Step4 心跳刷新 + Step10 输出目录更名与智能寻址优化

src/gui/water_quality_gui.py

@@ -1374,7 +1374,7 @@ class WaterQualityGUI(QMainWindow):
             'step7_index': "6_water_quality_indices/training_spectra_indices.csv",
             'step8_ml_train': "7_Supervised_Model_Training/",
             'step9_ml_predict': "11_12_13_predictions/Machine_Learning_Prediction/",
-            'step10_watercolor': "8_WaterIndex_Images/",
+            'step10_watercolor': "10_WaterIndex_Images/",
             'step11_map': "14_visualization/"
         }
         
@@ -2286,7 +2286,17 @@ class WaterQualityGUI(QMainWindow):
         if step_id not in self.step_default_outputs:
             return None
 
-        step_outputs = self.step_default_outputs[step_id]
+        raw = self.step_default_outputs[step_id]
+
+        # ★ 兼容扁平化后的纯字符串路径格式
+        rel_path = None
+        if isinstance(raw, str):
+            rel_path = raw
+        elif isinstance(raw, dict):
+            rel_path = raw.get(output_type) or list(raw.values())[0]
+
+        if not rel_path:
+            return None
 
         # ★ 掩膜类型列表：这些类型只接受科学数据格式
         mask_types = {'water_mask', 'glint_mask', 'boundary_mask'}
@@ -2319,12 +2329,11 @@ class WaterQualityGUI(QMainWindow):
 
         # 根据输出类型查找对应的文件
         if output_type == 'water_mask':
-            # 水域掩膜：优先查找NDWI生成的，其次是shp生成的
-            for mask_type in ['water_mask_ndwi', 'water_mask_shp']:
-                if mask_type in step_outputs:
-                    mask_path = work_path / step_outputs[mask_type]
-                    if mask_path.exists():
-                        return str(mask_path)
+            # 水域掩膜：直接用统一路径
+            if rel_path:
+                mask_path = work_path / rel_path
+                if mask_path.exists():
+                    return str(mask_path)
         elif output_type == 'reference_img':
             # 参考影像：从step1的配置中获取用户输入的影像路径
             if hasattr(self, 'step1_panel'):
@@ -2332,32 +2341,29 @@ class WaterQualityGUI(QMainWindow):
                 if img_path and Path(img_path).exists():
                     return img_path
         elif output_type == 'deglint_image':
-            # 去耀斑影像：查找step3的各种去耀斑方法输出
-            deglint_types = ['deglint_kutser', 'deglint_goodman', 'deglint_hedley', 'deglint_sugar']
-            for deglint_type in deglint_types:
-                if deglint_type in step_outputs:
-                    deglint_path = work_path / step_outputs[deglint_type]
-                    if deglint_path.exists():
-                        return str(deglint_path)
+            # 去耀斑影像：直接用统一路径
+            if rel_path:
+                deglint_path = work_path / rel_path
+                if deglint_path.exists():
+                    return str(deglint_path)
             # 还要检查插值方法生成的文件
             deglint_dir = work_path / "3_deglint"
             if deglint_dir.exists():
                 for file_path in deglint_dir.glob("interpolated_*.bsq"):
                     return str(file_path)
-        elif output_type in step_outputs:
-            # 直接匹配的输出类型
-            relative_path = step_outputs[output_type]
-            if relative_path.endswith('/'):
+        elif rel_path:
+            # 直接匹配的输出类型（统一使用 rel_path）
+            if rel_path.endswith('/'):
                 # 是目录
-                output_path = work_path / relative_path.rstrip('/')
+                output_path = work_path / rel_path.rstrip('/')
                 if output_path.exists() and output_path.is_dir():
                     return str(output_path)
             else:
                 # 是文件
-                output_path = work_path / relative_path
+                output_path = work_path / rel_path
                 if output_path.exists():
                     return str(output_path)
-        
+
         return None
 
     def scan_work_directory_for_files(self, work_path):