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Open Source Computer Vision Library
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54 lines
1.3 KiB
54 lines
1.3 KiB
// This file is part of OpenCV project. |
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// It is subject to the license terms in the LICENSE file found in the top-level directory |
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// of this distribution and at http://opencv.org/license.html. |
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#include "test_precomp.hpp" |
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namespace opencv_test { namespace { |
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TEST(ML_RTrees, getVotes) |
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{ |
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int n = 12; |
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int count, i; |
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int label_size = 3; |
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int predicted_class = 0; |
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int max_votes = -1; |
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int val; |
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// RTrees for classification |
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Ptr<ml::RTrees> rt = cv::ml::RTrees::create(); |
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//data |
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Mat data(n, 4, CV_32F); |
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randu(data, 0, 10); |
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//labels |
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Mat labels = (Mat_<int>(n,1) << 0,0,0,0, 1,1,1,1, 2,2,2,2); |
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rt->train(data, ml::ROW_SAMPLE, labels); |
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//run function |
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Mat test(1, 4, CV_32F); |
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Mat result; |
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randu(test, 0, 10); |
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rt->getVotes(test, result, 0); |
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//count vote amount and find highest vote |
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count = 0; |
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const int* result_row = result.ptr<int>(1); |
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for( i = 0; i < label_size; i++ ) |
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{ |
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val = result_row[i]; |
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//predicted_class = max_votes < val? i; |
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if( max_votes < val ) |
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{ |
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max_votes = val; |
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predicted_class = i; |
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} |
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count += val; |
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} |
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EXPECT_EQ(count, (int)rt->getRoots().size()); |
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EXPECT_EQ(result.at<float>(0, predicted_class), rt->predict(test)); |
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} |
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}} // namespace
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