mirror of
https://github.com/opencv/opencv.git
synced 2025-06-08 01:53:19 +08:00
Merge remote-tracking branch 'upstream/3.4' into merge-3.4
This commit is contained in:
Alexander Alekhin
commit
170bf6d7af
@ -23,7 +23,7 @@ set(OPENCV_DOWNLOAD_LOG "${OpenCV_BINARY_DIR}/CMakeDownloadLog.txt")
|
||||
set(OPENCV_DOWNLOAD_WITH_CURL "${OpenCV_BINARY_DIR}/download_with_curl.sh")
|
||||
set(OPENCV_DOWNLOAD_WITH_WGET "${OpenCV_BINARY_DIR}/download_with_wget.sh")
|
||||
set(OPENCV_DOWNLOAD_TRIES_LIST 1 CACHE STRING "List of download tries") # a list
|
||||
set(OPENCV_DOWNLOAD_PARAMS INACTIVITY_TIMEOUT 60 TIMEOUT 600 CACHE STRING "Download parameters to be passed to file(DOWNLAOD ...)")
|
||||
set(OPENCV_DOWNLOAD_PARAMS INACTIVITY_TIMEOUT 60 TIMEOUT 600 CACHE STRING "Download parameters to be passed to file(DOWNLOAD ...)")
|
||||
mark_as_advanced(OPENCV_DOWNLOAD_TRIES_LIST OPENCV_DOWNLOAD_PARAMS)
|
||||
|
||||
# Init download cache directory and log file and helper scripts
|
||||
|
||||
@ -31,7 +31,7 @@ MULTILINE_CPP_IS_BRIEF = NO
|
||||
INHERIT_DOCS = YES
|
||||
SEPARATE_MEMBER_PAGES = NO
|
||||
TAB_SIZE = 4
|
||||
ALIASES += add_toggle{1}="@htmlonly[block] <div class='newInnerHTML'>\1</div><div> <script type="text/javascript"> addToggle(); </script>@endhtmlonly"
|
||||
ALIASES += add_toggle{1}="@htmlonly[block] <div class='newInnerHTML'>\1</div><div> <script type='text/javascript'> addToggle(); </script>@endhtmlonly"
|
||||
ALIASES += add_toggle_cpp="@htmlonly[block] <div class='newInnerHTML' title='cpp' style='display: none;'>C++</div><div class='toggleable_div label_cpp' style='display: none;'>@endhtmlonly"
|
||||
ALIASES += add_toggle_java="@htmlonly[block] <div class='newInnerHTML' title='java' style='display: none;'>Java</div><div class='toggleable_div label_java' style='display: none;'>@endhtmlonly"
|
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ALIASES += add_toggle_python="@htmlonly[block] <div class='newInnerHTML' title='python' style='display: none;'>Python</div><div class='toggleable_div label_python' style='display: none;'>@endhtmlonly"
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|
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@ -87,7 +87,7 @@ The tutorial consists of two main programs:
|
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|
||||
The application starts up extracting the ORB features and descriptors from the input image and
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then uses the mesh along with the [Möller–Trumbore intersection
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algorithm](http://http://en.wikipedia.org/wiki/M%C3%B6ller%E2%80%93Trumbore_intersection_algorithm/)
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algorithm](http://en.wikipedia.org/wiki/M%C3%B6ller%E2%80%93Trumbore_intersection_algorithm/)
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to compute the 3D coordinates of the found features. Finally, the 3D points and the descriptors
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are stored in different lists in a file with YAML format which each row is a different point. The
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technical background on how to store the files can be found in the @ref tutorial_file_input_output_with_xml_yml
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@ -1721,8 +1721,8 @@ concatenated together.
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@param imageSize Size of the image used only to initialize the camera intrinsic matrix.
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@param cameraMatrix Input/output 3x3 floating-point camera intrinsic matrix
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\f$\cameramatrix{A}\f$ . If @ref CALIB_USE_INTRINSIC_GUESS
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and/or @ref CALIB_FIX_ASPECT_RATIO are specified, some or all of fx, fy, cx, cy must be
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initialized before calling the function.
