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Merge branch 'master' into cuda-dev

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This commit is contained in:
Vladislav Vinogradov
2012-12-24 13:48:33 +04:00
parent 4db68b50f2 c02179a765
commit 5138b7d209
66 changed files with 3506 additions and 1452 deletions
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2
CMakeLists.txt
View File

@@ -459,7 +459,7 @@ if(BUILD_EXAMPLES OR BUILD_ANDROID_EXAMPLES OR INSTALL_PYTHON_EXAMPLES)
add_subdirectory(samples)
endif()
if(BUILD_ANDROID_SERVICE)
if(ANDROID)
add_subdirectory(android/service)
endif()

22
android/android.toolchain.cmake
View File

@@ -280,6 +280,9 @@
# - November 2012
# [+] updated for NDK r8c
# [+] added support for clang compiler
# - December 2012
# [~] fixed ccache full path search
# [+] updated for NDK r8d
# ------------------------------------------------------------------------------
cmake_minimum_required( VERSION 2.6.3 )
@@ -302,7 +305,7 @@ set( CMAKE_SYSTEM_VERSION 1 )
# rpath makes low sence for Android
set( CMAKE_SKIP_RPATH TRUE CACHE BOOL "If set, runtime paths are not added when using shared libraries." )
set( ANDROID_SUPPORTED_NDK_VERSIONS ${ANDROID_EXTRA_NDK_VERSIONS} -r8c -r8b -r8 -r7c -r7b -r7 -r6b -r6 -r5c -r5b -r5 "" )
set( ANDROID_SUPPORTED_NDK_VERSIONS ${ANDROID_EXTRA_NDK_VERSIONS} -r8d -r8c -r8b -r8 -r7c -r7b -r7 -r6b -r6 -r5c -r5b -r5 "" )
if(NOT DEFINED ANDROID_NDK_SEARCH_PATHS)
if( CMAKE_HOST_WIN32 )
file( TO_CMAKE_PATH "$ENV{PROGRAMFILES}" ANDROID_NDK_SEARCH_PATHS )
@@ -962,7 +965,11 @@ if( BUILD_WITH_ANDROID_NDK )
set( ANDROID_STL_INCLUDE_DIRS "${ANDROID_NDK}/sources/cxx-stl/gabi++/include" )
set( __libstl "${ANDROID_NDK}/sources/cxx-stl/gabi++/libs/${ANDROID_NDK_ABI_NAME}/libgabi++_static.a" )
elseif( ANDROID_STL MATCHES "stlport" )
if( NOT ANDROID_NDK_RELEASE STRLESS "r8d" )
set( ANDROID_EXCEPTIONS ON )
else()
set( ANDROID_EXCEPTIONS OFF )
endif()
if( ANDROID_NDK_RELEASE STRLESS "r7" )
set( ANDROID_RTTI OFF )
else()
@@ -974,7 +981,13 @@ if( BUILD_WITH_ANDROID_NDK )
set( ANDROID_EXCEPTIONS ON )
set( ANDROID_RTTI ON )
if( EXISTS "${ANDROID_NDK}/sources/cxx-stl/gnu-libstdc++/${ANDROID_COMPILER_VERSION}" )
if( ARMEABI_V7A AND ANDROID_COMPILER_VERSION VERSION_EQUAL "4.7" AND ANDROID_NDK_RELEASE STREQUAL "r8d" )
# gnustl binary for 4.7 compiler is buggy :(
# TODO: look for right fix
set( __libstl "${ANDROID_NDK}/sources/cxx-stl/gnu-libstdc++/4.6" )
else()
set( __libstl "${ANDROID_NDK}/sources/cxx-stl/gnu-libstdc++/${ANDROID_COMPILER_VERSION}" )
endif()
else()
set( __libstl "${ANDROID_NDK}/sources/cxx-stl/gnu-libstdc++" )
endif()
@@ -1031,6 +1044,9 @@ endif()
# ccache support
__INIT_VARIABLE( _ndk_ccache NDK_CCACHE ENV_NDK_CCACHE )
if( _ndk_ccache )
if( DEFINED NDK_CCACHE AND NOT EXISTS NDK_CCACHE )
unset( NDK_CCACHE CACHE )
endif()
find_program( NDK_CCACHE "${_ndk_ccache}" DOC "The path to ccache binary")
else()
unset( NDK_CCACHE CACHE )
@@ -1260,7 +1276,7 @@ endif()
if( ANDROID_COMPILER_VERSION VERSION_EQUAL "4.6" )
if( ANDROID_GOLD_LINKER AND (CMAKE_HOST_UNIX OR ANDROID_NDK_RELEASE STRGREATER "r8b") AND (ARMEABI OR ARMEABI_V7A OR X86) )
set( ANDROID_LINKER_FLAGS "${ANDROID_LINKER_FLAGS} -fuse-ld=gold" )
elseif( ANDROID_NDK_RELEASE STREQUAL "r8c")
elseif( ANDROID_NDK_RELEASE STRGREATER "r8b")
set( ANDROID_LINKER_FLAGS "${ANDROID_LINKER_FLAGS} -fuse-ld=bfd" )
elseif( ANDROID_NDK_RELEASE STREQUAL "r8b" AND ARMEABI AND NOT _CMAKE_IN_TRY_COMPILE )
message( WARNING "The default bfd linker from arm GCC 4.6 toolchain can fail with 'unresolvable R_ARM_THM_CALL relocation' error message. See https://code.google.com/p/android/issues/detail?id=35342
@@ -1520,7 +1536,7 @@ endif()
# BUILD_WITH_STANDALONE_TOOLCHAIN : TRUE if standalone toolchain is used
# ANDROID_NDK_HOST_SYSTEM_NAME : "windows", "linux-x86" or "darwin-x86" depending on host platform
# ANDROID_NDK_ABI_NAME : "armeabi", "armeabi-v7a", "x86" or "mips" depending on ANDROID_ABI
# ANDROID_NDK_RELEASE : one of r5, r5b, r5c, r6, r6b, r7, r7b, r7c, r8, r8b, r8c; set only for NDK
# ANDROID_NDK_RELEASE : one of r5, r5b, r5c, r6, r6b, r7, r7b, r7c, r8, r8b, r8c, r8d; set only for NDK
# ANDROID_ARCH_NAME : "arm" or "x86" or "mips" depending on ANDROID_ABI
# ANDROID_SYSROOT : path to the compiler sysroot
# TOOL_OS_SUFFIX : "" or ".exe" depending on host platform

