[opencv] 238/251: features2d(test): update descriptor regression test
Nobuhiro Iwamatsu
iwamatsu at moszumanska.debian.org
Sun Aug 27 23:27:47 UTC 2017
This is an automated email from the git hooks/post-receive script.
iwamatsu pushed a commit to annotated tag 3.3.0
in repository opencv.
commit 411d36ff130c2e9ee0da718875a77b048328e888
Author: Alexander Alekhin <alexander.alekhin at intel.com>
Date: Thu Aug 3 13:19:51 2017 +0300
features2d(test): update descriptor regression test
---
.../test/test_descriptors_regression.cpp | 117 +++++++++++++--------
1 file changed, 74 insertions(+), 43 deletions(-)
diff --git a/modules/features2d/test/test_descriptors_regression.cpp b/modules/features2d/test/test_descriptors_regression.cpp
index d6fd30d..0862649 100644
--- a/modules/features2d/test/test_descriptors_regression.cpp
+++ b/modules/features2d/test/test_descriptors_regression.cpp
@@ -56,6 +56,7 @@ static void writeMatInBin( const Mat& mat, const string& filename )
FILE* f = fopen( filename.c_str(), "wb");
if( f )
{
+ CV_Assert(4 == sizeof(int));
int type = mat.type();
fwrite( (void*)&mat.rows, sizeof(int), 1, f );
fwrite( (void*)&mat.cols, sizeof(int), 1, f );
@@ -72,6 +73,7 @@ static Mat readMatFromBin( const string& filename )
FILE* f = fopen( filename.c_str(), "rb" );
if( f )
{
+ CV_Assert(4 == sizeof(int));
int rows, cols, type, dataSize;
size_t elements_read1 = fread( (void*)&rows, sizeof(int), 1, f );
size_t elements_read2 = fread( (void*)&cols, sizeof(int), 1, f );
@@ -123,24 +125,37 @@ protected:
CV_Assert( DataType<ValueType>::type == validDescriptors.type() );
int dimension = validDescriptors.cols;
- DistanceType curMaxDist = std::numeric_limits<DistanceType>::min();
+ DistanceType curMaxDist = 0;
+ size_t exact_count = 0, failed_count = 0;
for( int y = 0; y < validDescriptors.rows; y++ )
{
DistanceType dist = distance( validDescriptors.ptr<ValueType>(y), calcDescriptors.ptr<ValueType>(y), dimension );
+ if (dist == 0)
+ exact_count++;
if( dist > curMaxDist )
+ {
+ if (dist > maxDist)
+ failed_count++;
curMaxDist = dist;
+ }
+#if 0
+ if (dist > 0)
+ {
+ std::cout << "i=" << y << " fail_count=" << failed_count << " dist=" << dist << std::endl;
+ std::cout << "valid: " << validDescriptors.row(y) << std::endl;
+ std::cout << " calc: " << calcDescriptors.row(y) << std::endl;
+ }
+#endif
}
+ float exact_percents = (100 * (float)exact_count / validDescriptors.rows);
+ float failed_percents = (100 * (float)failed_count / validDescriptors.rows);
stringstream ss;
- ss << "Max distance between valid and computed descriptors " << curMaxDist;
- if( curMaxDist <= maxDist )
- ss << "." << endl;
- else
- {
- ss << ">" << maxDist << " - bad accuracy!"<< endl;
- ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
- }
- ts->printf(cvtest::TS::LOG, ss.str().c_str() );
+ ss << "Exact count (dist == 0): " << exact_count << " (" << (int)exact_percents << "%)" << std::endl
+ << "Failed count (dist > " << maxDist << "): " << failed_count << " (" << (int)failed_percents << "%)" << std::endl
+ << "Max distance between valid and computed descriptors (" << validDescriptors.size() << "): " << curMaxDist;
+ EXPECT_LE(failed_percents, 20.0f);
+ std::cout << ss.str() << std::endl;
}
void emptyDataTest()
@@ -202,22 +217,57 @@ protected:
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_TEST_DATA );
return;
}
+ const std::string keypoints_filename = string(ts->get_data_path()) +
+ (detector.empty()
+ ? (FEATURES2D_DIR + "/" + std::string("keypoints.xml.gz"))
+ : (DESCRIPTOR_DIR + "/" + name + "_keypoints.xml.gz"));
+ FileStorage fs(keypoints_filename, FileStorage::READ);
+
vector<KeyPoint> keypoints;
- FileStorage fs( string(ts->get_data_path()) + FEATURES2D_DIR + "/keypoints.xml.gz", FileStorage::READ );
- if(!detector.empty()) {
- detector->detect(img, keypoints);
