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Open Source Computer Vision Library
https://opencv.org/
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93 lines
4.1 KiB
93 lines
4.1 KiB
8 years ago
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#!/usr/bin/env python
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from __future__ import print_function
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import xml.etree.ElementTree as ET
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from glob import glob
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from pprint import PrettyPrinter as PP
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LONG_TESTS_DEBUG_VALGRIND = [
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('calib3d', 'Calib3d_InitUndistortRectifyMap.accuracy', 2017.22),
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('features2d', 'Features2d_Feature2d.no_crash', 1235.68),
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('ml', 'ML_RTrees.regression', 1423.47),
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('optflow', 'DenseOpticalFlow_DeepFlow.ReferenceAccuracy', 1360.95),
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('optflow', 'DenseOpticalFlow_DeepFlow_perf.perf/0', 1881.59),
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('optflow', 'DenseOpticalFlow_DeepFlow_perf.perf/1', 5608.75),
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('optflow', 'DenseOpticalFlow_GlobalPatchColliderDCT.ReferenceAccuracy', 5433.84),
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('optflow', 'DenseOpticalFlow_GlobalPatchColliderWHT.ReferenceAccuracy', 5232.73),
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('optflow', 'DenseOpticalFlow_SimpleFlow.ReferenceAccuracy', 1542.1),
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('photo', 'Photo_Denoising.speed', 1484.87),
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('photo', 'Photo_DenoisingColoredMulti.regression', 2447.11),
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('rgbd', 'Rgbd_Normals.compute', 1156.32),
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('shape', 'Hauss.regression', 2625.72),
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('shape', 'ShapeEMD_SCD.regression', 61913.7),
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('shape', 'Shape_SCD.regression', 3311.46),
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('tracking', 'AUKF.br_mean_squared_error', 10764.6),
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('tracking', 'UKF.br_mean_squared_error', 5228.27),
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('xfeatures2d', 'Features2d_RotationInvariance_Descriptor_BoostDesc_LBGM.regression', 1124.51),
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('xfeatures2d', 'Features2d_RotationInvariance_Descriptor_VGG120.regression', 2198.1),
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('xfeatures2d', 'Features2d_RotationInvariance_Descriptor_VGG48.regression', 1958.52),
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('xfeatures2d', 'Features2d_RotationInvariance_Descriptor_VGG64.regression', 2113.12),
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('xfeatures2d', 'Features2d_RotationInvariance_Descriptor_VGG80.regression', 2167.16),
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('xfeatures2d', 'Features2d_ScaleInvariance_Descriptor_BoostDesc_LBGM.regression', 1511.39),
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('xfeatures2d', 'Features2d_ScaleInvariance_Descriptor_VGG120.regression', 1222.07),
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('xfeatures2d', 'Features2d_ScaleInvariance_Descriptor_VGG48.regression', 1059.14),
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('xfeatures2d', 'Features2d_ScaleInvariance_Descriptor_VGG64.regression', 1163.41),
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('xfeatures2d', 'Features2d_ScaleInvariance_Descriptor_VGG80.regression', 1179.06),
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('ximgproc', 'L0SmoothTest.SplatSurfaceAccuracy', 6382.26),
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('ximgproc', 'L0SmoothTest_perf.perf/17', 2052.16),
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('ximgproc', 'RollingGuidanceFilterTest_perf.perf/59', 2760.29),
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('ximgproc', 'TypicalSet1/RollingGuidanceFilterTest.MultiThreadReproducibility/5', 1086.33),
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('ximgproc', 'TypicalSet1/RollingGuidanceFilterTest.MultiThreadReproducibility/7', 1405.05),
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('ximgproc', 'TypicalSet1/RollingGuidanceFilterTest.SplatSurfaceAccuracy/5', 1253.07),
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('ximgproc', 'TypicalSet1/RollingGuidanceFilterTest.SplatSurfaceAccuracy/7', 1599.98),
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]
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def longTestFilter(data):
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res = ['*', '-']
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for _, v, _ in data:
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res.append(v)
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return '--gtest_filter={}'.format(':'.join(res))
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# Parse one xml file, filter out tests which took less than 'timeLimit' seconds
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# Returns tuple: ( <module_name>, [ (<module_name>, <test_name>, <test_time>), ... ] )
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def parseOneFile(filename, timeLimit):
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tree = ET.parse(filename)
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root = tree.getroot()
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def guess(s, delims):
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for delim in delims:
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tmp = s.partition(delim)
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if len(tmp[1]) != 0:
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return tmp[0]
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return None
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module = guess(filename, ['_posix_', '_nt_', '__']) or root.get('cv_module_name')
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if not module:
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return (None, None)
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res = []
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for elem in root.findall('.//testcase'):
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key = '{}.{}'.format(elem.get('classname'), elem.get('name'))
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val = elem.get('time')
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if float(val) >= timeLimit:
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res.append((module, key, float(val)))
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return (module, res)
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# Parse all xml files in current folder and combine results into one list
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# Print result to the stdout
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if __name__ == '__main__':
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LIMIT = 1000
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res = []
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xmls = glob('*.xml')
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for xml in xmls:
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print('Parsing file', xml, '...')
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module, testinfo = parseOneFile(xml, LIMIT)
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if not module:
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print('SKIP')
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continue
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res.extend(testinfo)
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print('========= RESULTS =========')
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PP(indent=4, width=100).pprint(sorted(res))
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