4
android/service/CMakeLists.txt
View File

@@ -1,2 +1,6 @@
if(BUILD_ANDROID_SERVICE)
add_subdirectory(engine)
#add_subdirectory(engine_test)
endif()
install(FILES "readme.txt" DESTINATION "apk/" COMPONENT main)

22
android/service/ReadMe.txt
View File

@@ -1,22 +0,0 @@
***************
Package Content
***************
The package provides new OpenCV SDK that uses OpenCV Manager for library initialization. OpenCV Manager provides the following benefits:
* Less memory usage. All apps use the same binaries from service and do not keep native libs inside them self;
* Hardware specific optimizations for all supported platforms;
* Trusted OpenCV library source. All packages with OpenCV are published on Google Play service;
* Regular updates and bug fixes;
Package consists from Library Project for Java development with Eclipse, C++ headers and libraries for native application development, javadoc samples and prebuilt binaries for ARM and X86 platforms.
To try new SDK on serial device with Google Play just install sample package and follow application messages (Google Play service access will be needed).
TO start example on device without Google Play you need to install OpenCV manager package and OpenCV binary pack for your platform from apk folder before.
See docs/doc/tutorials/introduction/android_binary_package/android_binary_package.html and docs/android/refmain.html for details about service.
On-line documentation will be available at address: http://docs.opencv.org/trunk
********
Contacts
********
Please send all feedback to Alexander Smorkalov mailto: alexander.smorkalov@itseez.com

44
android/service/doc/UseCases.rst
View File

@@ -1,6 +1,40 @@
*******************************************
Manager Workflow
*******************************************
****************
.. _manager_selection:
OpenCV Manager selection
------------------------
Since version 1.7 several packages of OpenCV Manager is built. Every package includes OpenCV library
for package target platform. The internal library is used for most cases, except the rare one, when
arm-v7a without NEON instruction set processor is detected. In this case additional binary package
for arm-v7a is used. The new package selection logic in most cases simplifies OpenCV installation
on end user devices. In most cases OpenCV Manager may be installed automatically from Google Play.
For such case, when Google Play is not available, i.e. emulator, developer board, etc, you can
install it manually using adb tool.
.. code-block:: sh
:linenos:
adb install OpenCV-2.4.3-android-sdk/apk/OpenCV_2.4.3_Manager_2.0_<platform_name>.apk
Use table to determine right OpenCV Manager package:
+----------------------------+-----------------+-----------------------------------------------------+
| Hardware Platform | Android version | Package name |
+============================+=================+=====================================================+
| Intel x86 | >= 2.3 | OpenCV_2.4.3_Manager_2.0_x86.apk |
+----------------------------+-----------------+-----------------------------------------------------+
| MIPS | >= 2.3 | OpenCV_2.4.3_Manager_2.0_mips.apk |
+----------------------------+-----------------+-----------------------------------------------------+
| armeabi (arm-v5, arm-v6) | >= 2.3 | OpenCV_2.4.3_Manager_2.0_armeabi.apk |
+----------------------------+-----------------+-----------------------------------------------------+
| armeabi-v7a (arm-v7a-NEON) | >= 2.3 | OpenCV_2.4.3_Manager_2.0_armv7a-neon.apk |
+----------------------------+-----------------+-----------------------------------------------------+
| armeabi-v7a (arm-v7a-NEON) | 2.2 | OpenCV_2.4.3.1_Manager_2.3_armv7a-neon-android8.apk |
+----------------------------+-----------------+-----------------------------------------------------+
First application start
-----------------------
@@ -9,10 +43,10 @@ There is no OpenCV Manager or OpenCV libraries:
.. image:: img/NoService.png
Aditional library package installation
--------------------------------------
Additional library package installation
---------------------------------------
There is an OpenCV Manager service, but there is no apropriate OpenCV library.
There is an OpenCV Manager service, but it does not contain appropriate OpenCV library.
If OpenCV library installation has been approved\:
.. image:: img/LibInstallAproved.png

4
android/service/engine/AndroidManifest.xml
View File

@@ -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"/>

4
android/service/engine/jni/BinderComponent/OpenCVEngine.cpp
View File

@@ -130,7 +130,7 @@ android::String16 OpenCVEngine::GetLibraryList(android::String16 version)
LOGD("Trying to load info library \"%s\"", tmp.c_str());
void* handle;
const char* (*info_func)();
InfoFunctionType info_func;
handle = dlopen(tmp.c_str(), RTLD_LAZY);
if (handle)
@@ -138,7 +138,7 @@ android::String16 OpenCVEngine::GetLibraryList(android::String16 version)
const char* error;
dlerror();
*(void **) (&info_func) = dlsym(handle, "GetLibraryList");
info_func = (InfoFunctionType)dlsym(handle, "GetLibraryList");
if ((error = dlerror()) == NULL)
{
result = String16((*info_func)());

