修复 PyQt 0xC0000409 崩溃：修复 window 属性命名冲突、全局异常钩子、可视化面板健壮重构

src/gui/panels/step6_5_panel.py

@@ -102,11 +102,11 @@ class Step6_5Panel(QWidget):
         self.spectral_start_col.setValue(1)
         params_layout.addRow("光谱起始列索引:", self.spectral_start_col)
 
-        # 窗口大小
-        self.window = QSpinBox()
-        self.window.setRange(1, 20)
-        self.window.setValue(5)
-        params_layout.addRow("窗口大小:", self.window)
+        # 窗口大小 (变量名已修正，避免覆盖 QWidget.window)
+        self.window_size_spinbox = QSpinBox()
+        self.window_size_spinbox.setRange(1, 20)
+        self.window_size_spinbox.setValue(5)
+        params_layout.addRow("窗口大小:", self.window_size_spinbox)
 
         params_group.setLayout(params_layout)
         layout.addWidget(params_group)
@@ -160,7 +160,7 @@ class Step6_5Panel(QWidget):
             'algorithms': selected_algorithms,
             'value_cols': value_cols,
             'spectral_start_col': self.spectral_start_col.value(),
-            'window': self.window.value(),
+            'window': self.window_size_spinbox.value(),
             'enabled': self.enable_checkbox.isChecked()
         }
 
@@ -205,7 +205,7 @@ class Step6_5Panel(QWidget):
             self.spectral_start_col.setValue(config['spectral_start_col'])
 
         if 'window' in config:
-            self.window.setValue(config['window'])
+            self.window_size_spinbox.setValue(config['window'])
         if 'output_dir' in config:
             self.output_dir.set_path(config['output_dir'])
         if 'csv_path' in config:
@@ -218,38 +218,54 @@ class Step6_5Panel(QWidget):
             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
+        try:
+            import traceback
 
-        # 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:
-                # 若为相对路径，使用 work_dir 合成为绝对路径
-                if not os.path.isabs(step5_output_path):
-                    step5_output_path = os.path.join(self.work_dir or '', step5_output_path).replace('\\', '/')
-                existing = self.training_csv_file.get_path()
-                if not existing or not existing.strip():
-                    self.training_csv_file.set_path(step5_output_path)
+            if work_dir:
+                self.work_dir = work_dir
+            elif hasattr(self, 'work_dir') and self.work_dir:
+                pass
+            else:
+                self.work_dir = None
 
-        # 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)
+            # 借用父组件的 window() 方法，安全绕过当前类的命名冲突
+            parent_widget = self.parentWidget()
+            main_window = parent_widget.window() if parent_widget else None
+            if main_window and hasattr(main_window, 'step5_panel'):
+                step5_widget = getattr(main_window.step5_panel, 'output_file', None)
+                step5_output_path = ""
+                if hasattr(step5_widget, 'get_path'):
+                    step5_output_path = step5_widget.get_path() or ""
+                elif hasattr(step5_widget, 'text'):
+                    step5_output_path = step5_widget.text() or ""
+
+                if step5_output_path:
+                    # 若为相对路径，使用 work_dir 合成为绝对路径
+                    if not os.path.isabs(step5_output_path):
+                        step5_output_path = os.path.join(self.work_dir or '', step5_output_path).replace('\\', '/')
+                    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)
+        except Exception as e:
+            import traceback
+            print(f"【{self.__class__.__name__}】自动填充失败，跳过: {e}")
+            traceback.print_exc()
 
     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()
+        # 借用父组件的 window() 方法，安全绕过当前类的命名冲突
+        parent_widget = self.parentWidget()
+        mw = parent_widget.window() if parent_widget else None
         if mw and hasattr(mw, 'work_dir') and mw.work_dir:
             return str(mw.work_dir)
         return ""

src/gui/panels/visualization_panel.py

@@ -493,17 +493,9 @@ class ChartViewerDialog(QDialog):
 
 
 class ImageCategoryTree(QTreeWidget):
-    """图像分类目录树 - 按类别组织图像文件"""
+    """图像分类目录树 - 按真实物理文件夹结构组织图像文件"""
 
