add assert_is_point

chainercv/utils/__init__.py

@@ -14,6 +14,7 @@
 from chainercv.utils.testing import assert_is_detection_link  # NOQA
 from chainercv.utils.testing import assert_is_image  # NOQA
 from chainercv.utils.testing import assert_is_label_dataset  # NOQA
+from chainercv.utils.testing import assert_is_point  # NOQA
 from chainercv.utils.testing import assert_is_semantic_segmentation_dataset  # NOQA
 from chainercv.utils.testing import assert_is_semantic_segmentation_link  # NOQA
 from chainercv.utils.testing import ConstantStubLink  # NOQA

chainercv/utils/testing/__init__.py

@@ -3,6 +3,7 @@
 from chainercv.utils.testing.assertions import assert_is_detection_link  # NOQA
 from chainercv.utils.testing.assertions import assert_is_image  # NOQA
 from chainercv.utils.testing.assertions import assert_is_label_dataset  # NOQA
+from chainercv.utils.testing.assertions import assert_is_point  # NOQA
 from chainercv.utils.testing.assertions import assert_is_semantic_segmentation_dataset  # NOQA
 from chainercv.utils.testing.assertions import assert_is_semantic_segmentation_link  # NOQA
 from chainercv.utils.testing.constant_stub_link import ConstantStubLink  # NOQA

chainercv/utils/testing/assertions/__init__.py

@@ -3,5 +3,6 @@
 from chainercv.utils.testing.assertions.assert_is_detection_link import assert_is_detection_link  # NOQA
 from chainercv.utils.testing.assertions.assert_is_image import assert_is_image  # NOQA
 from chainercv.utils.testing.assertions.assert_is_label_dataset import assert_is_label_dataset  # NOQA
+from chainercv.utils.testing.assertions.assert_is_point import assert_is_point  # NOQA
 from chainercv.utils.testing.assertions.assert_is_semantic_segmentation_dataset import assert_is_semantic_segmentation_dataset  # NOQA
 from chainercv.utils.testing.assertions.assert_is_semantic_segmentation_link import assert_is_semantic_segmentation_link  # NOQA

chainercv/utils/testing/assertions/assert_is_point.py

@@ -0,0 +1,43 @@
+import numpy as np
+
+
+def assert_is_point(point, mask=None, size=None):
+    """Checks if points satisfy the format.
+
+    This function checks if given points satisfy the format and
+    raises an :class:`AssertionError` when the points violate the convention.
+
+    Args:
+        point (~numpy.ndarray): Points to be checked.
+        mask (~numpy.ndarray): A mask of the points.
+            If this is :obj:`None`, all points are regarded as valid.
+        size (tuple of ints): The size of an image.
+            If this argument is specified,
+            the coordinates of valid points are checked to be within the image.
+    """
+
+    assert isinstance(point, np.ndarray), \
+        'point must be a numpy.ndarray.'
+    assert point.dtype == np.float32, \
+        'The type of point must be numpy.float32.'
+    assert point.shape[1:] == (2,), \
+        'The shape of point must be (*, 2).'
+
+    if mask is not None:
+        assert isinstance(mask, np.ndarray), \
+            'a mask of points must be a numpy.ndarray.'
+        assert mask.dtype == np.bool, \
+            'The type of mask must be numpy.bool.'
+        assert mask.ndim == 1, \
+            'The dimensionality of a mask must be one.'
+        assert mask.shape[0] == point.shape[0], \
+            'The size of the first axis should be the same for ' \
+            'corresponding point and mask.'
+        valid_point = point[mask]
+    else:
+        valid_point = point
+
+    if size is not None:
+        assert (valid_point >= 0).all() and (valid_point <= size).all(),\
+            'The coordinates of valid points ' \
+            'should not exceed the size of image.'

docs/source/reference/utils.rst

@@ -87,6 +87,10 @@ assert_is_label_dataset
 ~~~~~~~~~~~~~~~~~~~~~~~
 .. autofunction:: assert_is_label_dataset
 
+assert_is_point
+~~~~~~~~~~~~~~~
+.. autofunction:: assert_is_point
+
 assert_is_semantic_segmentation_dataset
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 .. autofunction:: assert_is_semantic_segmentation_dataset

tests/utils_tests/testing_tests/assertions_tests/test_assert_is_point.py

@@ -0,0 +1,61 @@
+import numpy as np
+import unittest
+
+from chainer import testing
+
+from chainercv.utils import assert_is_point
+
+
+@testing.parameterize(
+    # no mask and size
+    {'point': np.random.uniform(-1, 1, size=(10, 2)).astype(np.float32),
+     'valid': True},
+    {'point': ((1., 2.), (4., 8.)),
+     'valid': False},
+    {'point': np.random.uniform(-1, 1, size=(10, 2)).astype(np.int32),
+     'valid': False},
+    {'point': np.random.uniform(-1, 1, size=(10, 3)).astype(np.float32),
+     'valid': False},
+    # use mask, no size
+    {'point': np.random.uniform(-1, 1, size=(10, 2)).astype(np.float32),
+     'mask': np.random.randint(0, 2, size=(10,)).astype(np.bool),
+     'valid': True},
+    {'point': np.random.uniform(-1, 1, size=(4, 2)).astype(np.float32),
+     'mask': (True, True, True, True),
+     'valid': False},
+    {'point': np.random.uniform(-1, 1, size=(10, 2)).astype(np.float32),
+     'mask': np.random.randint(0, 2, size=(10,)).astype(np.int32),
+     'valid': False},
+    {'point': np.random.uniform(-1, 1, size=(10, 2)).astype(np.float32),
+     'mask': np.random.randint(0, 2, size=(10, 2)).astype(np.bool),
+     'valid': False},
+    {'point': np.random.uniform(-1, 1, size=(10, 2)).astype(np.float32),
+     'mask': np.random.randint(0, 2, size=(9,)).astype(np.bool),
+     'valid': False},
+    # use mask and size
+    {'point': np.random.uniform(0, 32, size=(10, 2)).astype(np.float32),
+     'mask': np.random.randint(0, 2, size=(10,)).astype(np.bool),
+     'size': (32, 32),
+     'valid': True},
+    {'point': np.random.uniform(32, 64, size=(10, 2)).astype(np.float32),
+     'mask': np.random.randint(0, 2, size=(10,)).astype(np.bool),
+     'size': (32, 32),
+     'valid': False},
+)
+class TestAssertIsPoint(unittest.TestCase):
+
+    def setUp(self):
+        if not hasattr(self, 'mask'):
+            self.mask = None
+        if not hasattr(self, 'size'):
+            self.size = None
+
+    def test_assert_is_bbox(self):
+        if self.valid:
+            assert_is_point(self.point, self.mask, self.size)
+        else:
+            with self.assertRaises(AssertionError):
+                assert_is_point(self.point, self.mask, self.size)
+
+
+testing.run_module(__name__, __file__)