Merge remote-tracking branch 'upstream/master' into SIMDFastAreaResize-2

pull/220/head
Ilya Lavrenov 12 years ago
commit 743dce6a4b
  1. 4
      android/service/engine/AndroidManifest.xml
  2. 2
      android/service/engine/src/org/opencv/engine/manager/ManagerActivity.java
  3. 25
      doc/CMakeLists.txt
  4. 2
      modules/calib3d/perf/perf_pnp.cpp
  5. 9
      modules/core/include/opencv2/core/core.hpp
  6. 5
      modules/core/include/opencv2/core/operations.hpp
  7. 30
      modules/core/src/persistence.cpp
  8. 33
      modules/core/src/system.cpp
  9. 2
      modules/features2d/perf/perf_fast.cpp
  10. 4
      modules/features2d/src/matchers.cpp
  11. 2
      modules/highgui/perf/perf_output.cpp
  12. 16
      modules/imgproc/include/opencv2/imgproc/imgproc.hpp
  13. 13
      modules/imgproc/include/opencv2/imgproc/types_c.h
  14. 25
      modules/imgproc/perf/perf_cvt_color.cpp
  15. 2
      modules/imgproc/perf/perf_filter2d.cpp
  16. 983
      modules/imgproc/src/color.cpp
  17. 1516
      modules/imgproc/src/demosaicing.cpp
  18. 375
      modules/imgproc/test/test_color.cpp
  19. 4
      modules/nonfree/perf/perf_surf.cpp
  20. 8
      modules/objdetect/include/opencv2/objdetect/objdetect.hpp
  21. 2
      modules/objdetect/src/objdetect_init.cpp
  22. 57
      modules/objdetect/src/softcascade.cpp
  23. 24
      modules/stitching/perf/perf_stich.cpp
  24. 2
      modules/stitching/src/matchers.cpp
  25. 112
      modules/ts/misc/run.py
  26. 20
      modules/ts/src/ts_perf.cpp
  27. 2
      modules/video/perf/perf_tvl1optflow.cpp
  28. 2
      modules/video/test/test_backgroundsubtractor_gbh.cpp
  29. 39
      modules/video/test/test_tvl1optflow.cpp
  30. 18
      samples/android/tutorial-5-cameracontrol/src/org/opencv/samples/tutorial5/Sample5CameraControl.java
  31. 5
      samples/android/tutorial-5-cameracontrol/src/org/opencv/samples/tutorial5/SampleJavaCameraView.java

@ -1,8 +1,8 @@
<?xml version="1.0" encoding="utf-8"?>
<manifest xmlns:android="http://schemas.android.com/apk/res/android"
package="org.opencv.engine"
android:versionCode="23@ANDROID_PLATFORM_VERSION_CODE@"
android:versionName="2.3" >
android:versionCode="24@ANDROID_PLATFORM_VERSION_CODE@"
android:versionName="2.4" >
<uses-sdk android:minSdkVersion="@ANDROID_NATIVE_API_LEVEL@" />
<uses-feature android:name="android.hardware.touchscreen" android:required="false"/>

@ -358,6 +358,8 @@ public class ManagerActivity extends Activity
else
{
temp.put("Activity", "n");
if (!PublicName.equals("Built-in OpenCV library"))
Tags = "safe to remove";
}
}
else

@ -2,8 +2,6 @@
# CMake file for OpenCV docs
#
file(GLOB FILES_DOC *.htm *.txt *.jpg *.png *.pdf)
file(GLOB FILES_DOC_VS vidsurv/*.doc)
file(GLOB FILES_TEX *.tex *.sty *.bib)
file(GLOB FILES_TEX_PICS pics/*.png pics/*.jpg)
@ -11,6 +9,14 @@ if(BUILD_DOCS AND HAVE_SPHINX)
project(opencv_docs)
set(DOC_LIST "${OpenCV_SOURCE_DIR}/doc/opencv-logo.png" "${OpenCV_SOURCE_DIR}/doc/opencv-logo2.png"
"${OpenCV_SOURCE_DIR}/doc/opencv-logo-white.png" "${OpenCV_SOURCE_DIR}/doc/opencv.ico"
"${OpenCV_SOURCE_DIR}/doc/haartraining.htm" "${OpenCV_SOURCE_DIR}/doc/license.txt"
"${OpenCV_SOURCE_DIR}/doc/pattern.png" "${OpenCV_SOURCE_DIR}/doc/acircles_pattern.png")
set(OPTIONAL_DOC_LIST "")
set(OPENCV2_BASE_MODULES core imgproc highgui video calib3d features2d objdetect ml flann gpu photo stitching nonfree contrib legacy)
# build lists of modules to be documented
@ -81,6 +87,9 @@ if(BUILD_DOCS AND HAVE_SPHINX)
COMMENT "Generating the PDF Manuals"
)
LIST(APPEND OPTIONAL_DOC_LIST "${CMAKE_BINARY_DIR}/doc/opencv2refman.pdf" "${CMAKE_BINARY_DIR}/doc/opencv2manager.pdf"
"${CMAKE_BINARY_DIR}/doc/opencv_user.pdf" "${CMAKE_BINARY_DIR}/doc/opencv_tutorials.pdf" "${CMAKE_BINARY_DIR}/doc/opencv_cheatsheet.pdf")
if(ENABLE_SOLUTION_FOLDERS)
set_target_properties(docs PROPERTIES FOLDER "documentation")
endif()
@ -97,7 +106,13 @@ if(BUILD_DOCS AND HAVE_SPHINX)
if(ENABLE_SOLUTION_FOLDERS)
set_target_properties(html_docs PROPERTIES FOLDER "documentation")
endif()
endif()
install(FILES ${FILES_DOC} DESTINATION "${OPENCV_DOC_INSTALL_PATH}" COMPONENT main)
install(FILES ${FILES_DOC_VS} DESTINATION "${OPENCV_DOC_INSTALL_PATH}/vidsurv" COMPONENT main)
foreach(f ${DOC_LIST})
install(FILES "${f}" DESTINATION "${OPENCV_DOC_INSTALL_PATH}" COMPONENT main)
endforeach()
foreach(f ${OPTIONAL_DOC_LIST})
install(FILES "${f}" DESTINATION "${OPENCV_DOC_INSTALL_PATH}" OPTIONAL)
endforeach()
endif()

@ -16,7 +16,7 @@ typedef perf::TestBaseWithParam<int> PointsNum;
PERF_TEST_P(PointsNum_Algo, solvePnP,
testing::Combine(
testing::Values(4, 3*9, 7*13),
testing::Values(/*4,*/ 3*9, 7*13), //TODO: find why results on 4 points are too unstable
testing::Values((int)CV_ITERATIVE, (int)CV_EPNP)
)
)

@ -109,13 +109,6 @@ template<typename _Tp> class CV_EXPORTS MatIterator_;
template<typename _Tp> class CV_EXPORTS MatConstIterator_;
template<typename _Tp> class CV_EXPORTS MatCommaInitializer_;
#if !defined(ANDROID) || (defined(_GLIBCXX_USE_WCHAR_T) && _GLIBCXX_USE_WCHAR_T)
typedef std::basic_string<wchar_t> WString;
CV_EXPORTS string fromUtf16(const WString& str);
CV_EXPORTS WString toUtf16(const string& str);
#endif
CV_EXPORTS string format( const char* fmt, ... );
CV_EXPORTS string tempfile( const char* suffix CV_DEFAULT(0));
@ -1284,6 +1277,8 @@ public:
operator _Tp* ();
operator const _Tp*() const;
bool operator==(const Ptr<_Tp>& ptr) const;
_Tp* obj; //< the object pointer.
int* refcount; //< the associated reference counter
};

@ -2690,6 +2690,11 @@ template<typename _Tp> template<typename _Tp2> inline const Ptr<_Tp2> Ptr<_Tp>::
return p;
}
template<typename _Tp> inline bool Ptr<_Tp>::operator==(const Ptr<_Tp>& _ptr) const
{
return refcount == _ptr.refcount;
}
//// specializied implementations of Ptr::delete_obj() for classic OpenCV types
template<> CV_EXPORTS void Ptr<CvMat>::delete_obj();

