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added smoke test on EM, fixed EM reading #1570 (thanks to mr.pppoe),

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This commit is contained in:
Maria Dimashova 2012-03-29 08:55:43 +00:00
parent ec793df30f
commit 8d9d964550
2 changed files with 91 additions and 21 deletions
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36
modules/ml/src/em.cpp
View File

@ -141,8 +141,6 @@ void CvEM::read( CvFileStorage* fs, CvFileNode* node )
CvFileNode* em_node = 0;
CvFileNode* tmp_node = 0;
CvSeq* seq = 0;
CvMat **tmp_covs = 0;
CvMat **tmp_cov_rotate_mats = 0;
read_params( fs, node );
@ -156,13 +154,10 @@ void CvEM::read( CvFileStorage* fs, CvFileNode* node )
CV_CALL( inv_eigen_values = (CvMat*)cvReadByName( fs, em_node, "inv_eigen_values" ));
// Size of all the following data
data_size = params.nclusters*2*sizeof(CvMat*);
CV_CALL( tmp_covs = (CvMat**)cvAlloc( data_size ));
memset( tmp_covs, 0, data_size );
tmp_cov_rotate_mats = tmp_covs + params.nclusters;
data_size = params.nclusters*sizeof(CvMat*);
CV_CALL( covs = (CvMat**)cvAlloc( data_size ));
memset( covs, 0, data_size );
CV_CALL( tmp_node = cvGetFileNodeByName( fs, em_node, "covs" ));
seq = tmp_node->data.seq;
if( !CV_NODE_IS_SEQ(tmp_node->tag) || seq->total != params.nclusters)
@ -170,24 +165,23 @@ void CvEM::read( CvFileStorage* fs, CvFileNode* node )
CV_CALL( cvStartReadSeq( seq, &reader, 0 ));
for( int i = 0; i < params.nclusters; i++ )
{
CV_CALL( tmp_covs[i] = (CvMat*)cvRead( fs, (CvFileNode*)reader.ptr ));
CV_CALL( covs[i] = (CvMat*)cvRead( fs, (CvFileNode*)reader.ptr ));
CV_NEXT_SEQ_ELEM( seq->elem_size, reader );
}
CV_CALL( cov_rotate_mats = (CvMat**)cvAlloc( data_size ));
memset( cov_rotate_mats, 0, data_size );
CV_CALL( tmp_node = cvGetFileNodeByName( fs, em_node, "cov_rotate_mats" ));
seq = tmp_node->data.seq;
if( !CV_NODE_IS_SEQ(tmp_node->tag) || seq->total != params.nclusters)
CV_ERROR( CV_StsParseError, "Missing or invalid sequence of rotated cov. matrices" );
CV_ERROR( CV_StsParseError, "Missing or invalid sequence of covariance matrices" );
CV_CALL( cvStartReadSeq( seq, &reader, 0 ));
for( int i = 0; i < params.nclusters; i++ )
{
CV_CALL( tmp_cov_rotate_mats[i] = (CvMat*)cvRead( fs, (CvFileNode*)reader.ptr ));
CV_CALL( cov_rotate_mats[i] = (CvMat*)cvRead( fs, (CvFileNode*)reader.ptr ));
CV_NEXT_SEQ_ELEM( seq->elem_size, reader );
}
covs = tmp_covs;
cov_rotate_mats = tmp_cov_rotate_mats;
ok = true;
__END__;
@ -862,10 +856,10 @@ void CvEM::kmeans( const CvVectors& train_data, int nclusters, CvMat* labels,
{
int i, nsamples = train_data.count, dims = train_data.dims;
cv::Ptr<CvMat> temp_mat = cvCreateMat(nsamples, dims, CV_32F);
for( i = 0; i < nsamples; i++ )
memcpy( temp_mat->data.ptr + temp_mat->step*i, train_data.data.fl[i], dims*sizeof(float));
cvKMeans2(temp_mat, nclusters, labels, termcrit, 10);
}
@ -1240,20 +1234,20 @@ CvEM::CvEM( const Mat& samples, const Mat& sample_idx, CvEMParams params )
{
means = weights = probs = inv_eigen_values = log_weight_div_det = 0;
covs = cov_rotate_mats = 0;
// just invoke the train() method
train(samples, sample_idx, params);
}
}
bool CvEM::train( const Mat& _samples, const Mat& _sample_idx,
CvEMParams _params, Mat* _labels )
{
CvMat samples = _samples, sidx = _sample_idx, labels, *plabels = 0;
if( _labels )
{
int nsamples = sidx.data.ptr ? sidx.rows : samples.rows;
if( !(_labels->data && _labels->type() == CV_32SC1 &&
(_labels->cols == 1 || _labels->rows == 1) &&
_labels->cols + _labels->rows - 1 == nsamples) )
@ -1267,7 +1261,7 @@ float
CvEM::predict( const Mat& _sample, Mat* _probs ) const
{
CvMat sample = _sample, probs, *pprobs = 0;
if( _probs )
{
int nclusters = params.nclusters;