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and/or @ref CALIB_FIX_ASPECT_RATIO, @ref CALIB_FIX_PRINCIPAL_POINT or @ref CALIB_FIX_FOCAL_LENGTH
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are specified, some or all of fx, fy, cx, cy must be initialized before calling the function.
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@param distCoeffs Input/output vector of distortion coefficients
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\f$\distcoeffs\f$.
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@param rvecs Output vector of rotation vectors (@ref Rodrigues ) estimated for each pattern view
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@ -1748,7 +1748,7 @@ the number of pattern views. \f$R_i, T_i\f$ are concatenated 1x3 vectors.
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fx, fy, cx, cy that are optimized further. Otherwise, (cx, cy) is initially set to the image
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center ( imageSize is used), and focal distances are computed in a least-squares fashion.
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Note, that if intrinsic parameters are known, there is no need to use this function just to
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estimate extrinsic parameters. Use solvePnP instead.
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estimate extrinsic parameters. Use @ref solvePnP instead.
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- @ref CALIB_FIX_PRINCIPAL_POINT The principal point is not changed during the global
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optimization. It stays at the center or at a different location specified when
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@ref CALIB_USE_INTRINSIC_GUESS is set too.
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@ -1758,24 +1758,23 @@ ratio fx/fy stays the same as in the input cameraMatrix . When
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ignored, only their ratio is computed and used further.
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- @ref CALIB_ZERO_TANGENT_DIST Tangential distortion coefficients \f$(p_1, p_2)\f$ are set
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to zeros and stay zero.
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- @ref CALIB_FIX_FOCAL_LENGTH The focal length is not changed during the global optimization if
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@ref CALIB_USE_INTRINSIC_GUESS is set.
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- @ref CALIB_FIX_K1,..., @ref CALIB_FIX_K6 The corresponding radial distortion
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coefficient is not changed during the optimization. If @ref CALIB_USE_INTRINSIC_GUESS is
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set, the coefficient from the supplied distCoeffs matrix is used. Otherwise, it is set to 0.
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- @ref CALIB_RATIONAL_MODEL Coefficients k4, k5, and k6 are enabled. To provide the
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backward compatibility, this extra flag should be explicitly specified to make the
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calibration function use the rational model and return 8 coefficients. If the flag is not
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set, the function computes and returns only 5 distortion coefficients.
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calibration function use the rational model and return 8 coefficients or more.
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- @ref CALIB_THIN_PRISM_MODEL Coefficients s1, s2, s3 and s4 are enabled. To provide the
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backward compatibility, this extra flag should be explicitly specified to make the
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calibration function use the thin prism model and return 12 coefficients. If the flag is not
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set, the function computes and returns only 5 distortion coefficients.
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||||
calibration function use the thin prism model and return 12 coefficients or more.
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- @ref CALIB_FIX_S1_S2_S3_S4 The thin prism distortion coefficients are not changed during
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the optimization. If @ref CALIB_USE_INTRINSIC_GUESS is set, the coefficient from the
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supplied distCoeffs matrix is used. Otherwise, it is set to 0.
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- @ref CALIB_TILTED_MODEL Coefficients tauX and tauY are enabled. To provide the
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||||
backward compatibility, this extra flag should be explicitly specified to make the
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calibration function use the tilted sensor model and return 14 coefficients. If the flag is not
|
||||
set, the function computes and returns only 5 distortion coefficients.
|
||||
calibration function use the tilted sensor model and return 14 coefficients.
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||||
- @ref CALIB_FIX_TAUX_TAUY The coefficients of the tilted sensor model are not changed during
|
||||
the optimization. If @ref CALIB_USE_INTRINSIC_GUESS is set, the coefficient from the
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supplied distCoeffs matrix is used. Otherwise, it is set to 0.
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@ -1800,12 +1799,12 @@ The algorithm performs the following steps:
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zeros initially unless some of CALIB_FIX_K? are specified.
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- Estimate the initial camera pose as if the intrinsic parameters have been already known. This is
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done using solvePnP .
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done using @ref solvePnP .
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- Run the global Levenberg-Marquardt optimization algorithm to minimize the reprojection error,
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that is, the total sum of squared distances between the observed feature points imagePoints and
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the projected (using the current estimates for camera parameters and the poses) object points
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objectPoints. See projectPoints for details.