@ -45,7 +45,6 @@
#include <ctype.h>
#include <deque>
#include <iterator>
#include <wchar.h>
#define USE_ZLIB 1
@ -156,35 +155,6 @@ cv::string cv::FileStorage::getDefaultObjectName(const string& _filename)
return cv::string(name);
}
namespace cv
{
#if !defined(ANDROID) || (defined(_GLIBCXX_USE_WCHAR_T) && _GLIBCXX_USE_WCHAR_T)
string fromUtf16(const WString& str)
{
cv::AutoBuffer<char> _buf(str.size()*4 + 1);
char* buf = _buf;
size_t sz = wcstombs(buf, str.c_str(), str.size());
if( sz == (size_t)-1 )
return string();
buf[sz] = '\0';
return string(buf);
}
WString toUtf16(const string& str)
{
cv::AutoBuffer<wchar_t> _buf(str.size() + 1);
wchar_t* buf = _buf;
size_t sz = mbstowcs(buf, str.c_str(), str.size());
if( sz == (size_t)-1 )
return WString();
buf[sz] = '\0';
return WString(buf);
}
#endif
}
typedef struct CvGenericHash
{
CV_SET_FIELDS()

@ -359,26 +359,24 @@ string format( const char* fmt, ... )
string tempfile( const char* suffix )
{
const char *temp_dir = getenv("OPENCV_TEMP_PATH");
string fname;
#if defined WIN32 || defined _WIN32
char temp_dir[MAX_PATH + 1] = { 0 };
char temp_dir2[MAX_PATH + 1] = { 0 };
char temp_file[MAX_PATH + 1] = { 0 };
::GetTempPathA(sizeof(temp_dir), temp_dir);
if (temp_dir == 0 || temp_dir[0] == 0)
{
::GetTempPathA(sizeof(temp_dir2), temp_dir2);
temp_dir = temp_dir2;
}
if(0 == ::GetTempFileNameA(temp_dir, "ocv", 0, temp_file))
return string();
DeleteFileA(temp_file);
string name = temp_file;
if(suffix)
{
if (suffix[0] != '.')
return name + "." + suffix;
else
return name + suffix;
}
else
return name;
fname = temp_file;
# else
# ifdef ANDROID
//char defaultTemplate[] = "/mnt/sdcard/__opencv_temp.XXXXXX";
@ -387,8 +385,6 @@ string tempfile( const char* suffix )
char defaultTemplate[] = "/tmp/__opencv_temp.XXXXXX";
# endif
string fname;
const char *temp_dir = getenv("OPENCV_TEMP_PATH");
if (temp_dir == 0 || temp_dir[0] == 0)
fname = defaultTemplate;
else
@ -401,19 +397,20 @@ string tempfile( const char* suffix )
}
const int fd = mkstemp((char*)fname.c_str());
if(fd == -1) return "";
if (fd == -1) return string();
close(fd);
remove(fname.c_str());
# endif
if (suffix)
{
if (suffix[0] != '.')
fname = fname + "." + suffix;
return fname + "." + suffix;
else
fname += suffix;
return fname + suffix;
}
return fname;
# endif
}
static CvErrorCallback customErrorCallback = 0;

@ -31,7 +31,7 @@ PERF_TEST_P(fast, detect, testing::Combine(
declare.in(frame);
Ptr<FeatureDetector> fd = Algorithm::create<FeatureDetector>("Feature2D.FAST");
ASSERT_FALSE( fd == 0 );
ASSERT_FALSE( fd.empty() );
fd->set("threshold", 20);
fd->set("nonmaxSuppression", true);
fd->set("type", type);

@ -531,7 +531,7 @@ void FlannBasedMatcher::train()
void FlannBasedMatcher::read( const FileNode& fn)
{
if (indexParams == 0)
if (indexParams.empty())
indexParams = new flann::IndexParams();
FileNode ip = fn["indexParams"];
@ -570,7 +570,7 @@ void FlannBasedMatcher::read( const FileNode& fn)
};
}
if (searchParams == 0)
if (searchParams.empty())
searchParams = new flann::SearchParams();
FileNode sp = fn["searchParams"];

@ -23,7 +23,7 @@ PERF_TEST_P(VideoWriter_Writing, WriteFrame,
string filename = getDataPath(get<0>(GetParam()));
bool isColor = get<1>(GetParam());
VideoWriter writer("perf_writer.avi", CV_FOURCC('X', 'V', 'I', 'D'), 25, cv::Size(640, 480), isColor);
VideoWriter writer(cv::tempfile(".avi"), CV_FOURCC('X', 'V', 'I', 'D'), 25, cv::Size(640, 480), isColor);
TEST_CYCLE() { Mat image = imread(filename, 1); writer << image; }

@ -1048,7 +1048,18 @@ enum
COLOR_RGBA2mRGBA = 125,
COLOR_mRGBA2RGBA = 126,
COLOR_COLORCVT_MAX = 127
// Edge-Aware Demosaicing
COLOR_BayerBG2BGR_EA = 127,
COLOR_BayerGB2BGR_EA = 128,
COLOR_BayerRG2BGR_EA = 129,
COLOR_BayerGR2BGR_EA = 130,
COLOR_BayerBG2RGB_EA = COLOR_BayerRG2BGR_EA,
COLOR_BayerGB2RGB_EA = COLOR_BayerGR2BGR_EA,
COLOR_BayerRG2RGB_EA = COLOR_BayerBG2BGR_EA,
COLOR_BayerGR2RGB_EA = COLOR_BayerGB2BGR_EA,
COLOR_COLORCVT_MAX = 131
};
@ -1252,6 +1263,9 @@ protected:
Point2f bottomRight;
};
// main function for all demosaicing procceses
CV_EXPORTS_W void demosaicing(InputArray _src, OutputArray _dst, int code, int dcn = 0);
}
#endif /* __cplusplus */

@ -310,7 +310,18 @@ enum
CV_RGBA2mRGBA = 125,
CV_mRGBA2RGBA = 126,
CV_COLORCVT_MAX = 127
// Edge-Aware Demosaicing
CV_BayerBG2BGR_EA = 127,
CV_BayerGB2BGR_EA = 128,
CV_BayerRG2BGR_EA = 129,
CV_BayerGR2BGR_EA = 130,
CV_BayerBG2RGB_EA = CV_BayerRG2BGR_EA,
CV_BayerGB2RGB_EA = CV_BayerGR2BGR_EA,
CV_BayerRG2RGB_EA = CV_BayerBG2BGR_EA,
CV_BayerGR2RGB_EA = CV_BayerGB2BGR_EA,
CV_COLORCVT_MAX = 131
};

@ -276,3 +276,28 @@ PERF_TEST_P(Size_CvtMode2, cvtColorYUV420,
SANITY_CHECK(dst, 1);
}
CV_ENUM(EdgeAwareBayerMode, COLOR_BayerBG2BGR_EA, COLOR_BayerGB2BGR_EA, COLOR_BayerRG2BGR_EA, COLOR_BayerGR2BGR_EA)
typedef std::tr1::tuple<Size, EdgeAwareBayerMode> EdgeAwareParams;
typedef perf::TestBaseWithParam<EdgeAwareParams> EdgeAwareDemosaicingTest;
PERF_TEST_P(EdgeAwareDemosaicingTest, demosaicingEA,
testing::Combine(
testing::Values(szVGA, sz720p, sz1080p, Size(130, 60)),
testing::ValuesIn(EdgeAwareBayerMode::all())
)
)
{
Size sz = get<0>(GetParam());
int mode = get<1>(GetParam());
Mat src(sz, CV_8UC1);
Mat dst(sz, CV_8UC3);
declare.in(src, WARMUP_RNG).out(dst);
TEST_CYCLE() cvtColor(src, dst, mode, 3);
SANITY_CHECK(dst, 1);
}

@ -70,7 +70,7 @@ PERF_TEST_P( Image_KernelSize, GaborFilter2d,
filter2D(sourceImage, filteredImage, CV_32F, gaborKernel);
}
SANITY_CHECK(filteredImage);
SANITY_CHECK(filteredImage, 1e-3);
}

