add part of opencv

2020-01-27 20:20:56 +08:00
parent 0c4ac1d8bb
commit a71fa47620
6518 changed files with 3122580 additions and 0 deletions
--- a/Lib/opencv/sources/modules/ml/test/test_save_load.cpp
+++ b/Lib/opencv/sources/modules/ml/test/test_save_load.cpp
@@ -0,0 +1,107 @@
+// This file is part of OpenCV project.
+// It is subject to the license terms in the LICENSE file found in the top-level directory
+// of this distribution and at http://opencv.org/license.html.
+
+#include "test_precomp.hpp"
+
+namespace opencv_test { namespace {
+
+
+void randomFillCategories(const string & filename, Mat & input)
+{
+    Mat catMap;
+    Mat catCount;
+    std::vector<uchar> varTypes;
+
+    FileStorage fs(filename, FileStorage::READ);
+    FileNode root = fs.getFirstTopLevelNode();
+    root["cat_map"] >> catMap;
+    root["cat_count"] >> catCount;
+    root["var_type"] >> varTypes;
+
+    int offset = 0;
+    int countOffset = 0;
+    uint var = 0, varCount = (uint)varTypes.size();
+    for (; var < varCount; ++var)
+    {
+        if (varTypes[var] == ml::VAR_CATEGORICAL)
+        {
+            int size = catCount.at<int>(0, countOffset);
+            for (int row = 0; row < input.rows; ++row)
+            {
+                int randomChosenIndex = offset + ((uint)cv::theRNG()) % size;
+                int value = catMap.at<int>(0, randomChosenIndex);
+                input.at<float>(row, var) = (float)value;
+            }
+            offset += size;
+            ++countOffset;
+        }
+    }
+}
+
+//==================================================================================================
+
+typedef tuple<string, string> ML_Legacy_Param;
+typedef testing::TestWithParam< ML_Legacy_Param > ML_Legacy_Params;
+
+TEST_P(ML_Legacy_Params, legacy_load)
+{
+    const string modelName = get<0>(GetParam());
+    const string dataName = get<1>(GetParam());
+    const string filename = findDataFile("legacy/" + modelName + "_" + dataName + ".xml");
+    const bool isTree = modelName == CV_BOOST || modelName == CV_DTREE || modelName == CV_RTREES;
+
+    Ptr<StatModel> model;
+    if (modelName == CV_BOOST)
+        model = Algorithm::load<Boost>(filename);
+    else if (modelName == CV_ANN)
+        model = Algorithm::load<ANN_MLP>(filename);
+    else if (modelName == CV_DTREE)
+        model = Algorithm::load<DTrees>(filename);
+    else if (modelName == CV_NBAYES)
+        model = Algorithm::load<NormalBayesClassifier>(filename);
+    else if (modelName == CV_SVM)
+        model = Algorithm::load<SVM>(filename);
+    else if (modelName == CV_RTREES)
+        model = Algorithm::load<RTrees>(filename);
+    else if (modelName == CV_SVMSGD)
+        model = Algorithm::load<SVMSGD>(filename);
+    ASSERT_TRUE(model);
+
+    Mat input = Mat(isTree ? 10 : 1, model->getVarCount(), CV_32F);
+    cv::theRNG().fill(input, RNG::UNIFORM, 0, 40);
+
+    if (isTree)
+        randomFillCategories(filename, input);
+
+    Mat output;
+    EXPECT_NO_THROW(model->predict(input, output, StatModel::RAW_OUTPUT | (isTree ? DTrees::PREDICT_SUM : 0)));
+    // just check if no internal assertions or errors thrown
+}
+
+ML_Legacy_Param param_list[] = {
+    ML_Legacy_Param(CV_ANN, "waveform"),
+    ML_Legacy_Param(CV_BOOST, "adult"),
+    ML_Legacy_Param(CV_BOOST, "1"),
+    ML_Legacy_Param(CV_BOOST, "2"),
+    ML_Legacy_Param(CV_BOOST, "3"),
+    ML_Legacy_Param(CV_DTREE, "abalone"),
+    ML_Legacy_Param(CV_DTREE, "mushroom"),
+    ML_Legacy_Param(CV_NBAYES, "waveform"),
+    ML_Legacy_Param(CV_SVM, "poletelecomm"),
+    ML_Legacy_Param(CV_SVM, "waveform"),
+    ML_Legacy_Param(CV_RTREES, "waveform"),
+    ML_Legacy_Param(CV_SVMSGD, "waveform"),
+};
+
+INSTANTIATE_TEST_CASE_P(/**/, ML_Legacy_Params, testing::ValuesIn(param_list));
+
+/*TEST(ML_SVM, throw_exception_when_save_untrained_model)
+{
+    Ptr<cv::ml::SVM> svm;
+    string filename = tempfile("svm.xml");
+    ASSERT_THROW(svm.save(filename.c_str()), Exception);
+    remove(filename.c_str());
+}*/
+
+}} // namespace