-    CATEGORIES = [
-        ("模型评估", ["scatter", "regression", "validation", "r2", "rmse"], "📊"),
-        ("光谱分析", ["spectrum", "spectral", "band", "wavelength"], "📈"),
-        ("统计图表", ["boxplot", "histogram", "heatmap", "statistics", "stats"], "📉"),
-        ("处理结果", ["mask", "glint", "deglint", "preview", "overlay", "water_mask"], "🖼️"),
-        ("含量分布图", [], "📁"),
-    ]
-
-    # 文件名中文翻译映射
+    # 文件名中文翻译映射（key: 文件名前缀 → 中文显示名）
     NAME_MAPPING = {
         "hsi_preview": "高光谱影像预览",
         "hsi_original": "原始高光谱影像",
@@ -537,14 +529,52 @@ class ImageCategoryTree(QTreeWidget):
         "error_analysis": "误差分析图",
         "rmse": "RMSE评估图",
         "r2_score": "R²得分图",
+        "flight": "飞行轨迹图",
+        "path": "轨迹图",
+        "trajectory": "轨迹图",
+        "glint_deglint": "耀斑去耀斑影像",
+        "enhanced": "增强分布图",
+        "content": "含量分布图",
+        "distribution": "分布图",
+        "prediction": "预测图",
+        "inversion": "反演图",
+        "scatter_true_vs_pred": "真值-预测散点图",
+        "true_vs_pred": "真值-预测散点图",
+        "correlation_heatmap": "相关性热力图",
+        "parameter_boxplot": "水质参数箱线图",
+        "spectrum_comparison": "光谱曲线对比图",
+        "scatter": "散点图",
+    }
+
+    # 目录层级中文翻译
+    DIR_MAPPING = {
+        "14_visualization": "可视化产物",
+        "glint_deglint_previews": "耀斑与去耀斑预览",
+        "sampling_maps": "采样点地图",
+        "scatter_plots": "模型评估散点图",
+        "flight_maps": "飞行轨迹图",
+        "11_12_13_predictions": "预测结果",
+        "Machine_Learning_Prediction": "机器学习预测",
+        "Non_Empirical_Prediction": "非经验模型预测",
+        "Custom_Regression_Prediction": "自定义回归预测",
+        "8_Regression_Modeling": "回归建模",
+        "10_feature_construction": "特征构建",
+        "5_training_spectra": "训练光谱",
+        "2_glint": "耀斑分析",
+        "3_deglint": "去耀斑处理",
+        "1_water_mask": "水掩膜",
+        "9_water_quality_prediction": "水质预测",
+        "8_spatial_inversion": "空间反演",
+        "4_processed_data": "处理数据",
     }
 
     def __init__(self, parent=None):
         super().__init__(parent)
+        self._dir_node_map: dict = {}  # 目录路径字符串 → QTreeWidgetItem
+        self._work_path: Optional[Path] = None
         self.setHeaderLabel("图像目录")
         self.setMaximumWidth(300)
         self.setMinimumWidth(250)
-        self.setup_categories()
         self.setStyleSheet("""
             QTreeWidget {
                 border: 1px solid #ddd;
@@ -564,96 +594,211 @@ class ImageCategoryTree(QTreeWidget):
             }
         """)
 
-    def setup_categories(self):
-        """初始化类别节点"""
-        self.category_items = {}
-        for category_name, keywords, icon in self.CATEGORIES:
-            item = QTreeWidgetItem(self)
-            item.setText(0, f"{icon} {category_name}")
-            item.setData(0, Qt.UserRole, {"type": "category", "keywords": keywords, "name": category_name})
-            item.setExpanded(True)
-            self.category_items[category_name] = item
-
     def clear_all_images(self):
         """清除所有图像项"""
-        for category_item in self.category_items.values():
-            while category_item.childCount() > 0:
-                category_item.removeChild(category_item.child(0))
+        try:
+            self.invisibleRootItem().takeChildren()
+            if hasattr(self, '_dir_node_map'):
+                self._dir_node_map.clear()
+        except Exception as e:
+            print(f"清空树状图出错: {e}")
+            import traceback
+            traceback.print_exc()
 