File diff suppressed because it is too large Load Diff

File diff suppressed because it is too large Load Diff

@ -1685,12 +1685,14 @@ TEST(Imgproc_ColorBayer, accuracy) { CV_ColorBayerTest test; test.safe_run(); }
TEST(Imgproc_ColorBayer, regression)
{
cvtest::TS& ts = *cvtest::TS::ptr();
cvtest::TS* ts = cvtest::TS::ptr();
Mat given = imread(string(ts.get_data_path()) + "/cvtcolor/bayer_input.png", CV_LOAD_IMAGE_GRAYSCALE);
Mat gold = imread(string(ts.get_data_path()) + "/cvtcolor/bayer_gold.png", CV_LOAD_IMAGE_UNCHANGED);
Mat given = imread(string(ts->get_data_path()) + "/cvtcolor/bayer_input.png", CV_LOAD_IMAGE_GRAYSCALE);
Mat gold = imread(string(ts->get_data_path()) + "/cvtcolor/bayer_gold.png", CV_LOAD_IMAGE_UNCHANGED);
Mat result;
CV_Assert(given.data != NULL && gold.data != NULL);
cvtColor(given, result, CV_BayerBG2GRAY);
EXPECT_EQ(gold.type(), result.type());
@ -1705,10 +1707,10 @@ TEST(Imgproc_ColorBayer, regression)
TEST(Imgproc_ColorBayerVNG, regression)
{
cvtest::TS& ts = *cvtest::TS::ptr();
cvtest::TS* ts = cvtest::TS::ptr();
Mat given = imread(string(ts.get_data_path()) + "/cvtcolor/bayer_input.png", CV_LOAD_IMAGE_GRAYSCALE);
string goldfname = string(ts.get_data_path()) + "/cvtcolor/bayerVNG_gold.png";
Mat given = imread(string(ts->get_data_path()) + "/cvtcolor/bayer_input.png", CV_LOAD_IMAGE_GRAYSCALE);
string goldfname = string(ts->get_data_path()) + "/cvtcolor/bayerVNG_gold.png";
Mat gold = imread(goldfname, CV_LOAD_IMAGE_UNCHANGED);
Mat result;
@ -1731,73 +1733,52 @@ TEST(Imgproc_ColorBayerVNG, regression)
}
}
TEST(Imgproc_ColorBayerVNG_Strict, regression)
// creating Bayer pattern
template <typename T, int depth>
static void calculateBayerPattern(const Mat& src, Mat& bayer, const char* pattern)
{
cvtest::TS& ts = *cvtest::TS::ptr();
const char pattern[][3] = { "bg", "gb", "rg", "gr" };
const std::string image_name = "lena.png";
const std::string parent_path = string(ts.get_data_path()) + "/cvtcolor_strict/";
Mat src, dst, bayer, reference;
std::string full_path = parent_path + image_name;
src = imread(full_path, CV_LOAD_IMAGE_UNCHANGED);
Size ssize = src.size();
const int scn = 1;
bayer.create(ssize, CV_MAKETYPE(depth, scn));
if (src.data == NULL)
{
ts.set_failed_test_info(cvtest::TS::FAIL_MISSING_TEST_DATA);
ts.printf(cvtest::TS::SUMMARY, "No input image\n");
ts.set_gtest_status();
return;
}
int type = -1;
for (int i = 0; i < 4; ++i)
{
// creating Bayer pattern
bayer.create(ssize, CV_MAKETYPE(src.depth(), 1));
if (!strcmp(pattern[i], "bg"))
if (!strcmp(pattern, "bg"))
{
for (int y = 0; y < ssize.height; ++y)
for (int x = 0; x < ssize.width; ++x)
{
if ((x + y) % 2)
bayer.at<uchar>(y, x) = src.at<Vec3b>(y, x)[1];
bayer.at<T>(y, x) = static_cast<T>(src.at<Vec3b>(y, x)[1]);
else if (x % 2)
bayer.at<uchar>(y, x) = src.at<Vec3b>(y, x)[0];
bayer.at<T>(y, x) = static_cast<T>(src.at<Vec3b>(y, x)[0]);
else
bayer.at<uchar>(y, x) = src.at<Vec3b>(y, x)[2];
bayer.at<T>(y, x) = static_cast<T>(src.at<Vec3b>(y, x)[2]);
}
type = CV_BayerBG2BGR_VNG;
}
else if (!strcmp(pattern[i], "gb"))
else if (!strcmp(pattern, "gb"))
{
for (int y = 0; y < ssize.height; ++y)
for (int x = 0; x < ssize.width; ++x)
{
if ((x + y) % 2 == 0)
bayer.at<uchar>(y, x) = src.at<Vec3b>(y, x)[1];
bayer.at<T>(y, x) = static_cast<T>(src.at<Vec3b>(y, x)[1]);
else if (x % 2 == 0)
bayer.at<uchar>(y, x) = src.at<Vec3b>(y, x)[0];
bayer.at<T>(y, x) = static_cast<T>(src.at<Vec3b>(y, x)[0]);
else
bayer.at<uchar>(y, x) = src.at<Vec3b>(y, x)[2];
bayer.at<T>(y, x) = static_cast<T>(src.at<Vec3b>(y, x)[2]);
}
type = CV_BayerGB2BGR_VNG;
}
else if (!strcmp(pattern[i], "rg"))
else if (!strcmp(pattern, "rg"))
{
for (int y = 0; y < ssize.height; ++y)
for (int x = 0; x < ssize.width; ++x)
{
if ((x + y) % 2)
bayer.at<uchar>(y, x) = src.at<Vec3b>(y, x)[1];
bayer.at<T>(y, x) = static_cast<T>(src.at<Vec3b>(y, x)[1]);
else if (x % 2 == 0)
bayer.at<uchar>(y, x) = src.at<Vec3b>(y, x)[0];
bayer.at<T>(y, x) = static_cast<T>(src.at<Vec3b>(y, x)[0]);
else
bayer.at<uchar>(y, x) = src.at<Vec3b>(y, x)[2];
bayer.at<T>(y, x) = static_cast<T>(src.at<Vec3b>(y, x)[2]);
}
type = CV_BayerRG2BGR_VNG;
}
else
{
@ -1805,17 +1786,41 @@ TEST(Imgproc_ColorBayerVNG_Strict, regression)
for (int x = 0; x < ssize.width; ++x)
{
if ((x + y) % 2 == 0)
bayer.at<uchar>(y, x) = src.at<Vec3b>(y, x)[1];
bayer.at<T>(y, x) = static_cast<T>(src.at<Vec3b>(y, x)[1]);
else if (x % 2)
bayer.at<uchar>(y, x) = src.at<Vec3b>(y, x)[0];
bayer.at<T>(y, x) = static_cast<T>(src.at<Vec3b>(y, x)[0]);
else
bayer.at<uchar>(y, x) = src.at<Vec3b>(y, x)[2];
bayer.at<T>(y, x) = static_cast<T>(src.at<Vec3b>(y, x)[2]);
}
}
type = CV_BayerGR2BGR_VNG;
}
TEST(Imgproc_ColorBayerVNG_Strict, regression)
{
cvtest::TS* ts = cvtest::TS::ptr();
const char pattern[][3] = { "bg", "gb", "rg", "gr" };
const std::string image_name = "lena.png";
const std::string parent_path = string(ts->get_data_path()) + "/cvtcolor_strict/";
Mat src, dst, bayer, reference;
std::string full_path = parent_path + image_name;
src = imread(full_path, CV_LOAD_IMAGE_UNCHANGED);
if (src.data == NULL)
{
ts->set_failed_test_info(cvtest::TS::FAIL_MISSING_TEST_DATA);
ts->printf(cvtest::TS::SUMMARY, "No input image\n");
ts->set_gtest_status();
return;
}
for (int i = 0; i < 4; ++i)
{
calculateBayerPattern<uchar, CV_8U>(src, bayer, pattern[i]);
CV_Assert(!bayer.empty() && bayer.type() == CV_8UC1);
// calculating a dst image
cvtColor(bayer, dst, type);
cvtColor(bayer, dst, CV_BayerBG2BGR_VNG + i);
// reading a reference image
full_path = parent_path + pattern[i] + image_name;
@ -1829,16 +1834,17 @@ TEST(Imgproc_ColorBayerVNG_Strict, regression)
if (reference.depth() != dst.depth() || reference.channels() != dst.channels() ||
reference.size() != dst.size())
{
ts.set_failed_test_info(cvtest::TS::FAIL_MISMATCH);
ts.printf(cvtest::TS::SUMMARY, "\nReference channels: %d\n"
std::cout << reference(Rect(0, 0, 5, 5)) << std::endl << std::endl << std::endl;
ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH);
ts->printf(cvtest::TS::SUMMARY, "\nReference channels: %d\n"
"Actual channels: %d\n", reference.channels(), dst.channels());
ts.printf(cvtest::TS::SUMMARY, "\nReference depth: %d\n"
ts->printf(cvtest::TS::SUMMARY, "\nReference depth: %d\n"
"Actual depth: %d\n", reference.depth(), dst.depth());
ts.printf(cvtest::TS::SUMMARY, "\nReference rows: %d\n"
ts->printf(cvtest::TS::SUMMARY, "\nReference rows: %d\n"
"Actual rows: %d\n", reference.rows, dst.rows);
ts.printf(cvtest::TS::SUMMARY, "\nReference cols: %d\n"
ts->printf(cvtest::TS::SUMMARY, "\nReference cols: %d\n"
"Actual cols: %d\n", reference.cols, dst.cols);
ts.set_gtest_status();
ts->set_gtest_status();
return;
}
@ -1849,16 +1855,15 @@ TEST(Imgproc_ColorBayerVNG_Strict, regression)
int nonZero = countNonZero(diff.reshape(1) > 1);
if (nonZero != 0)
{
ts.set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
ts.printf(cvtest::TS::SUMMARY, "\nCount non zero in absdiff: %d\n", nonZero);
ts.set_gtest_status();
ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
ts->printf(cvtest::TS::SUMMARY, "\nCount non zero in absdiff: %d\n", nonZero);
ts->set_gtest_status();
return;
}
}
}
void GetTestMatrix(Mat& src)
static void getTestMatrix(Mat& src)
{
Size ssize(1000, 1000);
