fix:保全代理报错

mower/solvers/sss/sss_ope.py

@@ -2,6 +2,7 @@ from mower.utils import config
 from mower.utils.graph import SceneGraphSolver
 from mower.utils.recognize import Scene
 
+from .sss_navi import SSSNaviSolver
 from .utils import is_full
 
 
@@ -45,4 +46,4 @@ class SSSOpeSolver(SceneGraphSolver):
                 return
             self.tap("sss/ope/use")
         else:
-            self.scene_graph_step(Scene.SSS_START)
+            SSSNaviSolver().run()

mower/utils/image.py

@@ -243,7 +243,7 @@ def template(
             cv2.rectangle(
                 disp, max_loc, (max_loc[0] + w, max_loc[1] + h), (0, 255, 0), 3
             )
-            plt.imshow(disp)
+            plt.imshow(disp, cmap="gray", vmin=0, vmax=255)
             plt.show()
         return score, scope
     except Exception as e:
@@ -312,8 +312,16 @@ def horizontal_stitch(images: list) -> np.ndarray:
         prev_img = stitched_image
         curr_img = images[i]
         # 转为灰度图，用于计算重叠区域
-        gray_prev = cv2.cvtColor(prev_img, cv2.COLOR_RGB2GRAY)
-        gray_curr = cv2.cvtColor(curr_img, cv2.COLOR_RGB2GRAY)
+        gray_prev = (
+            prev_img
+            if len(prev_img.shape) == 2
+            else cv2.cvtColor(prev_img, cv2.COLOR_RGB2GRAY)
+        )
+        gray_curr = (
+            curr_img
+            if len(curr_img.shape) == 2
+            else cv2.cvtColor(curr_img, cv2.COLOR_RGB2GRAY)
+        )
         # 匹配 prev_img 的右侧区域和 curr_img 的左侧区域
         match_width = min(800, gray_prev.shape[1])  # 假设重叠区域宽度最大为 800 像素
         prev_region = gray_prev[:, -match_width:]  # 取 prev_img 的右侧区域