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objectPoints. See @ref projectPoints for details.
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|
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@note
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If you use a non-square (i.e. non-N-by-N) grid and @ref findChessboardCorners for calibration,
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@ -680,7 +680,7 @@ __CV_ENUM_FLAGS_BITWISE_XOR_EQ (EnumType, EnumType)
|
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# define CV_XADD(addr, delta) (int)_InterlockedExchangeAdd((long volatile*)addr, delta)
|
||||
#else
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||||
#ifdef OPENCV_FORCE_UNSAFE_XADD
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CV_INLINE CV_XADD(int* addr, int delta) { int tmp = *addr; *addr += delta; return tmp; }
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CV_INLINE int CV_XADD(int* addr, int delta) { int tmp = *addr; *addr += delta; return tmp; }
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#else
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||||
#error "OpenCV: can't define safe CV_XADD macro for current platform (unsupported). Define CV_XADD macro through custom port header (see OPENCV_INCLUDE_PORT_FILE)"
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#endif
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@ -1737,12 +1737,31 @@ static TlsStorage &getTlsStorage()
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#ifndef _WIN32 // pthread key destructor
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static void opencv_tls_destructor(void* pData)
|
||||
{
|
||||
if (!g_isTlsStorageInitialized)
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||||
return; // nothing to release, so prefer to avoid creation of new global structures
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getTlsStorage().releaseThread(pData);
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}
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#else // _WIN32
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||||
#ifdef CV_USE_FLS
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||||
static void WINAPI opencv_fls_destructor(void* pData)
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||||
{
|
||||
// Empiric detection of ExitProcess call
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DWORD code = STILL_ACTIVE/*259*/;
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BOOL res = GetExitCodeProcess(GetCurrentProcess(), &code);
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||||
if (res && code != STILL_ACTIVE)
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{
|
||||
// Looks like we are in ExitProcess() call
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||||
// This is FLS specific only because their callback is called before DllMain.
|
||||
// TLS doesn't have similar problem, DllMain() is called first which mark __termination properly.
|
||||
// Note: this workaround conflicts with ExitProcess() steps order described in documentation, however it works:
|
||||
// 3. ... called with DLL_PROCESS_DETACH
|
||||
// 7. The termination status of the process changes from STILL_ACTIVE to the exit value of the process.
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||||
// (ref: https://docs.microsoft.com/en-us/windows/win32/api/processthreadsapi/nf-processthreadsapi-exitprocess)
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||||
cv::__termination = true;
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||||
}
|
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|
||||
if (!g_isTlsStorageInitialized)
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||||
return; // nothing to release, so prefer to avoid creation of new global structures
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getTlsStorage().releaseThread(pData);
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}
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#endif // CV_USE_FLS
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|
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@ -176,16 +176,20 @@ ocv_add_perf_tests(${INF_ENGINE_TARGET}
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FILES Include ${perf_hdrs}
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)
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ocv_option(${the_module}_PERF_CAFFE "Add performance tests of Caffe framework" OFF)
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ocv_option(${the_module}_PERF_CLCAFFE "Add performance tests of clCaffe framework" OFF)
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ocv_option(OPENCV_DNN_PERF_CAFFE "Add performance tests of Caffe framework" OFF)
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ocv_option(OPENCV_DNN_PERF_CLCAFFE "Add performance tests of clCaffe framework" OFF)
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if(BUILD_PERF_TESTS)
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if (${the_module}_PERF_CAFFE)