src.create(ssize, CV_32FC3);
@ -1883,7 +1888,7 @@ void GetTestMatrix(Mat& src)
}
}
void validate_result(const Mat& reference, const Mat& actual, const Mat& src = Mat(), int mode = -1)
static void validateResult(const Mat& reference, const Mat& actual, const Mat& src = Mat(), int mode = -1)
{
cvtest::TS* ts = cvtest::TS::ptr();
Size ssize = reference.size();
@ -1924,8 +1929,7 @@ void validate_result(const Mat& reference, const Mat& actual, const Mat& src = M
TEST(Imgproc_ColorLab_Full, accuracy)
{
Mat src;
GetTestMatrix(src);
Mat reference(src.size(), CV_32FC3);
getTestMatrix(src);
Size ssize = src.size();
CV_Assert(ssize.width == ssize.height);
@ -1942,12 +1946,245 @@ TEST(Imgproc_ColorLab_Full, accuracy)
cv::Mat recons;
cv::cvtColor(lab, recons, inverse_code);
validate_result(src, recons, src, forward_code);
validateResult(src, recons, src, forward_code);
}
static void test_Bayer2RGB_EdgeAware_8u(const Mat& src, Mat& dst, int code)
{
if (dst.empty())
dst.create(src.size(), CV_MAKETYPE(src.depth(), 3));
Size size = src.size();
size.width -= 1;
size.height -= 1;
int dcn = dst.channels();
CV_Assert(dcn == 3);
int step = src.step;
const uchar* S = src.ptr<uchar>(1) + 1;
uchar* D = dst.ptr<uchar>(1) + dcn;
int start_with_green = code == CV_BayerGB2BGR_EA || code == CV_BayerGR2BGR_EA ? 1 : 0;
int blue = code == CV_BayerGB2BGR_EA || code == CV_BayerBG2BGR_EA ? 1 : 0;
for (int y = 1; y < size.height; ++y)
{
S = src.ptr<uchar>(y) + 1;
D = dst.ptr<uchar>(y) + dcn;
if (start_with_green)
{
for (int x = 1; x < size.width; x += 2, S += 2, D += 2*dcn)
{
// red
D[0] = (S[-1] + S[1]) / 2;
D[1] = S[0];
D[2] = (S[-step] + S[step]) / 2;
if (!blue)
std::swap(D[0], D[2]);
}
S = src.ptr<uchar>(y) + 2;
D = dst.ptr<uchar>(y) + 2*dcn;
for (int x = 2; x < size.width; x += 2, S += 2, D += 2*dcn)
{
// red
D[0] = S[0];
D[1] = (std::abs(S[-1] - S[1]) > std::abs(S[step] - S[-step]) ? (S[step] + S[-step] + 1) : (S[-1] + S[1] + 1)) / 2;
D[2] = ((S[-step-1] + S[-step+1] + S[step-1] + S[step+1] + 2) / 4);
if (!blue)
std::swap(D[0], D[2]);
}
}
else
{
for (int x = 1; x < size.width; x += 2, S += 2, D += 2*dcn)
{
D[0] = S[0];
D[1] = (std::abs(S[-1] - S[1]) > std::abs(S[step] - S[-step]) ? (S[step] + S[-step] + 1) : (S[-1] + S[1] + 1)) / 2;
D[2] = ((S[-step-1] + S[-step+1] + S[step-1] + S[step+1] + 2) / 4);
if (!blue)
std::swap(D[0], D[2]);
}
S = src.ptr<uchar>(y) + 2;
D = dst.ptr<uchar>(y) + 2*dcn;
for (int x = 2; x < size.width; x += 2, S += 2, D += 2*dcn)
{
D[0] = (S[-1] + S[1] + 1) / 2;
D[1] = S[0];
D[2] = (S[-step] + S[step] + 1) / 2;
if (!blue)
std::swap(D[0], D[2]);
}
}
D = dst.ptr<uchar>(y + 1) - dcn;
for (int i = 0; i < dcn; ++i)
{
D[i] = D[-dcn + i];
D[-static_cast<int>(dst.step)+dcn+i] = D[-static_cast<int>(dst.step)+(dcn<<1)+i];
}
start_with_green ^= 1;
blue ^= 1;
}
++size.width;
uchar* firstRow = dst.data, *lastRow = dst.data + size.height * dst.step;
size.width *= dcn;
for (int x = 0; x < size.width; ++x)
{
firstRow[x] = firstRow[dst.step + x];
lastRow[x] = lastRow[-static_cast<int>(dst.step)+x];
}
}
template <typename T>
static void checkData(const Mat& actual, const Mat& reference, cvtest::TS* ts, const char* type,
bool& next, const char* bayer_type)
{
EXPECT_EQ(actual.size(), reference.size());
EXPECT_EQ(actual.channels(), reference.channels());
EXPECT_EQ(actual.depth(), reference.depth());
Size size = reference.size();
int dcn = reference.channels();
size.width *= dcn;
for (int y = 0; y < size.height && next; ++y)
{
const T* A = reinterpret_cast<const T*>(actual.data + actual.step * y);
const T* R = reinterpret_cast<const T*>(reference.data + reference.step * y);
for (int x = 0; x < size.width && next; ++x)
if (std::abs(A[x] - R[x]) > 1)
{
#define SUM cvtest::TS::SUMMARY
ts->printf(SUM, "\nReference value: %d\n", static_cast<int>(R[x]));
ts->printf(SUM, "Actual value: %d\n", static_cast<int>(A[x]));
ts->printf(SUM, "(y, x): (%d, %d)\n", y, x / reference.channels());
ts->printf(SUM, "Channel pos: %d\n", x % reference.channels());
ts->printf(SUM, "Pattern: %s\n", type);
ts->printf(SUM, "Bayer image type: %s", bayer_type);
#undef SUM
Mat diff;
absdiff(actual, reference, diff);
EXPECT_EQ(countNonZero(diff.reshape(1) > 1), 0);
ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
ts->set_gtest_status();
next = false;
}
}
}
TEST(ImgProc_BayerEdgeAwareDemosaicing, accuracy)
{
cvtest::TS* ts = cvtest::TS::ptr();
const std::string image_name = "lena.png";
const std::string parent_path = string(ts->get_data_path()) + "/cvtcolor_strict/";
Mat src, bayer;
std::string full_path = parent_path + image_name;
src = imread(full_path, CV_LOAD_IMAGE_UNCHANGED);
// src *= 255.0f;
// recons *= 255.0f;
if (src.data == NULL)
{
ts->set_failed_test_info(cvtest::TS::FAIL_MISSING_TEST_DATA);
ts->printf(cvtest::TS::SUMMARY, "No input image\n");
ts->set_gtest_status();
return;
}
/*
COLOR_BayerBG2BGR_EA = 127,
COLOR_BayerGB2BGR_EA = 128,
COLOR_BayerRG2BGR_EA = 129,
COLOR_BayerGR2BGR_EA = 130,
*/
bool next = true;
const char* types[] = { "bg", "gb", "rg", "gr" };
for (int i = 0; i < 4 && next; ++i)
{
calculateBayerPattern<uchar, CV_8U>(src, bayer, types[i]);
Mat reference;
test_Bayer2RGB_EdgeAware_8u(bayer, reference, CV_BayerBG2BGR_EA + i);
// imshow("Test", src);
// imshow("OpenCV", recons);
// waitKey();
for (int t = 0; t <= 1; ++t)
{
if (t == 1)
calculateBayerPattern<unsigned short int, CV_16U>(src, bayer, types[i]);
CV_Assert(!bayer.empty() && (bayer.type() == CV_8UC1 || bayer.type() == CV_16UC1));
Mat actual;
cv::demosaicing(bayer, actual, CV_BayerBG2BGR_EA + i);
if (t == 0)
checkData<unsigned char>(actual, reference, ts, types[i], next, "CV_8U");
else
{
Mat tmp;
reference.convertTo(tmp, CV_16U);
checkData<unsigned short int>(actual, tmp, ts, types[i], next, "CV_16U");
}
}
}
}
TEST(ImgProc_Bayer2RGBA, accuracy)
{
cvtest::TS* ts = cvtest::TS::ptr();
Mat raw = imread(string(ts->get_data_path()) + "/cvtcolor/bayer_input.png", CV_LOAD_IMAGE_GRAYSCALE);
Mat rgb, reference;
CV_Assert(raw.channels() == 1);
CV_Assert(raw.depth() == CV_8U);
CV_Assert(!raw.empty());
for (int code = CV_BayerBG2BGR; code <= CV_BayerGR2BGR; ++code)
{
cvtColor(raw, rgb, code);
cvtColor(rgb, reference, CV_BGR2BGRA);
Mat actual;
cvtColor(raw, actual, code, 4);
EXPECT_EQ(reference.size(), actual.size());
EXPECT_EQ(reference.depth(), actual.depth());
EXPECT_EQ(reference.channels(), actual.channels());
Size ssize = raw.size();
int cn = reference.channels();
ssize.width *= cn;
bool next = true;
for (int y = 0; y < ssize.height && next; ++y)
{
const uchar* rD = reference.ptr<uchar>(y);
const uchar* D = actual.ptr<uchar>(y);
for (int x = 0; x < ssize.width && next; ++x)
if (abs(rD[x] - D[x]) >= 1)
{
next = false;
ts->printf(cvtest::TS::SUMMARY, "Error in: (%d, %d)\n", x / cn, y);
ts->printf(cvtest::TS::SUMMARY, "Reference value: %d\n", rD[x]);
ts->printf(cvtest::TS::SUMMARY, "Actual value: %d\n", D[x]);
ts->printf(cvtest::TS::SUMMARY, "Src value: %d\n", raw.ptr<uchar>(y)[x]);
ts->printf(cvtest::TS::SUMMARY, "Size: (%d, %d)\n", reference.rows, reference.cols);
Mat diff;
absdiff(actual, reference, diff);
EXPECT_EQ(countNonZero(diff.reshape(1) > 1), 0);
ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
ts->set_gtest_status();
}
}
}
}

