It seems that this test does not PASS
@unittest.skipUnless(ocl, "PyOpenCl is missing")
def testOpenCLMedFilt2d(self):
"""test cpp engine for medfilt2d"""
res = medianfilter.medfilt2d(
image=TestMedianFilterEngines.IMG,
kernel_size=TestMedianFilterEngines.KERNEL,
engine='opencl')
self.assertTrue(numpy.array_equal(res, TestMedianFilterEngines.IMG))
testOpenCLMedFilt2d (silx.image.test.test_medianfilter.TestMedianFilterEngines)
test cpp engine for medfilt2d ... pocl error: lt_dlopen("(null)") or lt_dlsym()
failed with 'can't close resident module'.
note: missing symbols in the kernel binary might be reported as 'file not
found' errors.
Aborted
E: pybuild pybuild:341: test: plugin custom failed with: exit code=134: env
PYTHONPATH=/home/picca/silx-0.11.0+dfsg/.pybuild/cpython3_3.8_silx/build
WITH_QT_TEST=False xvfb-run -a --server-args="-screen 0 1024x768x24" python3.8
run_tests.py -vv --installed
dh_auto_test: pybuild --test -i python{version} -p "3.8 3.7" -s custom
"--test-args=env PYTHONPATH={build_dir} WITH_QT_TEST=False xvfb-run -a
--server-args=\"-screen 0 1024x768x24\" {interpreter} run_tests.py -vv
--installed" returned exit code 13
make[1]: *** [debian/rules:70: override_dh_auto_test] Error 255
make[1]: Leaving directory '/home/picca/silx-0.11.0+dfsg'
make: *** [debian/rules:27: build] Error 2
the code of medfilt2d is there
def medfilt2d(image, kernel_size=3, engine='cpp'):
"""Apply a median filter on an image.
This median filter is using a 'nearest' padding for values
past the array edges. If you want more padding options or
functionalities for the median filter (conditional filter
for example) please have a look at
:mod:`silx.math.medianfilter`.
:param numpy.ndarray image: the 2D array for which we want to apply
the median filter.
:param kernel_size: the dimension of the kernel.
Kernel size must be odd.
If a scalar is given, then it is used as the size in both dimension.
Default: (3, 3)
:type kernel_size: A int or a list of 2 int (kernel_height, kernel_width)
:param engine: the type of implementation to use.
Valid values are: 'cpp' (default) and 'opencl'
:returns: the array with the median value for each pixel.
.. note:: if the opencl implementation is requested but
is not present or fails, the cpp implementation is called.
"""
if engine not in MEDFILT_ENGINES:
err = 'silx doesn\'t have an implementation for the requested engine: '
err += '%s' % engine
raise ValueError(err)
if len(image.shape) is not 2:
raise ValueError('medfilt2d deals with arrays of dimension 2 only')
if engine == 'cpp':
return medianfilter_cpp.medfilt(data=image,
kernel_size=kernel_size,
conditional=False)
elif engine == 'opencl':
if medfilt_opencl is None:
wrn = 'opencl median filter not available. '
wrn += 'Launching cpp implementation.'
_logger.warning(wrn)
# instead call the cpp implementation
return medianfilter_cpp.medfilt(data=image,
kernel_size=kernel_size,
conditional=False)
else:
try:
medianfilter = medfilt_opencl.MedianFilter2D(image.shape,
devicetype="gpu")
res = medianfilter.medfilt2d(image, kernel_size)
except(RuntimeError, MemoryError, ImportError):
wrn = 'Exception occured in opencl median filter. '
wrn += 'To get more information see debug log.'
wrn += 'Launching cpp implementation.'
_logger.warning(wrn)
_logger.debug("median filter - openCL implementation issue.",
exc_info=True)
# instead call the cpp implementation
res = medianfilter_cpp.medfilt(data=image,
kernel_size=kernel_size,
conditional=False)
return res
in our case we have engine = 'opencl' and no warning message, so medfil_opencl
should not be None.
it comes from here
from silx.opencl import medfilt as medfilt_opencl
In this code we have
:param devicetype: type of device, can be "CPU", "GPU", "ACC" or "ALL"
So let's do a first test by replacing gpu by cpu to see if it change something
during the test.