-    def add_image(self, file_path: Path, display_name: str = None):
-        """添加图像到对应的类别（带中文名称翻译）"""
-        if display_name is None:
-            # 使用翻译映射，查询不到则用原文件名
-            file_base = file_path.stem
-            display_name = self.NAME_MAPPING.get(file_base, file_base)
+    def _translate_dir_name(self, dir_name: str) -> str:
+        """翻译目录名为中文"""
+        return self.DIR_MAPPING.get(dir_name, dir_name)
 
-        category = self._determine_category(file_path.name)
-        category_item = self.category_items.get(category, self.category_items["含量分布图"])
+    def _translate_filename(self, filename: str) -> str:
+        """翻译文件名为中文（动态替换后缀片段）"""
+        # 依次替换常见后缀模式
+        replacements = [
+            ("_spectrum_comparison", " 光谱曲线对比图"),
+            ("_scatter_true_vs_pred", " 真值-预测散点图"),
+            ("_true_vs_pred", " 真值-预测散点图"),
+            ("_histogram", " 分布直方图"),
+            ("_boxplot", " 箱线图"),
+            ("_distribution_map", " 分布图"),
+            ("_distribution_enhanced", " 增强分布图"),
+            ("_thematic_map", " 专题图"),
+            ("_water_quality_map", " 水质分布图"),
+            ("_prediction_map", " 预测结果图"),
+            ("_inversion_map", " 反演结果图"),
+            ("_glint_deglint", " 耀斑去耀斑对比"),
+            ("_glint_mask", " 耀斑掩膜"),
+            ("_deglint", " 去耀斑"),
+            ("_mask_overlay", " 掩膜叠加"),
+            ("_content", " 含量"),
+            ("_distribution", " 分布"),
+            ("_prediction", " 预测"),
+            ("_inversion", " 反演"),
+            ("_enhanced", " 增强"),
+            ("_scatter", " 散点图"),
+            ("_boxplot", " 箱线图"),
+            ("_correlation_heatmap", " 相关性热力图"),
+            ("_parameter_boxplot", " 箱线图"),
+            ("_sampling_point", " 采样点"),
+            ("_sampling_points", " 采样点"),
+            ("_flight_path", " 飞行轨迹"),
+            ("_trajectory", " 轨迹"),
+        ]
+        result = filename
+        for pattern, replacement in replacements:
+            result = result.replace(pattern, replacement)
 