- } else {
- read( fs.getFirstTopLevelNode(), keypoints );
+ EXPECT_TRUE(fs.isOpened()) << "Keypoint testdata is missing. Re-computing and re-writing keypoints testdata...";
+ if (!fs.isOpened())
+ {
+ fs.open(keypoints_filename, FileStorage::WRITE);
+ ASSERT_TRUE(fs.isOpened()) << "File for writting keypoints can not be opened.";
+ if (detector.empty())
+ {
+ Ptr<ORB> fd = ORB::create();
+ fd->detect(img, keypoints);
+ }
+ else
+ {
+ detector->detect(img, keypoints);
+ }
+ write(fs, "keypoints", keypoints);
+ fs.release();
}
- if(!keypoints.empty())
+ else
+ {
+ read(fs.getFirstTopLevelNode(), keypoints);
+ fs.release();
+ }
+
+ if(!detector.empty())
+ {
+ vector<KeyPoint> calcKeypoints;
+ detector->detect(img, calcKeypoints);
+ // TODO validate received keypoints
+ int diff = abs((int)calcKeypoints.size() - (int)keypoints.size());
+ if (diff > 0)
+ {
+ std::cout << "Keypoints difference: " << diff << std::endl;
+ EXPECT_LE(diff, (int)(keypoints.size() * 0.03f));
+ }
+ }
+ ASSERT_FALSE(keypoints.empty());
{
Mat calcDescriptors;
double t = (double)getTickCount();
- dextractor->compute( img, keypoints, calcDescriptors );
+ dextractor->compute(img, keypoints, calcDescriptors);
t = getTickCount() - t;
ts->printf(cvtest::TS::LOG, "\nAverage time of computing one descriptor = %g ms.\n", t/((double)getTickFrequency()*1000.)/calcDescriptors.rows);
- if( calcDescriptors.rows != (int)keypoints.size() )
+ if (calcDescriptors.rows != (int)keypoints.size())
{
ts->printf( cvtest::TS::LOG, "Count of computed descriptors and keypoints count must be equal.\n" );
ts->printf( cvtest::TS::LOG, "Count of keypoints is %d.\n", (int)keypoints.size() );
@@ -226,7 +276,7 @@ protected:
return;
}
- if( calcDescriptors.cols != dextractor->descriptorSize() || calcDescriptors.type() != dextractor->descriptorType() )
+ if (calcDescriptors.cols != dextractor->descriptorSize() || calcDescriptors.type() != dextractor->descriptorType())
{
ts->printf( cvtest::TS::LOG, "Incorrect descriptor size or descriptor type.\n" );
ts->printf( cvtest::TS::LOG, "Expected size is %d.\n", dextractor->descriptorSize() );
@@ -239,33 +289,14 @@ protected:
// TODO read and write descriptor extractor parameters and check them
Mat validDescriptors = readDescriptors();
- if( !validDescriptors.empty() )
- compareDescriptors( validDescriptors, calcDescriptors );
- else
+ EXPECT_FALSE(validDescriptors.empty()) << "Descriptors testdata is missing. Re-writing descriptors testdata...";
+ if (!validDescriptors.empty())
{
- if( !writeDescriptors( calcDescriptors ) )
- {
- ts->printf( cvtest::TS::LOG, "Descriptors can not be written.\n" );
- ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_TEST_DATA );
- return;
- }
- }
- }
- if(!fs.isOpened())
- {
- ts->printf( cvtest::TS::LOG, "Compute and write keypoints.\n" );
- fs.open( string(ts->get_data_path()) + FEATURES2D_DIR + "/keypoints.xml.gz", FileStorage::WRITE );
- if( fs.isOpened() )
- {
- Ptr<ORB> fd = ORB::create();
- fd->detect(img, keypoints);
- write( fs, "keypoints", keypoints );
+ compareDescriptors(validDescriptors, calcDescriptors);
}
else
{
- ts->printf(cvtest::TS::LOG, "File for writting keypoints can not be opened.\n");
- ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_TEST_DATA );
- return;
+ ASSERT_TRUE(writeDescriptors(calcDescriptors)) << "Descriptors can not be written.";
}
}
}
@@ -344,7 +375,7 @@ TEST( Features2d_DescriptorExtractor_KAZE, regression )
TEST( Features2d_DescriptorExtractor_AKAZE, regression )
{
CV_DescriptorExtractorTest<Hamming> test( "descriptor-akaze",
- (CV_DescriptorExtractorTest<Hamming>::DistanceType)12.f,
+ (CV_DescriptorExtractorTest<Hamming>::DistanceType)(486*0.05f),
AKAZE::create(),
Hamming(), AKAZE::create());
test.safe_run();
--
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