12
android/service/engine/jni/JNIWrapper/OpenCVLibraryInfo.cpp
View File

@@ -24,12 +24,12 @@ JNIEXPORT jlong JNICALL Java_org_opencv_engine_OpenCVLibraryInfo_open
JNIEXPORT jstring JNICALL Java_org_opencv_engine_OpenCVLibraryInfo_getPackageName
(JNIEnv* env, jobject, jlong handle)
{
const char* (*info_func)();
InfoFunctionType info_func;
const char* result;
const char* error;
dlerror();
*(void **) (&info_func) = dlsym((void*)handle, "GetPackageName");
info_func = (InfoFunctionType)dlsym((void*)handle, "GetPackageName");
if ((error = dlerror()) == NULL)
result = (*info_func)();
else
@@ -44,12 +44,12 @@ JNIEXPORT jstring JNICALL Java_org_opencv_engine_OpenCVLibraryInfo_getPackageNam
JNIEXPORT jstring JNICALL Java_org_opencv_engine_OpenCVLibraryInfo_getLibraryList
(JNIEnv* env, jobject, jlong handle)
{
const char* (*info_func)();
InfoFunctionType info_func;
const char* result;
const char* error;
dlerror();
*(void **) (&info_func) = dlsym((void*)handle, "GetLibraryList");
info_func = (InfoFunctionType)dlsym((void*)handle, "GetLibraryList");
if ((error = dlerror()) == NULL)
result = (*info_func)();
else
@@ -64,12 +64,12 @@ JNIEXPORT jstring JNICALL Java_org_opencv_engine_OpenCVLibraryInfo_getLibraryLis
JNIEXPORT jstring JNICALL Java_org_opencv_engine_OpenCVLibraryInfo_getVersionName
(JNIEnv* env, jobject, jlong handle)
{
const char* (*info_func)();
InfoFunctionType info_func;
const char* result;
const char* error;
dlerror();
*(void **) (&info_func) = dlsym((void*)handle, "GetRevision");
info_func = (InfoFunctionType)dlsym((void*)handle, "GetRevision");
if ((error = dlerror()) == NULL)
result = (*info_func)();
else

8
android/service/engine/jni/NativeService/CommonPackageManager.cpp
View File

@@ -144,6 +144,13 @@ int CommonPackageManager::GetHardwareRating(int platform, int cpu_id, const std:
{
int result = -1;
if ((cpu_id & ARCH_X86) || (cpu_id & ARCH_X64) || (cpu_id & ARCH_MIPS))
// Note: No raiting for x86, x64 and MIPS
// only one package is used
result = 0;
else
{
// Calculate rating for Arm
for (size_t i = 0; i < group.size(); i++)
{
if (group[i] == std::pair<int, int>(platform, cpu_id))
@@ -152,6 +159,7 @@ int CommonPackageManager::GetHardwareRating(int platform, int cpu_id, const std:
break;
}
}
}
return result;
}

8
android/service/engine/jni/NativeService/PackageInfo.cpp
View File

@@ -342,8 +342,8 @@ InstallPath(install_path)
LOGD("Trying to load info library \"%s\"", tmp.c_str());
void* handle;
const char* (*name_func)();
const char* (*revision_func)();
InfoFunctionType name_func;
InfoFunctionType revision_func;
handle = dlopen(tmp.c_str(), RTLD_LAZY);
if (handle)
@@ -351,8 +351,8 @@ InstallPath(install_path)
const char* error;
dlerror();
*(void **) (&name_func) = dlsym(handle, "GetPackageName");
*(void **) (&revision_func) = dlsym(handle, "GetRevision");
name_func = (InfoFunctionType)dlsym(handle, "GetPackageName");
revision_func = (InfoFunctionType)dlsym(handle, "GetRevision");
error = dlerror();
if (!error && revision_func && name_func)

2
android/service/engine/jni/include/EngineCommon.h
View File

@@ -17,4 +17,6 @@
// Class name of OpenCV engine binder object. Is needned for connection to service
#define OPECV_ENGINE_CLASSNAME "org.opencv.engine.OpenCVEngineInterface"
typedef const char* (*InfoFunctionType)();
#endif

2
android/service/engine/src/org/opencv/engine/manager/ManagerActivity.java
View File

@@ -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

28
android/service/readme.txt Normal file
View File

@@ -0,0 +1,28 @@
OpenCV Manager selection
========================
Since version 1.7 several packages of OpenCV Manager is built. Every package includes OpenCV library
for package target platform. The internal library is used for most cases, except the rare one, when
arm-v7a without NEON instruction set processor is detected. In this case additional binary package
for arm-v7a is used. The new package selection logic in most cases simplifies OpenCV installation
on end user devices. In most cases OpenCV Manager may be installed automatically from Google Play.
For such case, when Google Play is not available, i.e. emulator, developer board, etc, you can
install it manually using adb tool:
adb install OpenCV-2.4.3-android-sdk/apk/OpenCV_2.4.3.2_Manager_2.4_<platform_name>.apk
Use table to determine right OpenCV Manager package:
+----------------------------+-----------------+-----------------------------------------------------+
| Hardware Platform | Android version | Package name |
+============================+=================+=====================================================+
| Intel x86 | >= 2.3 | OpenCV_2.4.3.2_Manager_2.4_x86.apk |
+----------------------------+-----------------+-----------------------------------------------------+
| MIPS | >= 2.3 | OpenCV_2.4.3.2_Manager_2.4_mips.apk |
+----------------------------+-----------------+-----------------------------------------------------+
| armeabi (arm-v5, arm-v6) | >= 2.3 | OpenCV_2.4.3.2_Manager_2.4_armeabi.apk |
+----------------------------+-----------------+-----------------------------------------------------+
| armeabi-v7a (arm-v7a-NEON) | >= 2.3 | OpenCV_2.4.3.2_Manager_2.4_armv7a-neon.apk |
+----------------------------+-----------------+-----------------------------------------------------+
| armeabi-v7a (arm-v7a-NEON) | 2.2 | OpenCV_2.4.3.2_Manager_2.4_armv7a-neon-android8.apk |
+----------------------------+-----------------+-----------------------------------------------------+

