形状描边修复

konabot/plugins/fx_process/fx_handle.py

@@ -1191,6 +1191,10 @@ class ImageFilterImplement:
         
         # 创建描边图像
         stroke_img = np.zeros_like(img)
+
+        # 如果没有轮廓，直接返回原图
+        if not expanded_contours[0].any():
+            return image
         cv2.fillPoly(stroke_img, expanded_contours, ColorHandle.parse_color(stroke_color) + (255,))
 
         # 轮廓图像转为PIL格式

konabot/plugins/fx_process/math_helper.py

@@ -9,37 +9,24 @@ def fix_with_shapely(contours: list) -> np.ndarray:
     """
     使用Shapely库处理复杂自相交
     """
-    fixed_results = []
+    fixed_polygons = []
     for contour in contours:
         # 转换输入为正确的格式
         contour_array = contour.reshape(-1, 2)
         # 转换为Shapely多边形
         polygon = Polygon(contour_array)
-        
-        # 修复自相交
         if not polygon.is_valid:
-            polygon = polygon.buffer(0)  # 修复无效多边形
+            polygon = polygon.buffer(0)
-        
+        fixed_polygons.append(polygon)
-        # 提取修复后的轮廓点
-        if polygon.geom_type == 'Polygon':
-            fixed_points = np.array(polygon.exterior.coords, dtype=np.int32)
-        elif polygon.geom_type == 'MultiPolygon':
-            # 处理多个多边形
-            largest = max(polygon.geoms, key=lambda p: p.area)
-            fixed_points = np.array(largest.exterior.coords, dtype=np.int32)
-        
-        fixed_results.append(fixed_points.reshape(-1, 1, 2))
     # 接下来把所有轮廓合并为一个
-    if len(fixed_results) > 1:
+    if len(fixed_polygons) >= 1:
-        merged_polygon = unary_union([Polygon(cnt.reshape(-1, 2)) for cnt in fixed_results])
+        merged_polygon = unary_union(fixed_polygons)
         if merged_polygon.geom_type == 'Polygon':
             merged_points = np.array(merged_polygon.exterior.coords, dtype=np.int32)
         elif merged_polygon.geom_type == 'MultiPolygon':
             largest = max(merged_polygon.geoms, key=lambda p: p.area)
             merged_points = np.array(largest.exterior.coords, dtype=np.int32)
         return [merged_points.reshape(-1, 1, 2)]
-    elif len(fixed_results) == 1:
-        return [fixed_results[0]]
     else:
         logger.warning("No valid contours found after fixing with Shapely.")
         return [np.array([], dtype=np.int32).reshape(0, 1, 2)]