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add: test for mask_non_max_merge

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soumik12345 2025-07-15 15:01:36 +05:30
parent fd25f4bf81
commit ebf4b930b7
1 changed files with 172 additions and 0 deletions
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172
test/detection/test_overlap_filter.py
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@ -8,6 +8,7 @@ from supervision.detection.overlap_filter import (
box_non_max_suppression,
group_overlapping_boxes,
mask_non_max_suppression,
mask_non_max_merge,
)
@ -447,3 +448,174 @@ def test_mask_non_max_suppression(
predictions=predictions, masks=masks, iou_threshold=iou_threshold
)
assert np.array_equal(result, expected_result)
@pytest.mark.parametrize(
"predictions, masks, iou_threshold, expected_result, exception",
[
(
np.empty((0, 6)),
np.empty((0, 5, 5)),
0.5,
[],
DoesNotRaise(),
), # empty predictions and masks
(
np.array([[0, 0, 0, 0, 0.8]]),
np.array(
[
[
[False, False, False, False, False],
[False, True, True, True, False],
[False, True, True, True, False],
[False, True, True, True, False],
[False, False, False, False, False],
]
]
),
0.5,
[[0]],
DoesNotRaise(),
), # single mask with no category
(
np.array([[0, 0, 0, 0, 0.8, 0]]),
np.array(
[
[
[False, False, False, False, False],
[False, True, True, True, False],
[False, True, True, True, False],
[False, True, True, True, False],
[False, False, False, False, False],
]
]
),
0.5,
[[0]],
DoesNotRaise(),
), # single mask with category
(
np.array([[0, 0, 0, 0, 0.9], [0, 0, 0, 0, 0.8]]),
np.array(
[
[
[False, False, False, False, False],
[False, True, True, False, False],
[False, True, True, False, False],
[False, False, False, False, False],
[False, False, False, False, False],
],
[
[False, False, False, False, False],
[False, False, False, False, False],
[False, False, False, True, True],
[False, False, False, True, True],
[False, False, False, False, False],
],
]
),
0.5,
[[0], [1]],
DoesNotRaise(),
), # two masks non-overlapping with no category
(
np.array([[0, 0, 0, 0, 0.9], [0, 0, 0, 0, 0.8]]),
np.array(
[
[
[False, False, False, False, False],
[False, True, True, True, False],
[False, True, True, True, False],
[False, True, True, True, False],
[False, False, False, False, False],
],
[
[False, False, False, False, False],
[False, False, True, True, True],
[False, False, True, True, True],
[False, False, True, True, True],
[False, False, False, False, False],
],
]
),
0.2,
[[0, 1]],
DoesNotRaise(),
), # two masks partially overlapping with no category
(
np.array([[0, 0, 0, 0, 0.9, 0], [0, 0, 0, 0, 0.8, 1]]),
np.array(
[
[
[False, False, False, False, False],
[False, True, True, True, False],
[False, True, True, True, False],
[False, True, True, True, False],
[False, False, False, False, False],
],
[
[False, False, False, False, False],
[False, False, True, True, True],
[False, False, True, True, True],
[False, False, True, True, True],
[False, False, False, False, False],
],
]
),
0.2,
[[0], [1]],
DoesNotRaise(),
), # two masks partially overlapping with different category
(
np.array(
[
[0, 0, 0, 0, 0.9, 0],
[0, 0, 0, 0, 0.8, 0],
[0, 0, 0, 0, 0.85, 1],
]
),
np.array(
[
[ # mask 0, class 0
[False, False, False, False, False],
[False, True, True, True, False],
[False, True, True, True, False],
[False, True, True, True, False],
[False, False, False, False, False],
],
[ # mask 1, class 0
[False, False, False, False, False],
[False, False, True, True, True],
[False, False, True, True, True],
[False, False, True, True, True],
[False, False, False, False, False],
],
[ # mask 2, class 1
[False, False, False, False, False],
[False, False, False, True, True],
[False, False, False, True, True],
[False, False, False, False, False],
[False, False, False, False, False],
],
]
),
0.2,
[[0, 1], [2]],
DoesNotRaise(),
), # three masks, two overlapping with same class
],
)
def test_mask_non_max_merge(
predictions: np.ndarray,
masks: np.ndarray,
iou_threshold: float,
expected_result: List[List[int]],
exception: Exception,
) -> None:
with exception:
result = mask_non_max_merge(
predictions=predictions, masks=masks, iou_threshold=iou_threshold
)
result = sorted([sorted(group) for group in result])
expected_result = sorted([sorted(group) for group in expected_result])
assert result == expected_result