2
cmake/OpenCVCompilerOptions.cmake
View File

@@ -61,7 +61,7 @@ if(CMAKE_COMPILER_IS_GNUCXX)
add_extra_compiler_option(-W)
add_extra_compiler_option(-Wall)
add_extra_compiler_option(-Werror=return-type)
#add_extra_compiler_option(-Werror=non-virtual-dtor)
add_extra_compiler_option(-Werror=non-virtual-dtor)
add_extra_compiler_option(-Werror=address)
add_extra_compiler_option(-Werror=sequence-point)
add_extra_compiler_option(-Wformat)

2
cmake/OpenCVPCHSupport.cmake
View File

@@ -19,7 +19,7 @@ IF(CMAKE_COMPILER_IS_GNUCXX)
ARGS ${CMAKE_CXX_COMPILER_ARG1} -dumpversion
OUTPUT_VARIABLE gcc_compiler_version)
#MESSAGE("GCC Version: ${gcc_compiler_version}")
IF(gcc_compiler_version MATCHES "4\\.[0,2-9]\\.[0-9x]")
IF(gcc_compiler_version VERSION_GREATER "4.2.-1")
SET(PCHSupport_FOUND TRUE)
ENDIF()

25
doc/CMakeLists.txt
View File

@@ -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()

2
doc/tutorials/imgproc/shapedescriptors/bounding_rects_circles/bounding_rects_circles.rst
View File

@@ -85,7 +85,7 @@ This tutorial code's is shown lines below. You can also download it from `here <
for( int i = 0; i < contours.size(); i++ )
{ approxPolyDP( Mat(contours[i]), contours_poly[i], 3, true );
boundRect[i] = boundingRect( Mat(contours_poly[i]) );
minEnclosingCircle( contours_poly[i], center[i], radius[i] );
minEnclosingCircle( (Mat)contours_poly[i], center[i], radius[i] );
}

24
doc/tutorials/introduction/android_binary_package/O4A_SDK.rst
View File

@@ -50,8 +50,8 @@ The structure of package contents looks as follows:
OpenCV-2.4.3-android-sdk
|_ apk
| |_ OpenCV_2.4.3_binary_pack_XXX.apk
| |_ OpenCV_2.4.3_Manager.apk
| |_ OpenCV_2.4.3_binary_pack_armv7a.apk
| |_ OpenCV_2.4.3_Manager_2.0_XXX.apk
|
|_ doc
|_ samples
@@ -85,8 +85,8 @@ The structure of package contents looks as follows:
On production devices that have access to Google Play Market (and Internet) these packages will be
installed from Market on the first start of an application using OpenCV Manager API.
But devkits without Market or Internet connection require this packages to be installed manually.
Install the `Manager.apk` and the corresponding `binary_pack.apk` depending on the device CPU,
the Manager GUI provides this info. Below you'll see exact commands on how to do this.
Install the `Manager.apk` and optional `binary_pack.apk` if it needed.
See :ref:`manager_selection` for details.
.. note:: Installation from Internet is the preferable way since OpenCV team may publish updated
versions of this packages on the Market.
@@ -280,21 +280,7 @@ Well, running samples from Eclipse is very simple:
To get rid of the message you will need to install `OpenCV Manager` and the appropriate `OpenCV binary pack`.
Simply tap :menuselection:`Yes` if you have *Google Play Market* installed on your device/emulator. It will redirect you to the corresponding page on *Google Play Market*.
If you have no access to the *Market*, which is often the case with emulators - you will need to install the packages from OpenCV4Android SDK folder manually. Open the console/terminal and type in the following two commands:
.. code-block:: sh
:linenos:
<Android SDK path>/platform-tools/adb install <OpenCV4Android SDK path>/apk/OpenCV_2.4.3_Manager.apk
<Android SDK path>/platform-tools/adb install <OpenCV4Android SDK path>/apk/OpenCV_2.4.3_binary_pack_armv7a.apk
If you're running Windows, that will probably look like this:
.. image:: images/install_opencv_manager_with_adb.png
:alt: Run these commands in the console to install OpenCV Manager
:align: center
When done, you will be able to run OpenCV samples on your device/emulator seamlessly.
If you have no access to the *Market*, which is often the case with emulators - you will need to install the packages from OpenCV4Android SDK folder manually. See :ref:`manager_selection` for details.
* Here is ``Tutorial 2 - Use OpenCV Camera`` sample, running on top of stock camera-preview of the emulator.

16
doc/tutorials/introduction/android_binary_package/dev_with_OCV_on_Android.rst
View File

@@ -54,20 +54,8 @@ Using async initialization is a **recommended** way for application development.
:alt: Add dependency from OpenCV library
:align: center
To run OpenCV Manager-based application for the first time you need to install package with the `OpenCV Manager` for your platform. Armeabi, Armeabi-v7a with NEON, x86 and MIPS achitectures supported.
You can do it using Google Play Market or manually with ``adb`` tool:
.. code-block:: sh
:linenos:
<Android SDK path>/platform-tools/adb install <OpenCV4Android SDK path>/apk/OpenCV_2.4.3_Manager.apk
For rare cases if NEON instruction set is not supported you need to install aditional OpenCV Library package:
.. code-block:: sh
:linenos:
<Android SDK path>/platform-tools/adb install <OpenCV4Android SDK path>/apk/OpenCV_2.4.3_binary_pack_armv7a.apk
In most cases OpenCV Manager may be installed automatically from Google Play. For such case, when Google Play is not available, i.e. emulator, developer board, etc, you can
install it manually using adb tool. See :ref:`manager_selection` for details.
There is a very base code snippet implementing the async initialization. It shows basic principles. See the "15-puzzle" OpenCV sample for details.