76
modules/ml/test/test_emknearestkmeans.cpp
View File

@ -332,6 +332,82 @@ void CV_EMTest::run( int /*start_from*/ )
ts->set_failed_test_info( code );
}
class CV_EMTest_Smoke : public cvtest::BaseTest {
public:
CV_EMTest_Smoke() {}
protected:
virtual void run( int /*start_from*/ )
{
int code = cvtest::TS::OK;
CvEM em;
Mat samples = Mat(3,2,CV_32F);
samples.at<float>(0,0) = 1;
samples.at<float>(1,0) = 2;
samples.at<float>(2,0) = 3;
CvEMParams params;
params.nclusters = 2;
Mat labels;
em.train(samples, Mat(), params, &labels);
Mat firstResult(samples.rows, 1, CV_32FC1);
for( int i = 0; i < samples.rows; i++)
firstResult.at<float>(i) = em.predict( samples.row(i) );
// Write out
string filename = tempfile() + ".xml";
{
FileStorage fs = FileStorage(filename, FileStorage::WRITE);
try
{
em.write(fs.fs, "EM");
}
catch(...)
{
ts->printf( cvtest::TS::LOG, "Crash in write method.\n" );
ts->set_failed_test_info( cvtest::TS::FAIL_EXCEPTION );
}
}
em.clear();
// Read in
{
FileStorage fs = FileStorage(filename, FileStorage::READ);
FileNode fileNode = fs["EM"];
try
{
em.read(const_cast<CvFileStorage*>(fileNode.fs), const_cast<CvFileNode*>(fileNode.node));
}
catch(...)
{
ts->printf( cvtest::TS::LOG, "Crash in read method.\n" );
ts->set_failed_test_info( cvtest::TS::FAIL_EXCEPTION );
}
}
remove( filename.c_str() );
int errCaseCount = 0;
for( int i = 0; i < samples.rows; i++)
errCaseCount = std::abs(em.predict(samples.row(i)) - firstResult.at<float>(i)) < FLT_EPSILON ? 0 : 1;
if( errCaseCount > 0 )
{
ts->printf( cvtest::TS::LOG, "Different prediction results before writeing and after reading (errCaseCount=%d).\n", errCaseCount );
code = cvtest::TS::FAIL_BAD_ACCURACY;
}
ts->set_failed_test_info( code );
}
};
TEST(ML_KMeans, accuracy) { CV_KMeansTest test; test.safe_run(); }
TEST(ML_KNearest, accuracy) { CV_KNearestTest test; test.safe_run(); }
TEST(ML_EM, accuracy) { CV_EMTest test; test.safe_run(); }
TEST(ML_EM, smoke) { CV_EMTest_Smoke test; test.safe_run(); }