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#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Project: Median filter of images + OpenCL
# https://github.com/silx-kit/silx
#
# Permission is hereby granted, free of charge, to any person
# obtaining a copy of this software and associated documentation
# files (the "Software"), to deal in the Software without
# restriction, including without limitation the rights to use,
# copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the
# Software is furnished to do so, subject to the following
# conditions:
#
# The above copyright notice and this permission notice shall be
# included in all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
# EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
# OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
# NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
# HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
# WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
# FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
# OTHER DEALINGS IN THE SOFTWARE.
"""
Simple test of the median filter
"""
from __future__ import division, print_function
__authors__ = ["Jérôme Kieffer"]
__contact__ = "jerome.kieffer@esrf.eu"
__license__ = "MIT"
__copyright__ = "2013-2017 European Synchrotron Radiation Facility, Grenoble, France"
__date__ = "15/03/2017"
import sys
import time
import logging
import numpy
import unittest
from collections import namedtuple
try:
import mako
except ImportError:
mako = None
from ..common import ocl
if ocl:
import pyopencl
import pyopencl.array
from .. import medfilt
logger = logging.getLogger(__name__)
Result = namedtuple("Result", ["size", "error", "sp_time", "oc_time"])
try:
from scipy.misc import ascent
except:
def ascent():
"""Dummy image from random data"""
return numpy.random.random((512, 512))
try:
from scipy.ndimage import filters
median_filter = filters.median_filter
HAS_SCIPY = True
except:
HAS_SCIPY = False
from silx.math import medfilt2d as median_filter
@unittest.skipUnless(ocl and mako, "PyOpenCl is missing")
class TestMedianFilter(unittest.TestCase):
def setUp(self):
if ocl is None:
return
self.data = ascent().astype(numpy.float32)
self.medianfilter = medfilt.MedianFilter2D(self.data.shape, devicetype="gpu")
def tearDown(self):
self.data = None
self.medianfilter = None
def measure(self, size):
"Common measurement of accuracy and timings"
t0 = time.time()
if HAS_SCIPY:
ref = median_filter(self.data, size, mode="nearest")
else:
ref = median_filter(self.data, size)
t1 = time.time()
try:
got = self.medianfilter.medfilt2d(self.data, size)
except RuntimeError as msg:
logger.error(msg)
return
t2 = time.time()
delta = abs(got - ref).max()
return Result(size, delta, t1 - t0, t2 - t1)
@unittest.skipUnless(ocl and mako, "pyopencl is missing")
def test_medfilt(self):
"""
tests the median filter kernel
"""
r = self.measure(size=11)
if r is None:
logger.info("test_medfilt: size: %s: skipped")
else:
logger.info("test_medfilt: size: %s error %s, t_ref: %.3fs, t_ocl: %.3fs" % r)
self.assert_(r.error == 0, 'Results are correct')
def benchmark(self, limit=36):
"Run some benchmarking"
try:
import PyQt5
from ...gui.matplotlib import pylab
from ...gui.utils import update_fig
except:
pylab = None
def update_fig(*ag, **kwarg):
pass
fig = pylab.figure()
fig.suptitle("Median filter of an image 512x512")
sp = fig.add_subplot(1, 1, 1)
sp.set_title(self.medianfilter.ctx.devices[0].name)
sp.set_xlabel("Window width & height")
sp.set_ylabel("Execution time (s)")
sp.set_xlim(2, limit + 1)
sp.set_ylim(0, 4)
data_size = []
data_scipy = []
data_opencl = []
plot_sp = sp.plot(data_size, data_scipy, "-or", label="scipy")[0]
plot_opencl = sp.plot(data_size, data_opencl, "-ob", label="opencl")[0]
sp.legend(loc=2)
fig.show()
update_fig(fig)
for s in range(3, limit, 2):
r = self.measure(s)
print(r)
if r.error == 0:
data_size.append(s)
data_scipy.append(r.sp_time)
data_opencl.append(r.oc_time)
plot_sp.set_data(data_size, data_scipy)
plot_opencl.set_data(data_size, data_opencl)
update_fig(fig)
fig.show()
if sys.version_info[0] < 3:
raw_input()
else:
input()
def suite():
testSuite = unittest.TestSuite()
testSuite.addTest(TestMedianFilter("test_medfilt"))
return testSuite
def benchmark():
testSuite = unittest.TestSuite()
testSuite.addTest(TestMedianFilter("benchmark"))
return testSuite
if __name__ == '__main__':
unittest.main(defaultTest="suite")
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