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8
doc/user_guide/ug_mat.rst
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@@ -71,7 +71,9 @@ There are functions in OpenCV, especially from calib3d module, such as ``project
//... fill the array
Mat pointsMat = Mat(points);
One can access a point in this matrix using the same method \texttt{Mat::at}: ::
One can access a point in this matrix using the same method ``Mat::at`` :
::
Point2f point = pointsMat.at<Point2f>(i, 0);
@@ -109,7 +111,7 @@ Selecting a region of interest: ::
Rect r(10, 10, 100, 100);
Mat smallImg = img(r);
A convertion from \texttt{Mat} to C API data structures: ::
A convertion from ``Mat`` to C API data structures: ::
Mat img = imread("image.jpg");
IplImage img1 = img;
@@ -150,7 +152,7 @@ A call to ``waitKey()`` starts a message passing cycle that waits for a key stro
double minVal, maxVal;
minMaxLoc(sobelx, &minVal, &maxVal); //find minimum and maximum intensities
Mat draw;
sobelx.convertTo(draw, CV_8U, 255.0/(maxVal - minVal), -minVal);
sobelx.convertTo(draw, CV_8U, 255.0/(maxVal - minVal), -minVal * 255.0/(maxVal - minVal));
namedWindow("image", CV_WINDOW_AUTOSIZE);
imshow("image", draw);

2
modules/calib3d/perf/perf_pnp.cpp
View File

@@ -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)
)
)

13
modules/core/include/opencv2/core/core.hpp
View File

@@ -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
};
@@ -1345,7 +1340,7 @@ public:
virtual int channels(int i=-1) const;
virtual bool empty() const;
/*virtual*/ ~_InputArray();
virtual ~_InputArray();
int flags;
void* obj;
@@ -1413,7 +1408,7 @@ public:
virtual void release() const;
virtual void clear() const;
/*virtual*/ ~_OutputArray();
virtual ~_OutputArray();
};
typedef const _InputArray& InputArray;

7
modules/core/include/opencv2/core/operations.hpp
View File

@@ -64,7 +64,7 @@
#endif
#elif __GNUC__*10 + __GNUC_MINOR__ >= 42
#if !defined WIN32 && (defined __i486__ || defined __i586__ || \
#if !(defined WIN32 || defined _WIN32) && (defined __i486__ || defined __i586__ || \
defined __i686__ || defined __MMX__ || defined __SSE__ || defined __ppc__)
#define CV_XADD __sync_fetch_and_add
#else
@@ -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();

31
modules/core/src/persistence.cpp
View File

@@ -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()
@@ -5200,6 +5170,7 @@ void FileStorage::release()
string FileStorage::releaseAndGetString()
{
string buf;
buf.reserve(16); // HACK: Work around for compiler bug
if( fs.obj && fs.obj->outbuf )
icvClose(fs.obj, &buf);

33
modules/core/src/system.cpp
View File

@@ -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;

2
modules/features2d/perf/perf_fast.cpp
View File

@@ -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);

4
modules/features2d/src/matchers.cpp
View File

@@ -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"];

2
modules/highgui/perf/perf_output.cpp
View File

@@ -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; }

6
modules/highgui/src/cap_gstreamer.cpp
View File

@@ -399,12 +399,12 @@ bool CvCapture_GStreamer::open( int type, const char* filename )
gst_app_sink_set_max_buffers (GST_APP_SINK(sink), 1);
gst_app_sink_set_drop (GST_APP_SINK(sink), stream);
gst_app_sink_set_caps(GST_APP_SINK(sink), gst_caps_new_simple("video/x-raw-rgb",
caps = gst_caps_new_simple("video/x-raw-rgb",
"red_mask", G_TYPE_INT, 0x0000FF,
"green_mask", G_TYPE_INT, 0x00FF00,
"blue_mask", G_TYPE_INT, 0xFF0000,
NULL));
NULL);
gst_app_sink_set_caps(GST_APP_SINK(sink), caps);
gst_caps_unref(caps);
if(gst_element_set_state(GST_ELEMENT(pipeline), GST_STATE_READY) ==

2
modules/imgproc/doc/miscellaneous_transformations.rst
View File

@@ -661,7 +661,7 @@ Applies a fixed-level threshold to each array element.
:param dst: output array of the same size and type as ``src``.
:param thresh: treshold value.
:param thresh: threshold value.
:param maxval: maximum value to use with the ``THRESH_BINARY`` and ``THRESH_BINARY_INV`` thresholding types.

2
modules/imgproc/doc/structural_analysis_and_shape_descriptors.rst
View File

@@ -137,7 +137,7 @@ Finds contours in a binary image.
:param contours: Detected contours. Each contour is stored as a vector of points.
:param hierarchy: Optional output vector containing information about the image topology. It has as many elements as the number of contours. For each contour ``contours[i]`` , the elements ``hierarchy[i][0]`` , ``hiearchy[i][1]`` , ``hiearchy[i][2]`` , and ``hiearchy[i][3]`` are set to 0-based indices in ``contours`` of the next and previous contours at the same hierarchical level: the first child contour and the parent contour, respectively. If for a contour ``i`` there are no next, previous, parent, or nested contours, the corresponding elements of ``hierarchy[i]`` will be negative.
:param hierarchy: Optional output vector, containing information about the image topology. It has as many elements as the number of contours. For each i-th contour ``contours[i]`` , the elements ``hierarchy[i][0]`` , ``hiearchy[i][1]`` , ``hiearchy[i][2]`` , and ``hiearchy[i][3]`` are set to 0-based indices in ``contours`` of the next and previous contours at the same hierarchical level, the first child contour and the parent contour, respectively. If for the contour ``i`` there are no next, previous, parent, or nested contours, the corresponding elements of ``hierarchy[i]`` will be negative.
:param mode: Contour retrieval mode (if you use Python see also a note below).

