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ml: add checks of empty train data

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This commit is contained in:
Alexander Alekhin
2019-09-22 11:11:08 +00:00
parent eabbe38001
commit fef7fc343e
13 changed files with 33 additions and 11 deletions
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modules/ml/test/test_lr.cpp
+2 -5
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@@ -94,11 +94,7 @@ void CV_LRTest::run( int /*start_from*/ )
// initialize variables from the popular Iris Dataset
string dataFileName = ts->get_data_path() + "iris.data";
Ptr<TrainData> tdata = TrainData::loadFromCSV(dataFileName, 0);
if (tdata.empty()) {
ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA);
return;
}
ASSERT_FALSE(tdata.empty()) << "Could not find test data file : " << dataFileName;
// run LR classifier train classifier
Ptr<LogisticRegression> p = LogisticRegression::create();
@@ -156,6 +152,7 @@ void CV_LRTest_SaveLoad::run( int /*start_from*/ )
// initialize variables from the popular Iris Dataset
string dataFileName = ts->get_data_path() + "iris.data";
Ptr<TrainData> tdata = TrainData::loadFromCSV(dataFileName, 0);
ASSERT_FALSE(tdata.empty()) << "Could not find test data file : " << dataFileName;
Mat responses1, responses2;
Mat learnt_mat1, learnt_mat2;
modules/ml/test/test_mltests2.cpp
+7 -1
View File
@@ -105,6 +105,7 @@ int str_to_ann_activation_function(String& str)
void ann_check_data( Ptr<TrainData> _data )
{
CV_TRACE_FUNCTION();
CV_Assert(!_data.empty());
Mat values = _data->getSamples();
Mat var_idx = _data->getVarIdx();
int nvars = (int)var_idx.total();
@@ -118,6 +119,7 @@ void ann_check_data( Ptr<TrainData> _data )
Mat ann_get_new_responses( Ptr<TrainData> _data, map<int, int>& cls_map )
{
CV_TRACE_FUNCTION();
CV_Assert(!_data.empty());
Mat train_sidx = _data->getTrainSampleIdx();
int* train_sidx_ptr = train_sidx.ptr<int>();
Mat responses = _data->getResponses();
@@ -150,6 +152,8 @@ Mat ann_get_new_responses( Ptr<TrainData> _data, map<int, int>& cls_map )
float ann_calc_error( Ptr<StatModel> ann, Ptr<TrainData> _data, map<int, int>& cls_map, int type, vector<float> *resp_labels )
{
CV_TRACE_FUNCTION();
CV_Assert(!ann.empty());
CV_Assert(!_data.empty());
float err = 0;
Mat samples = _data->getSamples();
Mat responses = _data->getResponses();
@@ -264,13 +268,15 @@ TEST_P(ML_ANN_METHOD, Test)
String dataname = folder + "waveform" + '_' + methodName;
Ptr<TrainData> tdata2 = TrainData::loadFromCSV(original_path, 0);
ASSERT_FALSE(tdata2.empty()) << "Could not find test data file : " << original_path;
Mat samples = tdata2->getSamples()(Range(0, N), Range::all());
Mat responses(N, 3, CV_32FC1, Scalar(0));
for (int i = 0; i < N; i++)
responses.at<float>(i, static_cast<int>(tdata2->getResponses().at<float>(i, 0))) = 1;
Ptr<TrainData> tdata = TrainData::create(samples, ml::ROW_SAMPLE, responses);
ASSERT_FALSE(tdata.empty());
ASSERT_FALSE(tdata.empty()) << "Could not find test data file : " << original_path;
RNG& rng = theRNG();
rng.state = 0;
tdata->setTrainTestSplitRatio(0.8);