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if (OPENCV_DNN_PERF_CAFFE
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OR ${the_module}_PERF_CAFFE # compatibility for deprecated option
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)
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find_package(Caffe QUIET)
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if (Caffe_FOUND)
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add_definitions(-DHAVE_CAFFE=1)
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ocv_target_link_libraries(opencv_perf_dnn caffe)
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endif()
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elseif(${the_module}_PERF_CLCAFFE)
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elseif(OPENCV_DNN_PERF_CLCAFFE
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OR ${the_module}_PERF_CAFFE # compatibility for deprecated option
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)
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find_package(Caffe QUIET)
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if (Caffe_FOUND)
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add_definitions(-DHAVE_CLCAFFE=1)
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@ -20,6 +20,9 @@
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#include <opencv2/core/utils/configuration.private.hpp>
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#include <opencv2/core/utils/logger.hpp>
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|
||||
#include "opencv2/core/utils/filesystem.hpp"
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#include "opencv2/core/utils/filesystem.private.hpp"
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namespace cv { namespace dnn {
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|
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#ifdef HAVE_DNN_NGRAPH
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@ -683,6 +686,23 @@ void InfEngineNgraphNet::initPlugin(InferenceEngine::CNNNetwork& net)
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ie.SetConfig({{
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InferenceEngine::PluginConfigParams::KEY_CPU_THREADS_NUM, format("%d", getNumThreads()),
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}}, device_name);
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#endif
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#if INF_ENGINE_VER_MAJOR_GE(INF_ENGINE_RELEASE_2021_2)
|
||||
if (device_name.find("GPU") == 0)
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{
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#if OPENCV_HAVE_FILESYSTEM_SUPPORT
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std::string cache_path = utils::fs::getCacheDirectory((std::string("dnn_ie_cache_") + device_name).c_str(), "OPENCV_DNN_IE_GPU_CACHE_DIR");
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#else
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std::string cache_path = utils::getConfigurationParameterString("OPENCV_DNN_IE_GPU_CACHE_DIR", "");
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#endif
|
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if (!cache_path.empty() && cache_path != "disabled")
|
||||
{
|
||||
CV_LOG_INFO(NULL, "OpenCV/nGraph: using GPU kernels cache: " << cache_path);
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ie.SetConfig({{
|
||||
InferenceEngine::PluginConfigParams::KEY_CACHE_DIR, cache_path,
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||||
}}, device_name);
|
||||
}
|
||||
}
|
||||
#endif
|
||||
}
|
||||
std::map<std::string, std::string> config;
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||||
|
||||
@ -133,7 +133,8 @@ public:
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||||
auto input = nodes[0].dynamicCast<InfEngineNgraphNode>()->node;
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||||
auto rois = nodes[1].dynamicCast<InfEngineNgraphNode>()->node;
|
||||
|
||||
std::vector<size_t> dims = rois->get_shape(), offsets(4, 0);
|
||||
auto rois_shape = rois->get_shape();
|
||||
std::vector<int64_t> dims(rois_shape.begin(), rois_shape.end()), offsets(4, 0);
|
||||
offsets[3] = 2;
|
||||
dims[3] = 7;
|
||||
|
||||
@ -147,7 +148,7 @@ public:
|
||||
lower_bounds, upper_bounds, strides, std::vector<int64_t>{}, std::vector<int64_t>{});
|
||||
|
||||
// Reshape rois from 4D to 2D
|
||||
std::vector<size_t> shapeData = {dims[2], 5};
|
||||
std::vector<int64_t> shapeData = {dims[2], 5};
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||||
auto shape = std::make_shared<ngraph::op::Constant>(ngraph::element::i64, ngraph::Shape{2}, shapeData.data());
|
||||
auto reshape = std::make_shared<ngraph::op::v1::Reshape>(slice, shape, true);
|
||||
|
||||
|
||||
@ -625,7 +625,8 @@ icvFetchContour( schar *ptr,
|
||||
|
||||
/*
|
||||
trace contour until certain point is met.
|
||||
returns 1 if met, 0 else.
|
||||
returns 1 if met and this is the last contour
|
||||
encountered by a raster scan reaching the point, 0 else.
