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42
43 #include "test_precomp.hpp"
44
45
TestHaarCascadeLoader(std::string testName_,std::string cascadeName_)46 TestHaarCascadeLoader::TestHaarCascadeLoader(std::string testName_, std::string cascadeName_)
47 :
48 NCVTestProvider(testName_),
49 cascadeName(cascadeName_)
50 {
51 }
52
53
toString(std::ofstream & strOut)54 bool TestHaarCascadeLoader::toString(std::ofstream &strOut)
55 {
56 strOut << "cascadeName=" << cascadeName << std::endl;
57 return true;
58 }
59
60
init()61 bool TestHaarCascadeLoader::init()
62 {
63 return true;
64 }
65
66
process()67 bool TestHaarCascadeLoader::process()
68 {
69 NCVStatus ncvStat;
70 bool rcode = false;
71
72 Ncv32u numStages, numNodes, numFeatures;
73 Ncv32u numStages_2 = 0, numNodes_2 = 0, numFeatures_2 = 0;
74
75 ncvStat = ncvHaarGetClassifierSize(this->cascadeName, numStages, numNodes, numFeatures);
76 ncvAssertReturn(ncvStat == NCV_SUCCESS, false);
77
78 NCVVectorAlloc<HaarStage64> h_HaarStages(*this->allocatorCPU.get(), numStages);
79 ncvAssertReturn(h_HaarStages.isMemAllocated(), false);
80 NCVVectorAlloc<HaarClassifierNode128> h_HaarNodes(*this->allocatorCPU.get(), numNodes);
81 ncvAssertReturn(h_HaarNodes.isMemAllocated(), false);
82 NCVVectorAlloc<HaarFeature64> h_HaarFeatures(*this->allocatorCPU.get(), numFeatures);
83 ncvAssertReturn(h_HaarFeatures.isMemAllocated(), false);
84
85 NCVVectorAlloc<HaarStage64> h_HaarStages_2(*this->allocatorCPU.get(), numStages);
86 ncvAssertReturn(h_HaarStages_2.isMemAllocated(), false);
87 NCVVectorAlloc<HaarClassifierNode128> h_HaarNodes_2(*this->allocatorCPU.get(), numNodes);
88 ncvAssertReturn(h_HaarNodes_2.isMemAllocated(), false);
89 NCVVectorAlloc<HaarFeature64> h_HaarFeatures_2(*this->allocatorCPU.get(), numFeatures);
90 ncvAssertReturn(h_HaarFeatures_2.isMemAllocated(), false);
91
92 HaarClassifierCascadeDescriptor haar;
93 HaarClassifierCascadeDescriptor haar_2;
94
95 NCV_SET_SKIP_COND(this->allocatorGPU.get()->isCounting());
96 NCV_SKIP_COND_BEGIN
97
98 const std::string testNvbinName = cv::tempfile("test.nvbin");
99 ncvStat = ncvHaarLoadFromFile_host(this->cascadeName, haar, h_HaarStages, h_HaarNodes, h_HaarFeatures);
100 ncvAssertReturn(ncvStat == NCV_SUCCESS, false);
101
102 ncvStat = ncvHaarStoreNVBIN_host(testNvbinName, haar, h_HaarStages, h_HaarNodes, h_HaarFeatures);
103 ncvAssertReturn(ncvStat == NCV_SUCCESS, false);
104
105 ncvStat = ncvHaarGetClassifierSize(testNvbinName, numStages_2, numNodes_2, numFeatures_2);
106 ncvAssertReturn(ncvStat == NCV_SUCCESS, false);
107
108 ncvStat = ncvHaarLoadFromFile_host(testNvbinName, haar_2, h_HaarStages_2, h_HaarNodes_2, h_HaarFeatures_2);
109 ncvAssertReturn(ncvStat == NCV_SUCCESS, false);
110
111 NCV_SKIP_COND_END
112
113 //bit-to-bit check
114 bool bLoopVirgin = true;
115
116 NCV_SKIP_COND_BEGIN
117
118 if (
119 numStages_2 != numStages ||
120 numNodes_2 != numNodes ||
121 numFeatures_2 != numFeatures ||
122 haar.NumStages != haar_2.NumStages ||
123 haar.NumClassifierRootNodes != haar_2.NumClassifierRootNodes ||
124 haar.NumClassifierTotalNodes != haar_2.NumClassifierTotalNodes ||
125 haar.NumFeatures != haar_2.NumFeatures ||
126 haar.ClassifierSize.width != haar_2.ClassifierSize.width ||
127 haar.ClassifierSize.height != haar_2.ClassifierSize.height ||
128 haar.bNeedsTiltedII != haar_2.bNeedsTiltedII ||
129 haar.bHasStumpsOnly != haar_2.bHasStumpsOnly )
130 {
131 bLoopVirgin = false;
132 }
133 if (memcmp(h_HaarStages.ptr(), h_HaarStages_2.ptr(), haar.NumStages * sizeof(HaarStage64)) ||
134 memcmp(h_HaarNodes.ptr(), h_HaarNodes_2.ptr(), haar.NumClassifierTotalNodes * sizeof(HaarClassifierNode128)) ||
135 memcmp(h_HaarFeatures.ptr(), h_HaarFeatures_2.ptr(), haar.NumFeatures * sizeof(HaarFeature64)) )
136 {
137 bLoopVirgin = false;
138 }
139 NCV_SKIP_COND_END
140
141 if (bLoopVirgin)
142 {
143 rcode = true;
144 }
145
146 return rcode;
147 }
148
149
deinit()150 bool TestHaarCascadeLoader::deinit()
151 {
152 return true;
153 }
154