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@ -46,7 +46,7 @@ namespace opencv_test { namespace { |
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class CV_ThreshTest : public cvtest::ArrayTest |
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{ |
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public: |
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CV_ThreshTest(); |
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CV_ThreshTest(int test_type = 0); |
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protected: |
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void get_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types ); |
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@ -57,16 +57,22 @@ protected: |
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int thresh_type; |
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double thresh_val; |
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double max_val; |
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int extra_type; |
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}; |
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CV_ThreshTest::CV_ThreshTest() |
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CV_ThreshTest::CV_ThreshTest(int test_type) |
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{ |
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CV_Assert( (test_type & CV_THRESH_MASK) == 0 ); |
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test_array[INPUT].push_back(NULL); |
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test_array[OUTPUT].push_back(NULL); |
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test_array[REF_OUTPUT].push_back(NULL); |
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optional_mask = false; |
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element_wise_relative_error = true; |
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extra_type = test_type; |
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// Reduce number of test with automated thresholding
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if (extra_type != 0) |
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test_case_count = 250; |
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} |
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@ -78,6 +84,12 @@ void CV_ThreshTest::get_test_array_types_and_sizes( int test_case_idx, |
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cvtest::ArrayTest::get_test_array_types_and_sizes( test_case_idx, sizes, types ); |
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depth = depth == 0 ? CV_8U : depth == 1 ? CV_16S : depth == 2 ? CV_16U : depth == 3 ? CV_32F : CV_64F; |
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if ( extra_type == CV_THRESH_OTSU ) |
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{ |
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depth = cvtest::randInt(rng) % 2 == 0 ? CV_8U : CV_16U; |
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cn = 1; |
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} |
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types[INPUT][0] = types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_MAKETYPE(depth,cn); |
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thresh_type = cvtest::randInt(rng) % 5; |
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@ -123,18 +135,73 @@ double CV_ThreshTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, |
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void CV_ThreshTest::run_func() |
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{ |
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cvThreshold( test_array[INPUT][0], test_array[OUTPUT][0], |
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thresh_val, max_val, thresh_type ); |
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thresh_val, max_val, thresh_type | extra_type); |
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} |
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static double compute_otsu_thresh(const Mat& _src) |
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{ |
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int depth = _src.depth(); |
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int width = _src.cols, height = _src.rows; |
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const int N = 65536; |
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std::vector<int> h(N, 0); |
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int i, j; |
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double mu = 0, scale = 1./(width*height); |
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for(i = 0; i < height; ++i) |
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{ |
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for(j = 0; j < width; ++j) |
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{ |
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const int val = depth == CV_16UC1 ? (int)_src.at<ushort>(i, j) : (int)_src.at<uchar>(i,j); |
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h[val]++; |
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} |
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} |
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for( i = 0; i < N; i++ ) |
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{ |
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mu += i*(double)h[i]; |
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} |
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mu *= scale; |
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double mu1 = 0, q1 = 0; |
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double max_sigma = 0, max_val = 0; |
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for( i = 0; i < N; i++ ) |
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{ |
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double p_i, q2, mu2, sigma; |
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p_i = h[i]*scale; |
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mu1 *= q1; |
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q1 += p_i; |
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q2 = 1. - q1; |
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if( std::min(q1,q2) < FLT_EPSILON || std::max(q1,q2) > 1. - FLT_EPSILON ) |
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continue; |
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mu1 = (mu1 + i*p_i)/q1; |
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mu2 = (mu - q1*mu1)/q2; |
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sigma = q1*q2*(mu1 - mu2)*(mu1 - mu2); |
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if( sigma > max_sigma ) |
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{ |
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max_sigma = sigma; |
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max_val = i; |
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} |
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} |
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return max_val; |
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} |
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static void test_threshold( const Mat& _src, Mat& _dst, |
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double thresh, double maxval, int thresh_type ) |
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double thresh, double maxval, int thresh_type, int extra_type ) |
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{ |
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int i, j; |
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int depth = _src.depth(), cn = _src.channels(); |
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int width_n = _src.cols*cn, height = _src.rows; |
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int ithresh = cvFloor(thresh); |
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int imaxval, ithresh2; |
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if (extra_type == CV_THRESH_OTSU) |
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{ |
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thresh = compute_otsu_thresh(_src); |
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ithresh = cvFloor(thresh); |
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} |
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if( depth == CV_8U ) |
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{ |
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@ -157,7 +224,7 @@ static void test_threshold( const Mat& _src, Mat& _dst, |
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imaxval = cvRound(maxval); |
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} |
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assert( depth == CV_8U || depth == CV_16S || depth == CV_16U || depth == CV_32F || depth == CV_64F ); |
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CV_Assert( depth == CV_8U || depth == CV_16S || depth == CV_16U || depth == CV_32F || depth == CV_64F ); |
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switch( thresh_type ) |
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{ |
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@ -415,10 +482,11 @@ static void test_threshold( const Mat& _src, Mat& _dst, |
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void CV_ThreshTest::prepare_to_validation( int /*test_case_idx*/ ) |
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{ |
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test_threshold( test_mat[INPUT][0], test_mat[REF_OUTPUT][0], |
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thresh_val, max_val, thresh_type ); |
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thresh_val, max_val, thresh_type, extra_type ); |
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} |
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TEST(Imgproc_Threshold, accuracy) { CV_ThreshTest test; test.safe_run(); } |
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TEST(Imgproc_Threshold, accuracyOtsu) { CV_ThreshTest test(CV_THRESH_OTSU); test.safe_run(); } |
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BIGDATA_TEST(Imgproc_Threshold, huge) |
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{ |
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