diff --git a/src/model_api/models/utils.py b/src/model_api/models/utils.py
index e02b77bb..c362daf2 100644
--- a/src/model_api/models/utils.py
+++ b/src/model_api/models/utils.py
@@ -124,7 +124,16 @@ def add_rotated_rects(inst_seg_result: InstanceSegmentationResult) -> RotatedSeg
         # Check if contours were found before processing
         if contours:
             contour = np.vstack(contours)
-            objects_with_rects.append(cv2.minAreaRect(contour))
+            rotated_rect = cv2.minAreaRect(contour)
+            # Adjust angle to be in (0, 90] range
+            (cx, cy), (w, h), angle = rotated_rect
+            while angle <= 0:
+                (w, h) = (h, w)
+                angle += 90
+            while angle > 90:
+                (w, h) = (h, w)
+                angle -= 90
+            objects_with_rects.append(((cx, cy), (w, h), angle))
         else:
             objects_with_rects.append(((0, 0), (0, 0), 0))
     return RotatedSegmentationResult(
diff --git a/tests/accuracy/public_scope.json b/tests/accuracy/public_scope.json
index 5be791c2..554dfa68 100644
--- a/tests/accuracy/public_scope.json
+++ b/tests/accuracy/public_scope.json
@@ -641,7 +641,7 @@
       {
         "image": "coco128/images/train2017/000000000074.jpg",
         "reference": [
-          "61, 277, 358, 382, 17 (horse): 0.998, 18312, RotatedRect: 212.000 327.000 290.000 100.000 0.000; 1, 14, 162, 321, 2 (car): 0.994, 25867, RotatedRect: 54.067 173.034 285.208 156.889 61.996; 327, 96, 341, 134, 1 (bicycle): 0.930, 279, RotatedRect: 333.500 114.000 36.000 13.000 90.000; 460, 106, 493, 148, 1 (bicycle): 0.898, 786, RotatedRect: 476.284 126.621 27.308 45.993 19.179; 294, 93, 315, 153, 1 (bicycle): 0.869, 789, RotatedRect: 304.000 124.000 58.000 18.000 90.000; 278, 109, 290, 152, 1 (bicycle): 0.817, 355, RotatedRect: 283.500 130.000 42.000 11.000 90.000; 4, 4, 102, 191, 2 (car): 0.701, 9658, RotatedRect: 51.806 97.259 184.445 95.281 89.246; 270, 93, 290, 152, 1 (bicycle): 0.660, 723, RotatedRect: 280.500 122.500 17.000 59.000 0.000; 322, 114, 343, 152, 18 (sheep): 0.520, 298, RotatedRect: 332.000 133.000 34.000 14.000 90.000; 4; [1,1280,1,1]; "
+          "61, 277, 358, 382, 17 (horse): 0.998, 18312, RotatedRect: 212.000 327.000 100.000 290.000 90.000; 1, 14, 162, 321, 2 (car): 0.994, 25867, RotatedRect: 54.067 173.034 285.208 156.889 61.996; 327, 96, 341, 134, 1 (bicycle): 0.930, 279, RotatedRect: 333.500 114.000 36.000 13.000 90.000; 460, 106, 493, 148, 1 (bicycle): 0.898, 786, RotatedRect: 476.284 126.621 27.308 45.993 19.179; 294, 93, 315, 153, 1 (bicycle): 0.869, 789, RotatedRect: 304.000 124.000 58.000 18.000 90.000; 278, 109, 290, 152, 1 (bicycle): 0.817, 355, RotatedRect: 283.500 130.000 42.000 11.000 90.000; 4, 4, 102, 191, 2 (car): 0.701, 9658, RotatedRect: 51.806 97.259 184.445 95.281 89.246; 270, 93, 290, 152, 1 (bicycle): 0.660, 723, RotatedRect: 280.500 122.500 59.000 17.000 90.000; 322, 114, 343, 152, 18 (sheep): 0.520, 298, RotatedRect: 332.000 133.000 34.000 14.000 90.000; 4; [1,1280,1,1]; "
         ]
       }
     ]