16
modules/imgproc/include/opencv2/imgproc/imgproc.hpp
View File

@@ -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 */

13
modules/imgproc/include/opencv2/imgproc/types_c.h
View File

@@ -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
};

25
modules/imgproc/perf/perf_cvt_color.cpp
View File

@@ -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);
}

2
modules/imgproc/perf/perf_filter2d.cpp
View File

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

73
modules/imgproc/perf/perf_histogram.cpp
View File

@@ -9,14 +9,14 @@ using std::tr1::get;
typedef tr1::tuple<Size, MatType> Size_Source_t;
typedef TestBaseWithParam<Size_Source_t> Size_Source;
typedef TestBaseWithParam<Size> MatSize;
static const float rangeHight = 256.0f;
static const float rangeLow = 0.0f;
PERF_TEST_P(Size_Source, calcHist,
testing::Combine(testing::Values(TYPICAL_MAT_SIZES),
testing::Values(CV_8U, CV_32F)
)
PERF_TEST_P(Size_Source, calcHist1d,
testing::Combine(testing::Values(sz3MP, sz5MP),
testing::Values(CV_8U, CV_16U, CV_32F) )
)
{
Size size = get<0>(GetParam());
@@ -28,10 +28,69 @@ PERF_TEST_P(Size_Source, calcHist,
int dims = 1;
int numberOfImages = 1;
const float r[] = {0.0f, 256.0f};
const float r[] = {rangeLow, rangeHight};
const float* ranges[] = {r};
declare.in(source, WARMUP_RNG).time(20).iterations(1000);
randu(source, rangeLow, rangeHight);
declare.in(source);
TEST_CYCLE()
{
calcHist(&source, numberOfImages, channels, Mat(), hist, dims, histSize, ranges);
}
SANITY_CHECK(hist);
}
PERF_TEST_P(Size_Source, calcHist2d,
testing::Combine(testing::Values(sz3MP, sz5MP),
testing::Values(CV_8UC2, CV_16UC2, CV_32FC2) )
)
{
Size size = get<0>(GetParam());
MatType type = get<1>(GetParam());
Mat source(size.height, size.width, type);
Mat hist;
int channels [] = {0, 1};
int histSize [] = {256, 256};
int dims = 2;
int numberOfImages = 1;
const float r[] = {rangeLow, rangeHight};
const float* ranges[] = {r, r};
randu(source, rangeLow, rangeHight);
declare.in(source);
TEST_CYCLE()
{
calcHist(&source, numberOfImages, channels, Mat(), hist, dims, histSize, ranges);
}
SANITY_CHECK(hist);
}
PERF_TEST_P(Size_Source, calcHist3d,
testing::Combine(testing::Values(sz3MP, sz5MP),
testing::Values(CV_8UC3, CV_16UC3, CV_32FC3) )
)
{
Size size = get<0>(GetParam());
MatType type = get<1>(GetParam());
Mat hist;
int channels [] = {0, 1, 2};
int histSize [] = {32, 32, 32};
int dims = 3;
int numberOfImages = 1;
Mat source(size.height, size.width, type);
const float r[] = {rangeLow, rangeHight};
const float* ranges[] = {r, r, r};
randu(source, rangeLow, rangeHight);
declare.in(source);
TEST_CYCLE()
{
calcHist(&source, numberOfImages, channels, Mat(), hist, dims, histSize, ranges);

2
modules/imgproc/perf/perf_resize.cpp
View File

@@ -71,7 +71,7 @@ typedef TestBaseWithParam<MatInfo_Size_Scale_t> MatInfo_Size_Scale;
PERF_TEST_P(MatInfo_Size_Scale, ResizeAreaFast,
testing::Combine(
testing::Values(CV_8UC1, CV_8UC4),
testing::Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_16UC1, CV_16UC3, CV_16UC4),
testing::Values(szVGA, szqHD, sz720p, sz1080p),
testing::Values(2)
)