|
||||
*/
|
||||
static int
|
||||
icvTraceContour( schar *ptr, int step, schar *stop_ptr, int is_hole )
|
||||
@ -668,14 +669,39 @@ icvTraceContour( schar *ptr, int step, schar *stop_ptr, int is_hole )
|
||||
break;
|
||||
}
|
||||
|
||||
if( i3 == stop_ptr || (i4 == i0 && i3 == i1) )
|
||||
if (i3 == stop_ptr) {
|
||||
if (!(*i3 & 0x80)) {
|
||||
/* it's the only contour */
|
||||
return 1;
|
||||
}
|
||||
|
||||
/* check if this is the last contour */
|
||||
/* encountered during a raster scan */
|
||||
schar *i5;
|
||||
int t = s;
|
||||
while (true)
|
||||
{
|
||||
t = (t - 1) & 7;
|
||||
i5 = i3 + deltas[t];
|
||||
if (*i5 != 0)
|
||||
break;
|
||||
if (t == 0)
|
||||
return 1;
|
||||
}
|
||||
}
|
||||
|
||||
if( (i4 == i0 && i3 == i1) )
|
||||
break;
|
||||
|
||||
i3 = i4;
|
||||
s = (s + 4) & 7;
|
||||
} /* end of border following loop */
|
||||
}
|
||||
else {
|
||||
return i3 == stop_ptr;
|
||||
}
|
||||
|
||||
return 0;
|
||||
}
|
||||
|
||||
|
||||
|
||||
@ -1101,6 +1101,7 @@ static bool ipp_sqrDistance(const Mat& src, const Mat& tpl, Mat& dst)
|
||||
buffer.allocate( bufSize );
|
||||
|
||||
status = CV_INSTRUMENT_FUN_IPP(ippiSqrDistanceNorm, src.ptr(), (int)src.step, srcRoiSize, tpl.ptr(), (int)tpl.step, tplRoiSize, dst.ptr<Ipp32f>(), (int)dst.step, funCfg, buffer);
|
||||
dst = cv::max(dst, 0); // handle edge case from rounding in variance computation which can result in negative values
|
||||
return status >= 0;
|
||||
}
|
||||
|
||||
|
||||
@ -485,6 +485,55 @@ TEST(Imgproc_FindContours, border)
|
||||
ASSERT_EQ(0, cvtest::norm(img, img_draw_contours, NORM_INF));
|
||||
}
|
||||
|
||||
TEST(Imgproc_FindContours, regression_4363_shared_nbd)
|
||||
{
|
||||
// Create specific test image
|
||||
Mat1b img(12, 69, (const uchar&)0);
|
||||
|
||||
img(1, 1) = 1;
|
||||
|
||||
// Vertical rectangle with hole sharing the same NBD
|
||||
for (int r = 1; r <= 10; ++r) {
|
||||
for (int c = 3; c <= 5; ++c) {
|
||||
img(r, c) = 1;
|
||||
}
|
||||
}
|
||||
img(9, 4) = 0;
|
||||
|
||||
// 124 small CCs
|
||||
for (int r = 1; r <= 7; r += 2) {
|
||||
for (int c = 7; c <= 67; c += 2) {
|
||||
img(r, c) = 1;
|
||||
}
|
||||
}
|
||||
|
||||
// Last CC
|
||||
img(9, 7) = 1;
|
||||
|
||||
vector< vector<Point> > contours;
|
||||
vector<Vec4i> hierarchy;
|
||||
findContours(img, contours, hierarchy, RETR_TREE, CHAIN_APPROX_NONE);
|
||||
|
||||
bool found = false;
|
||||
size_t index = 0;
|
||||
for (vector< vector<Point> >::const_iterator i = contours.begin(); i != contours.end(); ++i)
|
||||
{
|
||||
const vector<Point>& c = *i;
|
||||
if (!c.empty() && c[0] == Point(7, 9))
|
||||
{
|
||||
found = true;
|
||||
index = (size_t)(i - contours.begin());
|
||||
break;
|
||||
}
|
||||
}
|
||||
EXPECT_TRUE(found) << "Desired result: point (7,9) is a contour - Actual result: point (7,9) is not a contour";
|
||||
|
||||
if (found)
|
||||
{
|
||||
EXPECT_LT(hierarchy[index][3], 0) << "Desired result: (7,9) has no parent - Actual result: parent of (7,9) is another contour. index = " << index;
|
||||
}
|
||||
}
|
||||
|
||||
TEST(Imgproc_PointPolygonTest, regression_10222)
|
||||
{
|
||||
vector<Point> contour;
|
||||
|
||||
@ -334,4 +334,95 @@ void CV_TemplMatchTest::prepare_to_validation( int /*test_case_idx*/ )
|
||||
|
||||
TEST(Imgproc_MatchTemplate, accuracy) { CV_TemplMatchTest test; test.safe_run(); }
|
||||
|
||||
}} // namespace
|
||||
}
|
||||
|
||||
TEST(Imgproc_MatchTemplate, bug_9597) {
|
||||
const uint8_t img[] = {
|
||||
245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245,
|
||||
245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245,
|
||||
245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245,
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|
||||
245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 246, 246, 245,
|
||||
245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 246, 246, 245,
|
||||
245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 246, 246, 245,
|
||||
245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 246, 246, 245,
|
||||
245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 247, 247, 247, 247, 245,
|
||||
245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245,