-        image_item = QTreeWidgetItem(category_item)
-        image_item.setText(0, f"  └─ {display_name}")
+        # 处理参数名（常见水质参数翻译）
+        param_map = {
+            "Chla": "叶绿素", "COD": "化学需氧量", "TN": "总氮", "TP": "总磷",
+            "Turbidity": "浊度", "DO": "溶解氧", "pH": "pH值",
+            "Conductivity": "电导率", "BOD": "生化需氧量", "NH3_N": "氨氮",
+        }
+        for eng, chn in param_map.items():
+            # 在文件名中找到参数名并翻译
+            if eng.lower() in result.lower():
+                result = result.replace(eng, chn)
+            if eng.lower() in result.lower():
+                result = result.replace(eng.lower(), chn)
+
+        # 如果没有任何替换，返回原文件名（去掉扩展名）
+        if result == filename:
+            return filename.rsplit(".", 1)[0] if "." in filename else filename
+        return result
+
+    def add_image_by_dir(self, file_path: Path, work_path: Path):
+        """按真实物理目录层级挂载图片节点
+
+        Args:
+            file_path: 图片文件的完整路径
+            work_path: 工作目录根路径
+        """
+        # 计算相对路径
+        try:
+            rel_path = file_path.relative_to(work_path)
+        except ValueError:
+            rel_path = Path(file_path.name)
+
+        # 分离父目录链和文件名
+        parts = rel_path.parts
+        if len(parts) <= 1:
+            parent_key = "__root__"
+            parent_display = "根目录"
+        else:
+            # 父目录路径（相对于work_path）
+            parent_key = str(Path(*parts[:-1]))
+            # 取最后一层目录名作为显示名
+            parent_display = self._translate_dir_name(parts[-2])
+
+        # 根目录节点特殊处理
+        root_display = self._translate_dir_name(parts[0]) if parts else "根目录"
+
+        # 获取或创建根目录节点
+        if root_display not in self._dir_node_map:
+            root_item = QTreeWidgetItem(self)
+            root_item.setText(0, f"📁 {root_display}")
+            root_item.setData(0, Qt.UserRole, {"type": "root_dir", "path": str(work_path / parts[0])})
+            root_item.setExpanded(True)
+            self._dir_node_map[root_display] = root_item
+            self._dir_node_map[f"__root__{root_display}"] = root_item
+        root_item = self._dir_node_map.get(f"__root__{root_display}")
+
+        if len(parts) > 1:
+            # 获取或创建子目录节点
+            if parent_key not in self._dir_node_map:
+                dir_item = QTreeWidgetItem(root_item)
+                dir_item.setText(0, f"  📂 {parent_display}")
+                dir_item.setData(0, Qt.UserRole, {"type": "sub_dir", "path": str(work_path / parent_key)})
+                dir_item.setExpanded(True)
+                self._dir_node_map[parent_key] = dir_item
+            parent_item = self._dir_node_map[parent_key]
+        else:
+            parent_item = root_item
+
+        # 创建图片节点
+        display_name = self._translate_filename(file_path.stem) + file_path.suffix
+        image_item = QTreeWidgetItem(parent_item)
+        image_item.setText(0, f"    🖼 {display_name}")
         image_item.setData(0, Qt.UserRole, {"type": "image", "path": str(file_path), "display_name": display_name})
         image_item.setToolTip(0, str(file_path))
 
         return image_item
 
-    def _determine_category(self, filename: str) -> str:
-        """根据文件名确定类别"""
-        filename_lower = filename.lower()
-
-        for category_name, keywords, _ in self.CATEGORIES:
-            if any(keyword in filename_lower for keyword in keywords):
-                return category_name
-
-        return "含量分布图"
-
     def scan_directory(self, work_dir: str):
-        """扫描目录中的所有图像文件（深度递归扫描）"""
-        self.clear_all_images()
+        """扫描目录中的所有图像文件（深度递归扫描）—— 按真实物理目录结构挂载"""
+        try:
+            if not work_dir:
+                print("可视化面板：工作目录为空，跳过扫描")
+                return
 
-        work_path = Path(work_dir)
-        if not work_path.exists():
+            self._work_path = Path(work_dir)
+
+            # 阻塞信号，防止在清空树状图时触发 selected 槽函数导致崩溃
+            # 因为当前类继承自 QTreeWidget，所以 self 本身就是树
+            self.blockSignals(True)
+            self.clear_all_images()
+            self.blockSignals(False)
+
+            if not self._work_path.exists():
+                return
+        except Exception as e:
+            import traceback
+            print(f"可视化面板初始化扫描出错: {e}")
+            traceback.print_exc()
+            # 确保信号锁被解开
+            self.blockSignals(False)
             return
 
-        image_extensions = ['*.png', '*.jpg', '*.jpeg', '*.tif', '*.tiff', '*.bmp']
+        try:
+            image_extensions = ['*.png', '*.jpg', '*.jpeg', '*.tif', '*.tiff', '*.bmp']
 
-        # 扫描根目录列表（按优先级）
-        scan_roots: List[Path] = [
-            work_path / "14_visualization",
-            work_path / "1_water_mask",
-            work_path / "9_water_quality_prediction",
-            work_path / "10_feature_construction",
-        ]
+            # 拓宽扫描根目录列表（新增多个遗漏目录）
+            scan_roots: List[Path] = [
+                self._work_path / "14_visualization",
+                self._work_path / "11_12_13_predictions",
+                self._work_path / "8_Regression_Modeling",
+                self._work_path / "10_feature_construction",
+                self._work_path / "5_training_spectra",
+                self._work_path / "2_glint",
+                self._work_path / "3_deglint",
+                self._work_path / "1_water_mask",
+                self._work_path / "9_water_quality_prediction",
+            ]
 