@ -27,7 +27,7 @@ PERF_TEST_P(surf, detect, testing::Values(SURF_IMAGES))
TEST_CYCLE() detector(frame, mask, points);
SANITY_CHECK_KEYPOINTS(points);
SANITY_CHECK_KEYPOINTS(points, 1e-3);
}
PERF_TEST_P(surf, extract, testing::Values(SURF_IMAGES))
@ -67,6 +67,6 @@ PERF_TEST_P(surf, full, testing::Values(SURF_IMAGES))
TEST_CYCLE() detector(frame, mask, points, descriptors, false);
SANITY_CHECK_KEYPOINTS(points);
SANITY_CHECK_KEYPOINTS(points, 1e-3);
SANITY_CHECK(descriptors, 1e-4);
}

@ -534,12 +534,14 @@ public:
int shrinkage;
};
enum { NO_REJECT = 1, DOLLAR = 2, /*PASCAL = 4,*/ DEFAULT = NO_REJECT};
// An empty cascade will be created.
// Param minScale is a minimum scale relative to the original size of the image on which cascade will be applyed.
// Param minScale is a maximum scale relative to the original size of the image on which cascade will be applyed.
// Param scales is a number of scales from minScale to maxScale.
// Param rejfactor is used for NMS.
CV_WRAP SCascade(const double minScale = 0.4, const double maxScale = 5., const int scales = 55, const int rejfactor = 1);
// Param rejCriteria is used for NMS.
CV_WRAP SCascade(const double minScale = 0.4, const double maxScale = 5., const int scales = 55, const int rejCriteria = 1);
CV_WRAP virtual ~SCascade();
@ -571,7 +573,7 @@ private:
double maxScale;
int scales;
int rejfactor;
int rejCriteria;
};
CV_EXPORTS bool initModule_objdetect(void);

@ -49,7 +49,7 @@ CV_INIT_ALGORITHM(SCascade, "CascadeDetector.SCascade",
obj.info()->addParam(obj, "minScale", obj.minScale);
obj.info()->addParam(obj, "maxScale", obj.maxScale);
obj.info()->addParam(obj, "scales", obj.scales);
obj.info()->addParam(obj, "rejfactor", obj.rejfactor));
obj.info()->addParam(obj, "rejCriteria", obj.rejCriteria));
bool initModule_objdetect(void)
{

@ -422,7 +422,7 @@ struct cv::SCascade::Fields
};
cv::SCascade::SCascade(const double mins, const double maxs, const int nsc, const int rej)
: fields(0), minScale(mins), maxScale(maxs), scales(nsc), rejfactor(rej) {}
: fields(0), minScale(mins), maxScale(maxs), scales(nsc), rejCriteria(rej) {}
cv::SCascade::~SCascade() { delete fields;}
@ -439,6 +439,57 @@ bool cv::SCascade::load(const FileNode& fn)
return fields->fill(fn);
}
namespace {
typedef cv::SCascade::Detection Detection;
typedef std::vector<Detection> dvector;
struct ConfidenceGt
{
bool operator()(const Detection& a, const Detection& b) const
{
return a.confidence > b.confidence;
}
};
static float overlap(const cv::Rect &a, const cv::Rect &b)
{
int w = std::min(a.x + a.width, b.x + b.width) - std::max(a.x, b.x);
int h = std::min(a.y + a.height, b.y + b.height) - std::max(a.y, b.y);
return (w < 0 || h < 0)? 0.f : (float)(w * h);
}
void DollarNMS(dvector& objects)
{
static const float DollarThreshold = 0.65f;
std::sort(objects.begin(), objects.end(), ConfidenceGt());
for (dvector::iterator dIt = objects.begin(); dIt != objects.end(); ++dIt)
{
const Detection &a = *dIt;
for (dvector::iterator next = dIt + 1; next != objects.end(); )
{
const Detection &b = *next;
const float ovl = overlap(a.bb, b.bb) / std::min(a.bb.area(), b.bb.area());
if (ovl > DollarThreshold)
next = objects.erase(next);
else
++next;
}
}
}
static void suppress(int type, std::vector<Detection>& objects)
{
CV_Assert(type == cv::SCascade::DOLLAR);
DollarNMS(objects);
}
}
void cv::SCascade::detectNoRoi(const cv::Mat& image, std::vector<Detection>& objects) const
{
Fields& fld = *fields;
@ -459,6 +510,8 @@ void cv::SCascade::detectNoRoi(const cv::Mat& image, std::vector<Detection>& obj
}
}
}
if (rejCriteria != NO_REJECT) suppress(rejCriteria, objects);
}
void cv::SCascade::detect(cv::InputArray _image, cv::InputArray _rois, std::vector<Detection>& objects) const
@ -506,6 +559,8 @@ void cv::SCascade::detect(cv::InputArray _image, cv::InputArray _rois, std::vect
}
}
}
if (rejCriteria != NO_REJECT) suppress(rejCriteria, objects);
}
void cv::SCascade::detect(InputArray _image, InputArray _rois, OutputArray _rects, OutputArray _confs) const