983
modules/imgproc/src/color.cpp
View File

File diff suppressed because it is too large Load Diff

1516
modules/imgproc/src/demosaicing.cpp Normal file
View File

File diff suppressed because it is too large Load Diff

815
modules/imgproc/src/histogram.cpp
View File

@@ -165,11 +165,13 @@ static void histPrepareImages( const Mat* images, int nimages, const int* channe
deltas[dims*2 + 1] = (int)(mask.step/mask.elemSize1());
}
#ifndef HAVE_TBB
if( isContinuous )
{
imsize.width *= imsize.height;
imsize.height = 1;
}
#endif
if( !ranges )
{
@@ -207,6 +209,538 @@ static void histPrepareImages( const Mat* images, int nimages, const int* channe
////////////////////////////////// C A L C U L A T E H I S T O G R A M ////////////////////////////////////
#ifdef HAVE_TBB
enum {one = 1, two, three}; // array elements number
template<typename T>
class calcHist1D_Invoker
{
public:
calcHist1D_Invoker( const vector<uchar*>& _ptrs, const vector<int>& _deltas,
Mat& hist, const double* _uniranges, int sz, int dims,
Size& imageSize )
: mask_(_ptrs[dims]),
mstep_(_deltas[dims*2 + 1]),
imageWidth_(imageSize.width),
histogramSize_(hist.size()), histogramType_(hist.type()),
globalHistogram_((tbb::atomic<int>*)hist.data)
{
p_[0] = ((T**)&_ptrs[0])[0];
step_[0] = (&_deltas[0])[1];
d_[0] = (&_deltas[0])[0];
a_[0] = (&_uniranges[0])[0];
b_[0] = (&_uniranges[0])[1];
size_[0] = sz;
}
void operator()( const BlockedRange& range ) const
{
T* p0 = p_[0] + range.begin() * (step_[0] + imageWidth_*d_[0]);
uchar* mask = mask_ + range.begin()*mstep_;
for( int row = range.begin(); row < range.end(); row++, p0 += step_[0] )
{
if( !mask_ )
{
for( int x = 0; x < imageWidth_; x++, p0 += d_[0] )
{
int idx = cvFloor(*p0*a_[0] + b_[0]);
if( (unsigned)idx < (unsigned)size_[0] )
{
globalHistogram_[idx].fetch_and_add(1);
}
}
}
else
{
for( int x = 0; x < imageWidth_; x++, p0 += d_[0] )
{
if( mask[x] )
{
int idx = cvFloor(*p0*a_[0] + b_[0]);
if( (unsigned)idx < (unsigned)size_[0] )
{
globalHistogram_[idx].fetch_and_add(1);
}
}
}
mask += mstep_;
}
}
}
private:
T* p_[one];
uchar* mask_;
int step_[one];
int d_[one];
int mstep_;
double a_[one];
double b_[one];
int size_[one];
int imageWidth_;
Size histogramSize_;
int histogramType_;
tbb::atomic<int>* globalHistogram_;
};
template<typename T>
class calcHist2D_Invoker
{
public:
calcHist2D_Invoker( const vector<uchar*>& _ptrs, const vector<int>& _deltas,
Mat& hist, const double* _uniranges, const int* size,
int dims, Size& imageSize, size_t* hstep )
: mask_(_ptrs[dims]),
mstep_(_deltas[dims*2 + 1]),
imageWidth_(imageSize.width),
histogramSize_(hist.size()), histogramType_(hist.type()),
globalHistogram_(hist.data)
{
p_[0] = ((T**)&_ptrs[0])[0]; p_[1] = ((T**)&_ptrs[0])[1];
step_[0] = (&_deltas[0])[1]; step_[1] = (&_deltas[0])[3];
d_[0] = (&_deltas[0])[0]; d_[1] = (&_deltas[0])[2];
a_[0] = (&_uniranges[0])[0]; a_[1] = (&_uniranges[0])[2];
b_[0] = (&_uniranges[0])[1]; b_[1] = (&_uniranges[0])[3];
size_[0] = size[0]; size_[1] = size[1];
hstep_[0] = hstep[0];
}
void operator()(const BlockedRange& range) const
{
T* p0 = p_[0] + range.begin()*(step_[0] + imageWidth_*d_[0]);
T* p1 = p_[1] + range.begin()*(step_[1] + imageWidth_*d_[1]);
uchar* mask = mask_ + range.begin()*mstep_;
for( int row = range.begin(); row < range.end(); row++, p0 += step_[0], p1 += step_[1] )
{
if( !mask_ )
{
for( int x = 0; x < imageWidth_; x++, p0 += d_[0], p1 += d_[1] )
{
int idx0 = cvFloor(*p0*a_[0] + b_[0]);
int idx1 = cvFloor(*p1*a_[1] + b_[1]);
if( (unsigned)idx0 < (unsigned)size_[0] && (unsigned)idx1 < (unsigned)size_[1] )
( (tbb::atomic<int>*)(globalHistogram_ + hstep_[0]*idx0) )[idx1].fetch_and_add(1);
}
}
else
{
for( int x = 0; x < imageWidth_; x++, p0 += d_[0], p1 += d_[1] )
{
if( mask[x] )
{
int idx0 = cvFloor(*p0*a_[0] + b_[0]);
int idx1 = cvFloor(*p1*a_[1] + b_[1]);
if( (unsigned)idx0 < (unsigned)size_[0] && (unsigned)idx1 < (unsigned)size_[1] )
((tbb::atomic<int>*)(globalHistogram_ + hstep_[0]*idx0))[idx1].fetch_and_add(1);
}
}
mask += mstep_;
}
}
}
private:
T* p_[two];
uchar* mask_;
int step_[two];
int d_[two];
int mstep_;
double a_[two];
double b_[two];
int size_[two];
const int imageWidth_;
size_t hstep_[one];
Size histogramSize_;
int histogramType_;
uchar* globalHistogram_;
};
template<typename T>
class calcHist3D_Invoker
{
public:
calcHist3D_Invoker( const vector<uchar*>& _ptrs, const vector<int>& _deltas,
