗体，还原原图的优雅感 */
+                font-family: "Times New Roman", "Georgia", "STZhongsong", serif; /* 衬线字体家族 */
+                letter-spacing: 1px;
+            }
+        """)
+        self.banner_title_label.setAttribute(Qt.WA_TransparentForMouseEvents)  # 鼠标穿透
+        self.banner_title_label.show()     # 第一道保险：强制现身
+        self.banner_title_label.raise_()   # 第二道保险：强制图层置顶
+
         banner_widget.setLayout(banner_layout)
 
         # 将横幅添加到窗口顶部（在标题栏下方）
@@ -1721,6 +1739,10 @@ class WaterQualityGUI(QMainWindow):
                 margin: 0px;
                 padding: 0px;
             }
+            QToolBar > QWidget {
+                margin: 0px;
+                padding: 0px;
+            }
         """)
 
         self.addToolBar(Qt.TopToolBarArea, banner_toolbar)
@@ -2122,10 +2144,34 @@ class WaterQualityGUI(QMainWindow):
         elif index == 6:
             self.step6_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline)
 
+        # Step6.5（非经验回归建模）切换时自动填充训练数据和模型目录
+        elif index == 7:
+            self.step6_5_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline)
+
+        # Step6.75（自定义回归建模）切换时自动填充训练数据和模型目录
+        elif index == 8:
+            self.step6_75_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline)
+
         # Step7（采样点布设）切换时自动填充掩膜和输出路径
         elif index == 9:
             self.step7_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline)
 
+        # Step8（机器学习预测）切换时自动填充采样光谱和模型目录
+        elif index == 10:
+            self.step8_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline)
+
+        # Step8.5（非经验模型预测）切换时自动填充采样光谱和回归模型目录
+        elif index == 11:
+            self.step8_5_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline)
+
+        # Step8.75（自定义回归预测）切换时自动填充采样光谱和自定义回归模型目录
+        elif index == 12:
+            self.step8_75_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline)
+
+        # Step9（专题图生成）切换时自动填充预测结果目录
+        elif index == 13:
+            self.step9_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline)
+
         # 可视化分析面板切换时自动推断图像目录并加载目录树
         elif index == 14:
             self.viz_panel.update_from_config(work_dir=self.work_dir, pipeline=self.pipeline)
@@ -2853,36 +2899,43 @@ class WaterQualityGUI(QMainWindow):
         self.training_mode_action.setText("有训练数据模式" if checked else "无训练数据模式")
 
     def update_banner_image(self):
-        """更新横幅图片 - 完全跟随窗口等比缩放，填满可用宽度"""
+        """更新横幅图片 - 固定高度 + 居中裁剪（类似 CSS object-fit: cover）"""
         if not hasattr(self, 'banner_pixmap') or self.banner_pixmap.isNull():
             return
 
-        # 获取可用宽度（考虑工具栏边距），跟随窗口实时变化
+        TARGET_HEIGHT = 140
-        available_width = max(200, self.width() - 60)
+        target_width = self.width()
-        
-        # 先根据可用宽度计算目标高度（严格 5.25:1）
-        target_height = int(available_width / 5.25)
-        
-        # 限制最小高度
-        if target_height < 38:
-            target_height = 38
-            available_width = int(38 * 5.25)
 
-        # 计算图片目标尺寸（保持 5.25:1 比例）
+        # 手动计算 Cover 缩放比例：取宽/高各自所需比例的最大值，
-        target_width = available_width
+        # 确保缩放后图片的宽 ≥ target_width 且高 ≥ TARGET_HEIGHT
-        
+        orig_w = self.banner_pixmap.width()
-        # 设置固定尺寸，确保标签严格填满整个区域
+        orig_h = self.banner_pixmap.height()
-        self.banner_label.setFixedSize(target_width, target_height)
+        scale_factor = max(target_width / orig_w, TARGET_HEIGHT / orig_h)
+        new_w = int(orig_w * scale_factor)
+        new_h = int(orig_h * scale_factor)
 
-        # 等比缩放到目标尺寸，填满整个区域（允许轻微裁剪）
         scaled_pixmap = self.banner_pixmap.scaled(
-            target_width,
+            new_w, new_h,
-            target_height,
+            Qt.IgnoreAspectRatio,
-            Qt.KeepAspectRatioByExpanding,  # 保持比例，填满区域，允许裁剪超出部分
             Qt.SmoothTransformation
         )
 
-        self.banner_label.setPixmap(scaled_pixmap)
+        # 居中裁剪，截取中间核心区域
+        crop_x = (new_w - target_width) // 2
+        crop_y = (new_h - TARGET_HEIGHT) // 2
+        final_pixmap = scaled_pixmap.copy(crop_x, crop_y, target_width, TARGET_HEIGHT)
+
+        self.banner_label.setFixedHeight(TARGET_HEIGHT)
+        self.banner_label.setFixedWidth(target_width)  # 强制宽度填满容器
+        self.banner_label.setPixmap(final_pixmap)
+        self.banner_label.setAlignment(Qt.AlignLeft | Qt.AlignVCenter)
+
+        # 文字叠加层：绝对定位，保持垂直居中
+        if hasattr(self, 'banner_title_label'):
+            title_x = 160
+            title_y = max(0, (TARGET_HEIGHT - 60) // 2)
+            self.banner_title_label.move(title_x, title_y)
+            self.banner_title_label.resize(target_width - title_x - 20, 60)
 
     def resizeEvent(self, event):
         """窗口大小改变事件 - 实时更新横幅图片等比缩放"""