-        # 只保留存在的目录，并补充工作根目录作为兜底
-        scan_roots = [p for p in scan_roots if p.is_dir()]
-        if not scan_roots:
-            scan_roots.append(work_path)
+            # 只保留存在的目录，并补充工作根目录作为兜底
+            scan_roots = [p for p in scan_roots if p.is_dir()]
+            if not scan_roots:
+                scan_roots.append(self._work_path)
 
-        seen_norm: set = set()
-        image_files: List[Path] = []
-        for root in scan_roots:
-            for ext in image_extensions:
-                # 使用 rglob 进行深度递归扫描
-                for p in root.rglob(ext):
-                    key = os.path.normcase(os.path.normpath(str(p.resolve())))
-                    if key in seen_norm:
-                        continue
-                    seen_norm.add(key)
-                    image_files.append(p)
+            seen_norm: set = set()
+            image_files: List[Path] = []
+            for root in scan_roots:
+                for ext in image_extensions:
+                    for p in root.rglob(ext):
+                        key = os.path.normcase(os.path.normpath(str(p.resolve())))
+                        if key in seen_norm:
+                            continue
+                        seen_norm.add(key)
+                        image_files.append(p)
 
-        for img_file in sorted(image_files):
-            if img_file.name.startswith('.') or 'thumb' in img_file.name.lower():
-                continue
-            self.add_image(img_file)
+            for img_file in sorted(image_files):
+                if img_file.name.startswith('.') or 'thumb' in img_file.name.lower():
+                    continue
+                self.add_image_by_dir(img_file, self._work_path)
 
-        for category_name, item in self.category_items.items():
-            count = item.childCount()
-            if count > 0:
-                for cat_name, _, icon in self.CATEGORIES:
-                    if cat_name == category_name:
-                        item.setText(0, f"{icon} {category_name} ({count})")
-                        break
+            # 更新目录节点计数
+            for key, item in self._dir_node_map.items():
+                if key.startswith("__root__"):
+                    continue
+                if item.data(0, Qt.UserRole).get("type") == "sub_dir":
+                    count = item.childCount()
+                    name = item.text(0)
+                    if count > 0 and f"({count})" not in name:
+                        # 从目录名中提取显示名并附加计数
+                        display = name.strip()
+                        item.setText(0, f"  📂 {display} ({count})")
+        except Exception as e:
+            import traceback
+            print(f"可视化面板图片挂载出错: {e}")
+            traceback.print_exc()
 
     def get_selected_image_path(self) -> Optional[str]:
         """获取当前选中的图像路径"""
@@ -1295,54 +1440,78 @@ class VisualizationPanel(QWidget):
         4. {work_dir}/14_visualization（可视化目录）
         5. {work_dir}（工作目录根）
         """
-        if work_dir:
-            self.work_dir = work_dir
-            self.work_dir_edit.setText(str(work_dir))
-        elif not self.work_dir:
-            return
+        try:
+            if work_dir:
+                self.work_dir = work_dir
+                self.work_dir_edit.setText(str(work_dir))
+            elif not self.work_dir:
+                return
 
-        work_path = Path(self.work_dir)
-        pred_dir = work_path / "11_12_13_predictions"
+            work_path = Path(self.work_dir)
+            pred_dir = work_path / "11_12_13_predictions"
 
