diff --git a/data_sub/test_3/return_objs_data.json b/data_sub/test_3/data_sub.json
similarity index 100%
rename from data_sub/test_3/return_objs_data.json
rename to data_sub/test_3/data_sub.json
diff --git a/search.py b/search.py
index 11d1a82..9f7241a 100644
--- a/search.py
+++ b/search.py
@@ -335,11 +335,11 @@ if __name__ == "__main__":
     # _im_edge_sobel = _sobel(sub_zero)
     # _, _im_thresh = cv2.threshold(_im_edge_sobel, 5, 255, cv2.THRESH_BINARY)
     # cnts = _findContours(_im_thresh)
-    original_rectangle = read_from_json("data_sub/test_2/data_sub.json")
+    original_rectangle = read_from_json("data_sub/test_3/data_sub.json")
     # 过滤矩形
     # cnts 过滤之后的矩形
     # sub_im 裁剪之后的图像
-    cnts,sub_im = filter_rectangle("data_sub/test_2/wide_image.png", original_rectangle)
+    cnts,sub_im = filter_rectangle("data_sub/test_3/wide_image.png", original_rectangle)
     sub_zero = np.zeros_like(sub_im)
     for contour in cnts:
         # x, y, w, h = cv2.boundingRect(contour)
@@ -453,7 +453,6 @@ if __name__ == "__main__":
         polar_list.append([r, theta])
     sum_r /= count * sub_roi_w_base_len
     sum_theta /= count
-    print(count, sum_r, sum_theta)
     print(f"[所有点到该预埋件左上点的个数] ====== [{count}]")
     print(f"[所有点到该预埋件左上点的平均极半径] ====== [{sum_r}]")
     print(f"[所有点到该预埋件左上点的平均极角] ====== [{sum_theta}]")
@@ -522,7 +521,12 @@ if __name__ == "__main__":
             sc1 = compute_shape_context(cartesian_points1)
             sc2 = compute_shape_context(cartesian_points2)
             match_score = match_shapes(sc1, sc2)
-            print(score, match_score, tmp_count, tmp_sum_r, tmp_sum_theta)
+            print("score>0.6")
+            print(f"[score] ====== [{score}]")
+            print(f"[match_score] ====== [{match_score}]")
+            print(f"[tmp_count] ====== [{tmp_count}]")
+            print(f"[tmp_sum_r] ====== [{tmp_sum_r}]")
+            print(f"[tmp_sum_theta] ====== [{tmp_sum_theta}]")
             if match_score < 5.0: #????
                 param["start_point"] = (tmp_roi_start_x, tmp_roi_start_y)
                 param["end_point"] = (tmp_roi_end_x, tmp_roi_end_y)
@@ -551,7 +555,7 @@ if __name__ == "__main__":
             print(f"起始预埋件ID：{id}，置信度为：{score[0]}，点数量：{score[1]}，平均长度为：{score[2]}，平均角度为：{score[3]}")
             print(f"match_sscore为：{match_score}")
             bim_im = cv2.rectangle(bim_im, param["start_point"], \
-                                        param["end_point"], 100 * (i+1), 6)
+                                        param["end_point"], 100 * (i+1), 50)
     
     elapsed_time = time.time() - start_time
     print(f"Execution time: {elapsed_time:.4f} seconds")
@@ -559,10 +563,10 @@ if __name__ == "__main__":
     # sub_im = cv2.resize(sub_im, (int(sub_im.shape[1]/10), int(sub_im.shape[0]/10)))
     cv2.imshow("2", img_matches)
     # cnts的矩形画在sub_im 上
-    for i in range(len(cnts)):
-        p = cnts[i]
-        cv2.rectangle(sub_im, (p['x'], p['y']), (p['x']+p['width'],p['y']+p['height']), (0, 0, 255), 2)
-        # 写编号
-        cv2.putText(sub_im, str(i), (p['x'], p['y']), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)
-    cv2.imshow("sub_im_after_filter", sub_im)
+    # for i in range(len(cnts)):
+    #     p = cnts[i]
+    #     cv2.rectangle(sub_im, (p['x'], p['y']), (p['x']+p['width'],p['y']+p['height']), (0, 0, 255), 2)
+    #     # 写编号
+    #     cv2.putText(sub_im, str(i), (p['x'], p['y']), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)
+    # cv2.imshow("sub_im_after_filter", sub_im)
     cv2.waitKey(0)
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