@ -19,7 +19,7 @@ typedef TestBaseWithParam<String> match;
typedef std::tr1::tuple<String, int> matchVector_t;
typedef TestBaseWithParam<matchVector_t> matchVector;
#ifdef HAVE_OPENCV_NONFREE
#ifdef HAVE_OPENCV_NONFREE_TODO_FIND_WHY_SURF_IS_NOT_ABLE_TO_STITCH_PANOS
#define TEST_DETECTORS testing::Values("surf", "orb")
#else
#define TEST_DETECTORS testing::Values<String>("orb")
@ -57,7 +57,11 @@ PERF_TEST_P(stitch, a123, TEST_DETECTORS)
stopTimer();
}
SANITY_CHECK(pano, 2);
Mat pano_small;
if (!pano.empty())
resize(pano, pano_small, Size(320, 240), 0, 0, INTER_AREA);
SANITY_CHECK(pano_small, 5);
}
PERF_TEST_P(stitch, b12, TEST_DETECTORS)
@ -91,7 +95,11 @@ PERF_TEST_P(stitch, b12, TEST_DETECTORS)
stopTimer();
}
SANITY_CHECK(pano, 2);
Mat pano_small;
if (!pano.empty())
resize(pano, pano_small, Size(320, 240), 0, 0, INTER_AREA);
SANITY_CHECK(pano_small, 5);
}
PERF_TEST_P( match, bestOf2Nearest, TEST_DETECTORS)
@ -137,7 +145,11 @@ PERF_TEST_P( match, bestOf2Nearest, TEST_DETECTORS)
matcher->collectGarbage();
}
SANITY_CHECK_MATCHES(pairwise_matches.matches);
std::vector<DMatch>& matches = pairwise_matches.matches;
if (GetParam() == "orb") matches.resize(0);
for(size_t q = 0; q < matches.size(); ++q)
if (matches[q].imgIdx < 0) { matches.resize(q); break;}
SANITY_CHECK_MATCHES(matches);
}
PERF_TEST_P( matchVector, bestOf2NearestVectorFeatures, testing::Combine(
@ -193,6 +205,8 @@ PERF_TEST_P( matchVector, bestOf2NearestVectorFeatures, testing::Combine(
}
std::vector<DMatch>& matches = pairwise_matches[0].matches;
std::vector<DMatch>& matches = pairwise_matches[detectorName == "surf" ? 1 : 0].matches;
for(size_t q = 0; q < matches.size(); ++q)
if (matches[q].imgIdx < 0) { matches.resize(q); break;}
SANITY_CHECK_MATCHES(matches);
}

@ -350,7 +350,7 @@ void SurfFeaturesFinder::find(const Mat &image, ImageFeatures &features)
Mat gray_image;
CV_Assert(image.type() == CV_8UC3);
cvtColor(image, gray_image, CV_BGR2GRAY);
if (surf == 0)
if (surf.empty())
{
detector_->detect(gray_image, features.keypoints);
extractor_->compute(gray_image, features.keypoints, features.descriptors);