-        # 按优先级寻找存在的目录
-        candidates = [
-            pred_dir / "Machine_Learning_Prediction",
-            pred_dir / "Non_Empirical_Prediction",
-            pred_dir / "Custom_Regression_Prediction",
-            work_path / "14_visualization",
-            work_path,
-        ]
-        detected_dir = None
-        for candidate in candidates:
-            if candidate.exists() and candidate.is_dir():
-                detected_dir = candidate
-                break
+            # 按优先级寻找存在的目录
+            candidates = [
+                pred_dir / "Machine_Learning_Prediction",
+                pred_dir / "Non_Empirical_Prediction",
+                pred_dir / "Custom_Regression_Prediction",
+                work_path / "14_visualization",
+                work_path,
+            ]
+            detected_dir = None
+            for candidate in candidates:
+                if candidate.exists() and candidate.is_dir():
+                    detected_dir = candidate
+                    break
 
-        if detected_dir:
-            detected_str = str(detected_dir)
-            self.img_dir_edit.setText(detected_str)
-            self.image_tree.scan_directory(detected_str)
-        else:
-            # 无预测目录时扫描整个工作目录
-            self.image_tree.scan_directory(self.work_dir)
+            if detected_dir:
+                detected_str = str(detected_dir)
+                self.img_dir_edit.setText(detected_str)
+                self.image_tree.scan_directory(detected_str)
+            else:
+                # 无预测目录时扫描整个工作目录
+                self.image_tree.scan_directory(self.work_dir)
 
-        # 自动触发加载第一张图像
-        self._load_first_image_from_tree()
+            # 自动触发加载第一张图像
+            self._load_first_image_from_tree()
+        except Exception as e:
+            import traceback
+            print(f"可视化面板 update_from_config 出错: {e}")
+            traceback.print_exc()
 
     def _load_first_image_from_tree(self):
-        """从目录树中加载第一张图像到右侧查看器"""
-        tree = self.image_tree
-        if tree is None:
-            return
-        for category_item in tree.category_items.values():
-            for i in range(category_item.childCount()):
-                child = category_item.child(i)
-                data = child.data(0, Qt.UserRole)
-                if data and data.get("type") == "image":
-                    img_path = data.get("path")
-                    if img_path and Path(img_path).exists():
-                        self.image_viewer.load_image(img_path)
-                        return
+        """自动加载树状图中的第一张有效图片（兼容物理目录层级结构）"""
+        try:
+            tree = getattr(self, 'image_tree', None)
+            if not tree:
+                return
+
+            from PyQt5.QtCore import Qt
+
+            def find_first_image(item):
+                # 检查当前节点是否是图片节点
+                data = item.data(0, Qt.UserRole)
+                if isinstance(data, dict) and data.get("type") == "image":
+                    return item
+                # 如果不是，递归检查所有子节点
+                for i in range(item.childCount()):
+                    found = find_first_image(item.child(i))
+                    if found:
+                        return found
+                return None
+
+            # 遍历所有顶层节点
+            for i in range(tree.topLevelItemCount()):
+                first_img_item = find_first_image(tree.topLevelItem(i))
+                if first_img_item:
+                    tree.setCurrentItem(first_img_item)
+                    # 主动触发一次点击槽函数，以在右侧渲染图片
+                    self.on_tree_item_clicked(first_img_item, 0)
+                    return
+        except Exception as e:
+            import traceback
+            print(f"自动加载首张图片失败: {e}")
+            traceback.print_exc()
 
     def scan_work_directory(self):
         """扫描工作目录中的图像文件"""

src/gui/water_quality_gui.py

@@ -29,6 +29,18 @@ from PyQt5.QtWidgets import (
 from PyQt5.QtCore import QThread, pyqtSignal, Qt, QTimer, QAbstractTableModel, QSize
 from PyQt5.QtGui import QIcon, QFont, QTextCursor, QPalette, QColor, QPixmap
 
+import sys
+import traceback
+
+def global_exception_handler(exc_type, exc_value, exc_traceback):
+    print("\n" + "="*50)
+    print("【严重错误拦截 - PyQt 崩溃死因】")
+    traceback.print_exception(exc_type, exc_value, exc_traceback)
+    print("="*50 + "\n")
+
+# 挂载全局异常钩子，阻止 PyQt 静默闪退
+sys.excepthook = global_exception_handler
+
 # 导入样式模块 - 兼容开发环境和 PyInstaller 打包
 try:
     from styles import ModernStylesheet