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Add comprehensive unittests for KeyPoints functionality (#2109)

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* Add comprehensive unittests for KeyPoints functionality
* fix(pre_commit): 🎨 auto format pre-commit hooks
* Refactor and expand KeyPoints tests for improved coverage

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
This commit is contained in:
Jirka Borovecandpre-commit-ci[bot] authored and GitHub committed 2026-01-29 16:50:11 +01:00
1 parent a765bd9bd7
commit beaa0be014
1 file changed
+183 -18
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test/key_points/test_core.py
+183 -18
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@@ -235,29 +235,13 @@ KEY_POINTS = _create_key_points(
(
KEY_POINTS,
(0, 0),
_create_key_points(
xy=[
[[0, 1]],
],
confidence=[
[0.8],
],
class_id=[0],
),
_create_key_points(xy=[[[0, 1]]], confidence=[[0.8]], class_id=[0]),
DoesNotRaise(),
), # select the first anchor from the first skeleton by index
(
KEY_POINTS,
(0, -1),
_create_key_points(
xy=[
[[8, 9]],
],
confidence=[
[0.5],
],
class_id=[0],
),
_create_key_points(xy=[[[8, 9]]], confidence=[[0.5]], class_id=[0]),
DoesNotRaise(),
), # select the last anchor from the first skeleton by index
],
@@ -266,3 +250,184 @@ def test_key_points_getitem(key_points, index, expected_result, exception):
with exception:
result = key_points[index]
assert result == expected_result
def test_key_points_empty():
"""Test the creation and behavior of an empty KeyPoints object."""
empty_key_points = KeyPoints.empty()
assert len(empty_key_points) == 0
assert empty_key_points.is_empty()
assert empty_key_points.xy.shape == (0, 0, 2)
def test_key_points_is_empty():
"""Test the is_empty method for KeyPoints objects."""
empty_key_points = KeyPoints.empty()
assert empty_key_points.is_empty()
non_empty_key_points = _create_key_points(
xy=[[[0, 1], [2, 3]]],
confidence=[[0.8, 0.9]],
class_id=[0],
)
assert not non_empty_key_points.is_empty()
def test_key_points_setitem():
"""Test the __setitem__ method for KeyPoints objects."""
key_points = _create_key_points(
xy=[[[0, 1], [2, 3]]],
confidence=[[0.8, 0.9]],
class_id=[0],
)
key_points["custom_data"] = ["value1"]
assert "custom_data" in key_points.data
assert np.array_equal(key_points.data["custom_data"], np.array(["value1"]))
with pytest.raises(TypeError):
key_points["invalid_data"] = 123
@pytest.mark.parametrize(
("key_points", "expected_xyxy", "expected_confidence", "expected_class_id"),
[
(
_create_key_points(
xy=[[[0, 1], [2, 3], [4, 5]]],
confidence=[[0.8, 0.9, 0.7]],
class_id=[0],
),
np.array([[0, 1, 4, 5]], dtype=np.float32),
np.array([0.8], dtype=np.float32),
np.array([0]),
),
(
_create_key_points(
xy=[[[0, 0], [2, 3], [4, 5]]],
confidence=[[0.8, 0.9, 0.7]],
class_id=[0],
),
np.array([[2, 3, 4, 5]], dtype=np.float32),
np.array([0.8], dtype=np.float32),
np.array([0]),
),
],
)
def test_key_points_as_detections(
key_points, expected_xyxy, expected_confidence, expected_class_id
):
"""Test the as_detections method for KeyPoints objects."""
detections = key_points.as_detections()
assert len(detections) == len(expected_xyxy)
assert np.array_equal(detections.xyxy, expected_xyxy)
assert np.allclose(detections.confidence, expected_confidence)
assert np.array_equal(detections.class_id, expected_class_id)
def test_key_points_as_detections_empty():
"""Test the as_detections method for empty KeyPoints objects."""
empty_key_points = KeyPoints.empty()
empty_detections = empty_key_points.as_detections()
assert empty_detections.is_empty()
def test_key_points_as_detections_with_data():
"""Test the as_detections method preserves data."""
key_points = _create_key_points(
xy=[[[0, 1], [2, 3], [4, 5]]],
confidence=[[0.8, 0.9, 0.7]],
class_id=[0],
)
key_points["custom_data"] = ["value1"]
detections = key_points.as_detections()
assert "custom_data" in detections.data
assert np.array_equal(detections.data["custom_data"], np.array(["value1"]))
def test_key_points_iteration():
"""Test the iteration over KeyPoints objects."""
key_points = _create_key_points(
xy=[[[0, 1], [2, 3]], [[4, 5], [6, 7]]],
confidence=[[0.8, 0.9], [0.7, 0.6]],
class_id=[0, 1],
)
iterations = 0
for i, (xy, confidence, class_id, data) in enumerate(key_points):
iterations += 1
assert xy.shape == (2, 2)
assert confidence.shape == (2,)
assert class_id in [0, 1]
assert isinstance(data, dict)
assert iterations == 2
def test_key_points_iteration_no_confidence():
"""Test the iteration over KeyPoints objects without confidence."""
key_points_no_conf = _create_key_points(
xy=[[[0, 1], [2, 3]]],
confidence=None,
class_id=[0],
)
for xy, confidence, class_id, data in key_points_no_conf:
assert confidence is None
@pytest.mark.parametrize(
("key_points1", "key_points2", "expected_equal"),
[
(
_create_key_points(
xy=[[[0, 1], [2, 3]]], confidence=[[0.8, 0.9]], class_id=[0]
),
_create_key_points(
xy=[[[0, 1], [2, 3]]], confidence=[[0.8, 0.9]], class_id=[0]
),
True,
),
(
_create_key_points(
xy=[[[0, 1], [2, 3]]], confidence=[[0.8, 0.9]], class_id=[0]
),
_create_key_points(
xy=[[[0, 1], [2, 3]]], confidence=[[0.8, 0.9]], class_id=[1]
),
False,
),
(
_create_key_points(
xy=[[[0, 1], [2, 3]]], confidence=[[0.8, 0.9]], class_id=[0]
),
_create_key_points(
xy=[[[0, 1], [2, 4]]], confidence=[[0.8, 0.9]], class_id=[0]
),
False,
),
(
_create_key_points(
xy=[[[0, 1], [2, 3]]], confidence=[[0.8, 0.9]], class_id=[0]
),
_create_key_points(
xy=[[[0, 1], [2, 3]]], confidence=[[0.8, 0.8]], class_id=[0]
),
False,
),
],
)
def test_key_points_equality(key_points1, key_points2, expected_equal):
"""Test the equality comparison for KeyPoints objects."""
status = key_points1 == key_points2
assert status is expected_equal
def test_key_points_equality_with_data():
"""Test the equality comparison for KeyPoints objects with data."""
key_points1 = _create_key_points(
xy=[[[0, 1], [2, 3]]], confidence=[[0.8, 0.9]], class_id=[0]
)
key_points2 = _create_key_points(
xy=[[[0, 1], [2, 3]]], confidence=[[0.8, 0.9]], class_id=[0]
)
key_points2["custom"] = ["value"]
assert key_points1 != key_points2