diff --git a/modules/python/test/test_fitline.py b/modules/python/test/test_fitline.py
index 2197f8db7f..3a04708a68 100644
--- a/modules/python/test/test_fitline.py
+++ b/modules/python/test/test_fitline.py
@@ -55,7 +55,7 @@ class fitline_test(NewOpenCVTests):
         for name in dist_func_names:
             func = getattr(cv, name)
             vx, vy, cx, cy = cv.fitLine(np.float32(points), func, 0, 0.01, 0.01)
-            line = [float(vx), float(vy), float(cx), float(cy)]
+            line = [vx[0], vy[0], cx[0], cy[0]]
             lines.append(line)
 
         eps = 0.05
diff --git a/modules/python/test/test_mser.py b/modules/python/test/test_mser.py
index c76e9d4c79..596c82adb5 100644
--- a/modules/python/test/test_mser.py
+++ b/modules/python/test/test_mser.py
@@ -8,6 +8,7 @@ from __future__ import print_function
 
 import numpy as np
 import cv2 as cv
+import random
 
 from tests_common import NewOpenCVTests
 
@@ -31,19 +32,18 @@ class mser_test(NewOpenCVTests):
          [255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255],
          [255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255]
         ]
-        thresharr = [ 0, 70, 120, 180, 255 ]
         kDelta = 5
         mserExtractor = cv.MSER_create()
         mserExtractor.setDelta(kDelta)
-        np.random.seed(10)
+        random.seed(10)
 
         for _i in range(100):
 
-            use_big_image = int(np.random.rand(1,1)*7) != 0
-            invert = int(np.random.rand(1,1)*2) != 0
-            binarize = int(np.random.rand(1,1)*5) != 0 if use_big_image else False
-            blur = int(np.random.rand(1,1)*2) != 0
-            thresh = thresharr[int(np.random.rand(1,1)*5)]
+            use_big_image = random.choice([True, False])
+            invert = random.choice([True, False])
+            binarize = random.choice([True, False]) if use_big_image else False
+            blur = random.choice([True, False])
+            thresh = random.choice([0, 70, 120, 180, 255])
             src0 = img if use_big_image else np.array(smallImg).astype('uint8')
             src = src0.copy()