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79 lines
1.6 KiB
79 lines
1.6 KiB
#include "test_precomp.hpp" |
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#include <iostream> |
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#include "npy_blob.hpp" |
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namespace cvtest |
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{ |
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using namespace std; |
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using namespace testing; |
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using namespace cv; |
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using namespace cv::dnn; |
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static std::string getOpenCVExtraDir() |
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{ |
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return cvtest::TS::ptr()->get_data_path(); |
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} |
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template<typename TStr> |
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static std::string getTestFile(TStr filename) |
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{ |
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return (getOpenCVExtraDir() + "/dnn/layers/") + filename; |
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} |
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template<typename T, int n> |
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bool isEqual(const cv::Vec<T, n> &l, const cv::Vec<T, n> &r) |
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{ |
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for (int i = 0; i < n; i++) |
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{ |
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if (l[i] != r[i]) |
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return false; |
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} |
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return true; |
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} |
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static void testLayer(String proto, String caffemodel = String()) |
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{ |
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Blob inp = blobFromNPY(getTestFile("blob.npy")); |
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Blob ref = blobFromNPY(getTestFile(proto + ".caffe.npy")); |
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Net net; |
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{ |
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Ptr<Importer> importer = createCaffeImporter(getTestFile(proto), caffemodel); |
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ASSERT_TRUE(importer != NULL); |
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importer->populateNet(net); |
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} |
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net.setBlob("input", inp); |
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net.forward(); |
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Blob out = net.getBlob("output"); |
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EXPECT_TRUE(isEqual(ref.shape(), out.shape())); |
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Mat &mRef = ref.getMatRef(); |
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Mat &mOut = out.getMatRef(); |
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size_t N = ref.total(); |
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double normL1 = cvtest::norm(mRef, mOut, NORM_L1)/N; |
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EXPECT_LE(normL1, 0.0001); |
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double normInf = cvtest::norm(mRef, mOut, NORM_INF); |
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EXPECT_LE(normInf, 0.0001); |
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} |
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TEST(Layer_Softmax_Test, Accuracy) |
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{ |
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testLayer("softmax.prototxt"); |
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} |
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TEST(Layer_LRN_spatial_Test, Accuracy) |
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{ |
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testLayer("lrn_spatial.prototxt"); |
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} |
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TEST(Layer_LRN_channels_Test, Accuracy) |
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{ |
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testLayer("lrn_channels.prototxt"); |
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} |
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}
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