I had a case where the test failed one time with the following error:
FAIL: test_detect_faces (tests.test_opencv.TestOpenCVOperations.test_detect_faces)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/tmp/autopkgtest.BPuIbH/autopkgtest_tmp/tests/test_opencv.py", line 74, in test_detect_faces
assert_allclose(faces, self.expected_faces, atol=2)
File "/usr/lib/python3/dist-packages/numpy/testing/_private/utils.py", line 1592, in assert_allclose
assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
File "/usr/lib/python3.11/contextlib.py", line 81, in inner
return func(*args, **kwds)
^^^^^^^^^^^^^^^^^^^
File "/usr/lib/python3/dist-packages/numpy/testing/_private/utils.py", line 862, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Not equal to tolerance rtol=1e-07, atol=2
Mismatched elements: 8 / 8 (100%)
Max absolute difference: 182
Max relative difference: 1.98901099
x: array([[ 90, 164, 188, 262],
[272, 88, 365, 181]], dtype=int32)
y: array([[272, 89, 364, 181],
[ 91, 165, 187, 261]])
As can be seen, this is essentially the same array just ordered differently. I think in the context of detecting faces that should be okay? I don't know if there is a why to test this though, maybe one can sort the outer array.
I had a case where the test failed one time with the following error:
As can be seen, this is essentially the same array just ordered differently. I think in the context of detecting faces that should be okay? I don't know if there is a why to test this though, maybe one can sort the outer array.
Most of the time, the test does not seem to fail.