Rare test failures on windows CI

[zhiltsov-max]

It doesn't fail every time.

Example: https://github.com/openvinotoolkit/datumaro/pull/407/checks?check_run_id=3359354762

__________________________ BytesImageTest.test_ctors __________________________

self = <tests.test_images.BytesImageTest testMethod=test_ctors>

    @mark_requirement(Requirements.DATUM_GENERAL_REQ)
    def test_ctors(self):
        with TestDir() as test_dir:
            path = osp.join(test_dir, 'path.png')
            image = np.ones([2, 4, 3])
            image_bytes = encode_image(image, 'png')
    
            for args in [
                { 'data': image_bytes },
                { 'data': lambda _: image_bytes },
                { 'data': lambda _: image_bytes, 'ext': '.jpg' },
                { 'data': image_bytes, 'path': path },
                { 'data': image_bytes, 'path': path, 'size': (2, 4) },
                { 'data': image_bytes, 'path': path, 'size': (2, 4) },
                { 'path': path },
                { 'path': path, 'size': (2, 4) },
            ]:
                with self.subTest(**args):
                    img = ByteImage(**args)
                    # pylint: disable=pointless-statement
                    self.assertEqual('data' in args, img.has_data)
                    if img.has_data:
>                       self.assertEqual(img, image)

tests\test_images.py:126: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
datumaro\util\image.py:366: in __eq__
    return super().__eq__(other)
datumaro\util\image.py:311: in __eq__
    return self.has_data and np.array_equal(self.data, other)
datumaro\util\image.py:282: in data
    data = self._data()
datumaro\util\image.py:227: in __call__
    image = self.loader(self.path)
datumaro\util\image.py:338: in <lambda>
    loader = lambda _: decode_image(self.get_bytes())
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

image_bytes = <object object at 0x0000025118C7B6D0>
dtype = <class 'numpy.float32'>

    def decode_image(image_bytes, dtype=np.float32):
        if _IMAGE_BACKEND == _IMAGE_BACKENDS.cv2:
            import cv2
>           image = np.frombuffer(image_bytes, dtype=np.uint8)
E           TypeError: a bytes-like object is required, not 'object'

datumaro\util\image.py:155: TypeError