|
||||
245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245,
|
||||
245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 247, 247, 245, 245, 245,
|
||||
245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245,
|
||||
245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245,
|
||||
245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245,
|
||||
245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245};
|
||||
const uint8_t tmpl[] = {
|
||||
245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245,
|
||||
245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245,
|
||||
245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245,
|
||||
245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245,
|
||||
245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245,
|
||||
245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245,
|
||||
245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245,
|
||||
245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245,
|
||||
245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245,
|
||||
245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245,
|
||||
245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245,
|
||||
245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245,
|
||||
245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245,
|
||||
245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245,
|
||||
245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245,
|
||||
245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245,
|
||||
245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245, 245 };
|
||||
cv::Mat cvimg(cv::Size(61, 82), CV_8UC1, (void*)img, cv::Mat::AUTO_STEP);
|
||||
cv::Mat cvtmpl(cv::Size(17, 17), CV_8UC1, (void*)tmpl, cv::Mat::AUTO_STEP);
|
||||
cv::Mat result;
|
||||
cv::matchTemplate(cvimg, cvtmpl, result, CV_TM_SQDIFF);
|
||||
double minValue;
|
||||
cv::minMaxLoc(result, &minValue, NULL, NULL, NULL);
|
||||
ASSERT_GE(minValue, 0);
|
||||
}
|
||||
} // namespace
|
||||
|
||||
@ -285,9 +285,9 @@ void Decolor::grad_system(const Mat &im, vector < vector < double > > &polyGrad,
|
||||
add_vector(comb,idx,r,g,b);
|
||||
for(int i = 0;i<h;i++)
|
||||
for(int j=0;j<w;j++)
|
||||
curIm.at<float>(i,j)=
|
||||
curIm.at<float>(i,j)=static_cast<float>(
|
||||
pow(rgb_channel[2].at<float>(i,j),r)*pow(rgb_channel[1].at<float>(i,j),g)*
|
||||
pow(rgb_channel[0].at<float>(i,j),b);
|
||||
pow(rgb_channel[0].at<float>(i,j),b));
|
||||
vector <double> curGrad;
|
||||
gradvector(curIm,curGrad);
|
||||
add_to_vector_poly(polyGrad,curGrad,idx1);
|
||||
|
||||
@ -496,7 +496,7 @@ void BestOf2NearestRangeMatcher::operator ()(const std::vector<ImageFeatures> &f
|
||||
|
||||
std::vector<std::pair<int,int> > near_pairs;
|
||||
for (int i = 0; i < num_images - 1; ++i)
|
||||
for (int j = i + 1; j < std::min(num_images, i + range_width_); ++j)
|
||||
for (int j = i + 1; j < std::min(num_images, i + 1 + range_width_); ++j)
|
||||
if (features[i].keypoints.size() > 0 && features[j].keypoints.size() > 0 && mask_(i, j))
|
||||
near_pairs.push_back(std::make_pair(i, j));
|
||||
|
||||
|
||||
@ -323,17 +323,34 @@ double cv::computeECC(InputArray templateImage, InputArray inputImage, InputArra
|
||||
Scalar meanTemplate, sdTemplate;
|
||||
|
||||
int active_pixels = inputMask.empty() ? templateImage.size().area() : countNonZero(inputMask);
|
||||
|
||||
int type = templateImage.type();
|
||||
meanStdDev(templateImage, meanTemplate, sdTemplate, inputMask);
|
||||
Mat templateImage_zeromean = Mat::zeros(templateImage.size(), templateImage.type());
|
||||
subtract(templateImage, meanTemplate, templateImage_zeromean, inputMask);
|
||||
Mat templateMat = templateImage.getMat();
|
||||
Mat inputMat = inputImage.getMat();
|
||||
|
||||
/*
|
||||
* For unsigned ints, when the mean is computed and subtracted, any values less than the mean
|
||||
* will be set to 0 (since there are no negatives values). This impacts the norm and dot product, which
|
||||
* ultimately results in an incorrect ECC. To circumvent this problem, if unsigned ints are provided,
|
||||
* we convert them to a signed ints with larger resolution for the subtraction step.