@ -66,13 +66,13 @@ parse_patterns = (
{'name': "opencv_cxx_flags_debug", 'default': "", 'pattern': re.compile("^OPENCV_EXTRA_C_FLAGS_DEBUG:INTERNAL=(.*)$")},
{'name': "opencv_cxx_flags_release", 'default': "", 'pattern': re.compile("^OPENCV_EXTRA_C_FLAGS_RELEASE:INTERNAL=(.*)$")},
{'name': "cxx_flags_android", 'default': None, 'pattern': re.compile("^ANDROID_CXX_FLAGS:INTERNAL=(.*)$")},
{'name': "cxx_compiler_path", 'default': None, 'pattern': re.compile("^CMAKE_CXX_COMPILER:FILEPATH=(.*)$")},
{'name': "ndk_path", 'default': None, 'pattern': re.compile("^(?:ANDROID_NDK|ANDROID_STANDALONE_TOOLCHAIN)?:PATH=(.*)$")},
{'name': "android_abi", 'default': None, 'pattern': re.compile("^ANDROID_ABI:STRING=(.*)$")},
{'name': "android_executable", 'default': None, 'pattern': re.compile("^ANDROID_EXECUTABLE:FILEPATH=(.*android.*)$")},
{'name': "is_x64", 'default': "OFF", 'pattern': re.compile("^CUDA_64_BIT_DEVICE_CODE:BOOL=(ON)$")},#ugly(
{'name': "cmake_generator", 'default': None, 'pattern': re.compile("^CMAKE_GENERATOR:INTERNAL=(.+)$")},
{'name': "cxx_compiler", 'default': None, 'pattern': re.compile("^CMAKE_CXX_COMPILER:FILEPATH=(.+)$")},
{'name': "cxx_compiler_arg1", 'default': None, 'pattern': re.compile("^CMAKE_CXX_COMPILER_ARG1:[A-Z]+=(.+)$")},
{'name': "with_cuda", 'default': "OFF", 'pattern': re.compile("^WITH_CUDA:BOOL=(ON)$")},
{'name': "cuda_library", 'default': None, 'pattern': re.compile("^CUDA_CUDA_LIBRARY:FILEPATH=(.+)$")},
{'name': "core_dependencies", 'default': None, 'pattern': re.compile("^opencv_core_LIB_DEPENDS:STATIC=(.+)$")},
@ -199,20 +199,21 @@ def getRunningProcessExePathByName(name):
except:
return None
class RunInfo(object):
def setCallback(self, name, callback):
setattr(self, name, callback)
def __init__(self, path, options):
class TestSuite(object):
def __init__(self, options, path = None):
self.options = options
self.path = path
self.error = None
self.setUp = None
self.tearDown = None
self.nameprefix = "opencv_" + options.mode + "_"
self.adb = None
self.targetos = None
self.nameprefix = "opencv_" + self.options.mode + "_"
for p in parse_patterns:
setattr(self, p["name"], p["default"])
cachefile = open(os.path.join(path, "CMakeCache.txt"), "rt")
if self.path:
cachefile = open(os.path.join(self.path, "CMakeCache.txt"), "rt")
try:
for l in cachefile.readlines():
ll = l.strip()
@ -228,11 +229,21 @@ class RunInfo(object):
pass
cachefile.close()
# detect target platform
if self.android_executable or self.android_abi or self.ndk_path:
self.targetos = "android"
else:
self.targetos = hostos
self.initialize()
def initialize(self):
# fix empty tests dir
if not self.tests_dir:
self.tests_dir = self.path
self.tests_dir = os.path.normpath(self.tests_dir)
# add path to adb
# compute path to adb
if self.android_executable:
self.adb = os.path.join(os.path.dirname(os.path.dirname(self.android_executable)), ("platform-tools/adb","platform-tools/adb.exe")[hostos == 'nt'])
if not os.path.isfile(self.adb) or not os.access(self.adb, os.X_OK):
@ -240,20 +251,14 @@ class RunInfo(object):
else:
self.adb = None
# detect target platform
if self.android_executable or self.android_abi or self.ndk_path:
self.targetos = "android"
else:
self.targetos = hostos
if self.targetos == "android":
# fix adb tool location
if not self.adb:
self.adb = getRunningProcessExePathByName("adb")
if not self.adb:
self.adb = "adb"
if options.adb_serial:
self.adb = [self.adb, "-s", options.adb_serial]
if self.options.adb_serial:
self.adb = [self.adb, "-s", self.options.adb_serial]
else:
self.adb = [self.adb]
try:
@ -261,7 +266,7 @@ class RunInfo(object):
except OSError:
self.adb = []
# remember current device serial. Needed if another device is connected while this script runs
if self.adb and not options.adb_serial:
if self.adb and not self.options.adb_serial:
adb_res = self.runAdb("devices")
if not adb_res:
self.error = "Could not run adb command: %s (for %s)" % (self.error, self.path)
@ -276,11 +281,8 @@ class RunInfo(object):
self.error = "Too many (%s) devices are connected. Please specify single device using --serial option:\n\n" % (len(connected_devices)) + adb_res
self.adb = []
else:
options.adb_serial = connected_devices[0].split("\t")[0]
self.adb = self.adb + ["-s", options.adb_serial]
if self.adb:
print "adb command:", " ".join(self.adb)
self.options.adb_serial = connected_devices[0].split("\t")[0]
self.adb = self.adb + ["-s", self.options.adb_serial]
if self.adb:
# construct name for aapt tool
self.aapt = [os.path.join(os.path.dirname(self.adb[0]), ("aapt","aapt.exe")[hostos == 'nt'])]
@ -295,14 +297,17 @@ class RunInfo(object):
# fix test path
if "Visual Studio" in self.cmake_generator:
if options.configuration:
self.tests_dir = os.path.join(self.tests_dir, options.configuration)
if self.options.configuration:
self.tests_dir = os.path.join(self.tests_dir, self.options.configuration)
else:
self.tests_dir = os.path.join(self.tests_dir, self.build_type)
elif not self.is_x64 and self.cxx_compiler:
#one more attempt to detect x64 compiler
try:
output = Popen([self.cxx_compiler, "-v"], stdout=PIPE, stderr=PIPE).communicate()
compiler = [self.cxx_compiler]
if self.cxx_compiler_arg1:
compiler.append(self.cxx_compiler_arg1)
output = Popen(compiler + ["-v"], stdout=PIPE, stderr=PIPE).communicate()
if not output[0] and "x86_64" in output[1]:
self.is_x64 = True
except OSError:
@ -499,9 +504,11 @@ class RunInfo(object):
fd = os.fdopen(tmpfile[0], "w+b")
fd.write(SIMD_DETECTION_PROGRAM)
fd.close();
options = [self.cxx_compiler_path]
options = [self.cxx_compiler]
if self.cxx_compiler_arg1:
options.append(self.cxx_compiler_arg1)
cxx_flags = self.cxx_flags + " " + self.cxx_flags_release + " " + self.opencv_cxx_flags + " " + self.opencv_cxx_flags_release
if self.targetos == "android":
if self.targetos == "android" and self.cxx_flags_android:
cxx_flags = self.cxx_flags_android + " " + cxx_flags
prev_option = None
@ -634,18 +641,18 @@ class RunInfo(object):
logfile = userlog[0][userlog[0].find(":")+1:]
if self.targetos == "android" and exe.endswith(".apk"):
print "running java tests:", exe
print "Run java tests:", exe
try:
# get package info
output = Popen(self.aapt + ["dump", "xmltree", exe, "AndroidManifest.xml"], stdout=PIPE, stderr=_stderr).communicate()
if not output[0]:
print >> _stderr, "failed to get manifest info from", exe
print >> _stderr, "fail to dump manifest from", exe
return
tags = re.split(r"[ ]+E: ", output[0])
# get package name
manifest_tag = [t for t in tags if t.startswith("manifest ")]
if not manifest_tag:
print >> _stderr, "failed to get manifest info from", exe
print >> _stderr, "fail to read package name from", exe
return
pkg_name = re.search(r"^[ ]+A: package=\"(?P<pkg>.*?)\" \(Raw: \"(?P=pkg)\"\)\r?$", manifest_tag[0], flags=re.MULTILINE).group("pkg")
# get test instrumentation info
@ -663,7 +670,7 @@ class RunInfo(object):
pkg_target += self.options.junit_package
else:
pkg_target = self.options.junit_package
#uninstall already installed package
# uninstall previously installed package
print >> _stderr, "Uninstalling old", pkg_name, "from device..."
Popen(self.adb + ["uninstall", pkg_name], stdout=PIPE, stderr=_stderr).communicate()
print >> _stderr, "Installing new", exe, "to device...",
@ -675,10 +682,10 @@ class RunInfo(object):
print >> _stderr, "Failed to install", exe, "to device"
return
print >> _stderr, "Running jUnit tests for ", pkg_target
if self.setUp is not None:
if self.setUp:
self.setUp()
Popen(self.adb + ["shell", "am instrument -w -e package " + pkg_target + " " + pkg_name + "/" + pkg_runner], stdout=_stdout, stderr=_stderr).wait()
if self.tearDown is not None:
if self.tearDown:
self.tearDown()
except OSError:
pass
@ -710,10 +717,10 @@ class RunInfo(object):
else:
command = exename + " " + " ".join(args)
print >> _stderr, "Run command:", command
if self.setUp is not None:
if self.setUp:
self.setUp()
Popen(self.adb + ["shell", "export OPENCV_TEST_DATA_PATH=" + self.test_data_path + "&& cd " + andoidcwd + "&& ./" + command], stdout=_stdout, stderr=_stderr).wait()
if self.tearDown is not None:
Popen(self.adb + ["shell", "export OPENCV_TEST_DATA_PATH=" + self.options.test_data_path + "&& cd " + andoidcwd + "&& ./" + command], stdout=_stdout, stderr=_stderr).wait()
if self.tearDown:
self.tearDown()
# try get log
if not self.options.help:
@ -758,6 +765,7 @@ class RunInfo(object):
try:
shutil.rmtree(temp_path)
pass
except:
pass
@ -767,8 +775,12 @@ class RunInfo(object):
return None
def runTests(self, tests, _stdout, _stderr, workingDir, args = []):
if not self.isRunnable():
print >> _stderr, "Error:", self.error
if self.error:
return []
if self.adb and self.targetos == "android":
print "adb command:", " ".join(self.adb)
if not tests:
tests = self.tests
logs = []
@ -802,7 +814,6 @@ if __name__ == "__main__":
parser = OptionParser()
parser.add_option("-t", "--tests", dest="tests", help="comma-separated list of modules to test", metavar="SUITS", default="")
parser.add_option("-w", "--cwd", dest="cwd", help="working directory for tests", metavar="PATH", default=".")
parser.add_option("-a", "--accuracy", dest="accuracy", help="look for accuracy tests instead of performance tests", action="store_true", default=False)
parser.add_option("-l", "--longname", dest="useLongNames", action="store_true", help="generate log files with long names", default=False)
@ -812,6 +823,7 @@ if __name__ == "__main__":
parser.add_option("", "--package", dest="junit_package", help="Android: run jUnit tests for specified package", metavar="package", default="")
parser.add_option("", "--help-tests", dest="help", help="Show help for test executable", action="store_true", default=False)
parser.add_option("", "--check", dest="check", help="Shortcut for '--perf_min_samples=1 --perf_force_samples=1'", action="store_true", default=False)
parser.add_option("", "--list", dest="list", help="List available tests", action="store_true", default=False)
(options, args) = parser.parse_args(argv)
@ -823,7 +835,7 @@ if __name__ == "__main__":
run_args = getRunArgs(args[1:] or ['.'])
if len(run_args) == 0:
print >> sys.stderr, "Usage:\n", os.path.basename(sys.argv[0]), "<build_path>"
print >> sys.stderr, "Usage:", os.path.basename(sys.argv[0]), "[options] [build_path]"
exit(1)
tests = [s.strip() for s in options.tests.split(",") if s]
@ -833,17 +845,25 @@ if __name__ == "__main__":
test_args = [a for a in test_args if not a.startswith("--gtest_output=")]
if options.check:
test_args.extend(["--perf_min_samples=1", "--perf_force_samples=1"])
if not [a for a in test_args if a.startswith("--perf_min_samples=")] :
test_args.extend(["--perf_min_samples=1"])
if not [a for a in test_args if a.startswith("--perf_force_samples=")] :
test_args.extend(["--perf_force_samples=1"])
if not [a for a in test_args if a.startswith("--perf_verify_sanity")] :
test_args.extend(["--perf_verify_sanity"])
logs = []
test_list = []
for path in run_args:
info = RunInfo(path, options)
#print vars(info),"\n"
if not info.isRunnable():
print >> sys.stderr, "Error:", info.error
suite = TestSuite(options, path)
#print vars(suite),"\n"
if options.list:
test_list.extend(suite.tests)
else:
info.test_data_path = options.test_data_path
logs.extend(info.runTests(tests, sys.stdout, sys.stderr, options.cwd, test_args))
logs.extend(suite.runTests(tests, sys.stdout, sys.stderr, options.cwd, test_args))
if options.list:
print os.linesep.join(test_list) or "No tests found"
if logs:
print >> sys.stderr, "Collected: ", " ".join(logs)