|
||||
*/
|
||||
if(type == CV_8U || type == CV_16U) {
|
||||
int newType = type == CV_8U ? CV_16S : CV_32S;
|
||||
Mat templateMatConverted, inputMatConverted;
|
||||
templateMat.convertTo(templateMatConverted, newType);
|
||||
cv::swap(templateMat, templateMatConverted);
|
||||
inputMat.convertTo(inputMatConverted, newType);
|
||||
cv::swap(inputMat, inputMatConverted);
|
||||
}
|
||||
subtract(templateMat, meanTemplate, templateImage_zeromean, inputMask);
|
||||
double templateImagenorm = std::sqrt(active_pixels*sdTemplate.val[0]*sdTemplate.val[0]);
|
||||
|
||||
Scalar meanInput, sdInput;
|
||||
|
||||
Mat inputImage_zeromean = Mat::zeros(inputImage.size(), inputImage.type());
|
||||
meanStdDev(inputImage, meanInput, sdInput, inputMask);
|
||||
subtract(inputImage, meanInput, inputImage_zeromean, inputMask);
|
||||
subtract(inputMat, meanInput, inputImage_zeromean, inputMask);
|
||||
double inputImagenorm = std::sqrt(active_pixels*sdInput.val[0]*sdInput.val[0]);
|
||||
|
||||
return templateImage_zeromean.dot(inputImage_zeromean)/(templateImagenorm*inputImagenorm);
|
||||
|
||||
@ -501,6 +501,18 @@ TEST(Video_ECC_Test_Compute, accuracy)
|
||||
EXPECT_NEAR(ecc, -0.5f, 1e-5f);
|
||||
}
|
||||
|
||||
TEST(Video_ECC_Test_Compute, bug_14657)
|
||||
{
|
||||
/*
|
||||
* Simple test case - a 2 x 2 matrix with 10, 10, 10, 6. When the mean (36 / 4 = 9) is subtracted,
|
||||
* it results in 1, 1, 1, 0 for the unsigned int case - compare to 1, 1, 1, -3 in the signed case.
|
||||
* For this reason, when the same matrix was provided as the input and the template, we didn't get 1 as expected.
|
||||
*/
|
||||
Mat img = (Mat_<uint8_t>(2, 2) << 10, 10, 10, 6);
|
||||
EXPECT_NEAR(computeECC(img, img), 1.0f, 1e-5f);
|
||||
}
|
||||
|
||||
|
||||
TEST(Video_ECC_Translation, accuracy) { CV_ECC_Test_Translation test; test.safe_run();}
|
||||
TEST(Video_ECC_Euclidean, accuracy) { CV_ECC_Test_Euclidean test; test.safe_run(); }
|
||||
TEST(Video_ECC_Affine, accuracy) { CV_ECC_Test_Affine test; test.safe_run(); }
|
||||
|
||||
@ -123,14 +123,14 @@ static void findSquares( const Mat& image, vector<vector<Point> >& squares )
|
||||
|
||||
int main(int argc, char** argv)
|
||||
{
|
||||
static const char* names[] = { "pic1.png", "pic2.png", "pic3.png",
|
||||
const char* names[] = { "pic1.png", "pic2.png", "pic3.png",
|
||||
"pic4.png", "pic5.png", "pic6.png", 0 };
|
||||
help(argv[0]);
|
||||
|
||||
if( argc > 1)
|
||||
{
|
||||
names[0] = argv[1];
|
||||
names[1] = "0";
|
||||
names[1] = 0;
|
||||
}
|
||||
|
||||
for( int i = 0; names[i] != 0; i++ )
|
||||
|
||||
Loading…
Reference in New Issue
Block a user