@ -16,7 +16,8 @@ const std::string command_line_keys =
"{ perf_force_samples |100 |force set maximum number of samples for all tests}"
"{ perf_seed |809564 |seed for random numbers generator}"
"{ perf_threads |-1 |the number of worker threads, if parallel execution is enabled}"
"{ perf_write_sanity | |allow to create new records for sanity checks}"
"{ perf_write_sanity | |create new records for sanity checks}"
"{ perf_verify_sanity | |fail tests having no regression data for sanity checks}"
#ifdef ANDROID
"{ perf_time_limit |6.0 |default time limit for a single test (in seconds)}"
"{ perf_affinity_mask |0 |set affinity mask for the main thread}"
@ -41,6 +42,7 @@ static uint64 param_seed;
static double param_time_limit;
static int param_threads;
static bool param_write_sanity;
static bool param_verify_sanity;
#ifdef HAVE_CUDA
static bool param_run_cpu;
static int param_cuda_device;
@ -491,7 +493,7 @@ void Regression::verify(cv::FileNode node, cv::InputArray array, double eps, ERR
cv::minMaxLoc(diff.reshape(1), 0, &max);
FAIL() << " Absolute difference (=" << max << ") between argument \""
<< node.name() << "[" << idx << "]\" and expected value is bugger than " << eps;
<< node.name() << "[" << idx << "]\" and expected value is greater than " << eps;
}
}
else if (err == ERROR_RELATIVE)
@ -501,7 +503,7 @@ void Regression::verify(cv::FileNode node, cv::InputArray array, double eps, ERR
if (violations > 0)
{
FAIL() << " Relative difference (" << maxv << " of " << maxa << " allowed) between argument \""
<< node.name() << "[" << idx << "]\" and expected value is bugger than " << eps << " in " << violations << " points";
<< node.name() << "[" << idx << "]\" and expected value is greater than " << eps << " in " << violations << " points";
}
}
}
@ -545,7 +547,7 @@ void Regression::verify(cv::FileNode node, cv::InputArray array, double eps, ERR
cv::minMaxLoc(diff.reshape(1), 0, &max);
FAIL() << " Difference (=" << max << ") between argument1 \"" << node.name()
<< "\" and expected value is bugger than " << eps;
<< "\" and expected value is greater than " << eps;
}
}
else if (err == ERROR_RELATIVE)
@ -555,7 +557,7 @@ void Regression::verify(cv::FileNode node, cv::InputArray array, double eps, ERR
if (violations > 0)
{
FAIL() << " Relative difference (" << maxv << " of " << maxa << " allowed) between argument \"" << node.name()
<< "\" and expected value is bugger than " << eps << " in " << violations << " points";
<< "\" and expected value is greater than " << eps << " in " << violations << " points";
}
}
}
@ -595,10 +597,15 @@ Regression& Regression::operator() (const std::string& name, cv::InputArray arra
write() << nodename << "{";
}
// TODO: verify that name is alphanumeric, current error message is useless
write() << name << "{";
write(array);
write() << "}";
}
else if(param_verify_sanity)
{
ADD_FAILURE() << " No regression data for " << name << " argument";
}
}
else
{
@ -656,6 +663,7 @@ void TestBase::Init(int argc, const char* const argv[])
param_time_limit = std::max(0., args.get<double>("perf_time_limit"));
param_force_samples = args.get<unsigned int>("perf_force_samples");
param_write_sanity = args.has("perf_write_sanity");
param_verify_sanity = args.has("perf_verify_sanity");
param_threads = args.get<int>("perf_threads");
#ifdef ANDROID
param_affinity_mask = args.get<int>("perf_affinity_mask");
@ -970,7 +978,7 @@ void TestBase::validateMetrics()
if (m.gstddev > DBL_EPSILON)
{
EXPECT_GT(/*m.gmean * */1., /*m.gmean * */ 2 * sinh(m.gstddev * param_max_deviation))
<< " Test results are not reliable ((mean-sigma,mean+sigma) deviation interval is bigger than measured time interval).";
<< " Test results are not reliable ((mean-sigma,mean+sigma) deviation interval is greater than measured time interval).";
}
EXPECT_LE(m.outliers, std::max((unsigned int)cvCeil(m.samples * param_max_outliers / 100.), 1u))

@ -29,5 +29,5 @@ PERF_TEST_P(ImagePair, OpticalFlowDual_TVL1, testing::Values(impair("cv/optflow/
tvl1(frame1, frame2, flow);
}
SANITY_CHECK(flow);
SANITY_CHECK(flow, 0.5);
}

@ -41,7 +41,7 @@ void CV_BackgroundSubtractorTest::run(int)
Algorithm::create<BackgroundSubtractorGMG>("BackgroundSubtractor.GMG");
Mat fgmask;
if (fgbg == NULL)
if (fgbg.empty())
CV_Error(CV_StsError,"Failed to create Algorithm\n");
/**

@ -107,10 +107,41 @@ namespace
}
}
}
bool isFlowCorrect(Point2f u)
{
return !cvIsNaN(u.x) && !cvIsNaN(u.y) && (fabs(u.x) < 1e9) && (fabs(u.y) < 1e9);
}
double calcRMSE(const Mat_<Point2f>& flow1, const Mat_<Point2f>& flow2)
{
double sum = 0.0;
int counter = 0;
for (int i = 0; i < flow1.rows; ++i)
{
for (int j = 0; j < flow1.cols; ++j)
{
const Point2f u1 = flow1(i, j);
const Point2f u2 = flow2(i, j);
if (isFlowCorrect(u1) && isFlowCorrect(u2))
{
const Point2f diff = u1 - u2;
sum += diff.ddot(diff);
++counter;
}
}
}
return sqrt(sum / (1e-9 + counter));
}
}
TEST(Video_calcOpticalFlowDual_TVL1, Regression)
{
const double MAX_RMSE = 0.01;
const string frame1_path = TS::ptr()->get_data_path() + "optflow/RubberWhale1.png";
const string frame2_path = TS::ptr()->get_data_path() + "optflow/RubberWhale2.png";
const string gold_flow_path = TS::ptr()->get_data_path() + "optflow/tvl1_flow.flo";
@ -130,7 +161,11 @@ TEST(Video_calcOpticalFlowDual_TVL1, Regression)
#else
Mat_<Point2f> gold;
readOpticalFlowFromFile(gold, gold_flow_path);
double err = norm(gold, flow, NORM_INF);
EXPECT_EQ(0.0f, err);
ASSERT_EQ(gold.rows, flow.rows);
ASSERT_EQ(gold.cols, flow.cols);
const double err = calcRMSE(gold, flow);
EXPECT_LE(err, MAX_RMSE);
#endif
}

@ -1,5 +1,7 @@
package org.opencv.samples.tutorial5;
import java.text.SimpleDateFormat;
import java.util.Date;
import java.util.List;
import java.util.ListIterator;
@ -9,6 +11,7 @@ import org.opencv.android.OpenCVLoader;
import org.opencv.core.Mat;
import org.opencv.android.CameraBridgeViewBase.CvCameraViewListener;
import android.annotation.SuppressLint;
import android.app.Activity;
import android.os.Bundle;
import android.os.Environment;
@ -20,6 +23,7 @@ import android.view.SurfaceView;
import android.view.View;
import android.view.View.OnTouchListener;
import android.view.WindowManager;
import android.widget.Toast;
public class Sample5CameraControl extends Activity implements CvCameraViewListener, OnTouchListener {
private static final String TAG = "OCVSample::Activity";
@ -100,6 +104,11 @@ public class Sample5CameraControl extends Activity implements CvCameraViewListen
public boolean onCreateOptionsMenu(Menu menu) {
List<String> effects = mOpenCvCameraView.getEffectList();
if (effects == null) {
Log.e(TAG, "Color effects are not supported by device!");
return true;
}
mEffectMenuItems = new MenuItem[effects.size()];
int idx = 0;
@ -115,13 +124,20 @@ public class Sample5CameraControl extends Activity implements CvCameraViewListen
public boolean onOptionsItemSelected(MenuItem item) {
Log.i(TAG, "called onOptionsItemSelected; selected item: " + item);
mOpenCvCameraView.setEffect((String) item.getTitle());
Toast.makeText(this, mOpenCvCameraView.getEffect(), Toast.LENGTH_SHORT).show();
return true;
}
@SuppressLint("SimpleDateFormat")
@Override
public boolean onTouch(View v, MotionEvent event) {
Log.i(TAG,"onTouch event");
mOpenCvCameraView.takePicture(Environment.getExternalStorageDirectory().getPath() + "/sample_picture.jpg");
SimpleDateFormat sdf = new SimpleDateFormat("yyyy-MM-dd_HH-mm-ss");
String currentDateandTime = sdf.format(new Date());
String fileName = Environment.getExternalStorageDirectory().getPath() +
"/sample_picture_" + currentDateandTime + ".jpg";
mOpenCvCameraView.takePicture(fileName);
Toast.makeText(this, fileName + " saved", Toast.LENGTH_SHORT).show();
return false;
}
}

@ -25,6 +25,10 @@ public class SampleJavaCameraView extends JavaCameraView {
return mCamera.getParameters().getSupportedColorEffects();
}
public boolean isEffectSupported() {
return (mCamera.getParameters().getColorEffect() != null);
}
public String getEffect() {
return mCamera.getParameters().getColorEffect();
}
@ -48,6 +52,7 @@ public class SampleJavaCameraView extends JavaCameraView {
try {
FileOutputStream out = new FileOutputStream(mPictureFileName);
picture.compress(Bitmap.CompressFormat.JPEG, 90, out);
picture.recycle();
mCamera.startPreview();
} catch (Exception e) {
e.printStackTrace();

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