Size imsize, Mat& hist, const double* uniranges, int _dims,
size_t* hstep, int* size )
: mask_(_ptrs[_dims]),
mstep_(_deltas[_dims*2 + 1]),
imageWidth_(imsize.width),
globalHistogram_(hist.data)
{
p_[0] = ((T**)&_ptrs[0])[0]; p_[1] = ((T**)&_ptrs[0])[1]; p_[2] = ((T**)&_ptrs[0])[2];
step_[0] = (&_deltas[0])[1]; step_[1] = (&_deltas[0])[3]; step_[2] = (&_deltas[0])[5];
d_[0] = (&_deltas[0])[0]; d_[1] = (&_deltas[0])[2]; d_[2] = (&_deltas[0])[4];
a_[0] = uniranges[0]; a_[1] = uniranges[2]; a_[2] = uniranges[4];
b_[0] = uniranges[1]; b_[1] = uniranges[3]; b_[2] = uniranges[5];
size_[0] = size[0]; size_[1] = size[1]; size_[2] = size[2];
hstep_[0] = hstep[0]; hstep_[1] = hstep[1];
}
void operator()( const BlockedRange& range ) const
{
T* p0 = p_[0] + range.begin()*(imageWidth_*d_[0] + step_[0]);
T* p1 = p_[1] + range.begin()*(imageWidth_*d_[1] + step_[1]);
T* p2 = p_[2] + range.begin()*(imageWidth_*d_[2] + step_[2]);
uchar* mask = mask_ + range.begin()*mstep_;
for( int i = range.begin(); i < range.end(); i++, p0 += step_[0], p1 += step_[1], p2 += step_[2] )
{
if( !mask_ )
{
for( int x = 0; x < imageWidth_; x++, p0 += d_[0], p1 += d_[1], p2 += d_[2] )
{
int idx0 = cvFloor(*p0*a_[0] + b_[0]);
int idx1 = cvFloor(*p1*a_[1] + b_[1]);
int idx2 = cvFloor(*p2*a_[2] + b_[2]);
if( (unsigned)idx0 < (unsigned)size_[0] &&
(unsigned)idx1 < (unsigned)size_[1] &&
(unsigned)idx2 < (unsigned)size_[2] )
{
( (tbb::atomic<int>*)(globalHistogram_ + hstep_[0]*idx0 + hstep_[1]*idx1) )[idx2].fetch_and_add(1);
}
}
}
else
{
for( int x = 0; x < imageWidth_; x++, p0 += d_[0], p1 += d_[1], p2 += d_[2] )
{
if( mask[x] )
{
int idx0 = cvFloor(*p0*a_[0] + b_[0]);
int idx1 = cvFloor(*p1*a_[1] + b_[1]);
int idx2 = cvFloor(*p2*a_[2] + b_[2]);
if( (unsigned)idx0 < (unsigned)size_[0] &&
(unsigned)idx1 < (unsigned)size_[1] &&
(unsigned)idx2 < (unsigned)size_[2] )
{
( (tbb::atomic<int>*)(globalHistogram_ + hstep_[0]*idx0 + hstep_[1]*idx1) )[idx2].fetch_and_add(1);
}
}
}
mask += mstep_;
}
}
}
static bool isFit( const Mat& histogram, const Size imageSize )
{
return ( imageSize.width * imageSize.height >= 320*240
&& histogram.total() >= 8*8*8 );
}
private:
T* p_[three];
uchar* mask_;
int step_[three];
int d_[three];
const int mstep_;
double a_[three];
double b_[three];
int size_[three];
int imageWidth_;
size_t hstep_[two];
uchar* globalHistogram_;
};
class CalcHist1D_8uInvoker
{
public:
CalcHist1D_8uInvoker( const vector<uchar*>& ptrs, const vector<int>& deltas,
Size imsize, Mat& hist, int dims, const vector<size_t>& tab,
tbb::mutex* lock )
: mask_(ptrs[dims]),
mstep_(deltas[dims*2 + 1]),
imageWidth_(imsize.width),
imageSize_(imsize),
histSize_(hist.size()), histType_(hist.type()),
tab_((size_t*)&tab[0]),
histogramWriteLock_(lock),
globalHistogram_(hist.data)
{
p_[0] = (&ptrs[0])[0];
step_[0] = (&deltas[0])[1];
d_[0] = (&deltas[0])[0];
}
void operator()( const BlockedRange& range ) const
{
int localHistogram[256] = { 0, };
uchar* mask = mask_;
uchar* p0 = p_[0];
int x;
tbb::mutex::scoped_lock lock;
if( !mask_ )
{
int n = (imageWidth_ - 4) / 4 + 1;
int tail = imageWidth_ - n*4;
int xN = 4*n;
p0 += (xN*d_[0] + tail*d_[0] + step_[0]) * range.begin();
}
else
{
p0 += (imageWidth_*d_[0] + step_[0]) * range.begin();
mask += mstep_*range.begin();
}
for( int i = range.begin(); i < range.end(); i++, p0 += step_[0] )
{
if( !mask_ )
{
if( d_[0] == 1 )
{
for( x = 0; x <= imageWidth_ - 4; x += 4 )
{
int t0 = p0[x], t1 = p0[x+1];
localHistogram[t0]++; localHistogram[t1]++;
t0 = p0[x+2]; t1 = p0[x+3];
localHistogram[t0]++; localHistogram[t1]++;
}
p0 += x;
}
else
{
for( x = 0; x <= imageWidth_ - 4; x += 4 )
{
int t0 = p0[0], t1 = p0[d_[0]];
localHistogram[t0]++; localHistogram[t1]++;
p0 += d_[0]*2;
t0 = p0[0]; t1 = p0[d_[0]];
localHistogram[t0]++; localHistogram[t1]++;
p0 += d_[0]*2;
}
}
for( ; x < imageWidth_; x++, p0 += d_[0] )
{
localHistogram[*p0]++;
}
}
else
{
for( x = 0; x < imageWidth_; x++, p0 += d_[0] )
{
if( mask[x] )
{
localHistogram[*p0]++;
}
}
mask += mstep_;
}
}
lock.acquire(*histogramWriteLock_);
for(int i = 0; i < 256; i++ )
{
size_t hidx = tab_[i];
if( hidx < OUT_OF_RANGE )
{
*(int*)((globalHistogram_ + hidx)) += localHistogram[i];
}
}
lock.release();
}
static bool isFit( const Mat& histogram, const Size imageSize )
{
return ( histogram.total() >= 8
&& imageSize.width * imageSize.height >= 160*120 );
}
private:
uchar* p_[one];
uchar* mask_;
int mstep_;
int step_[one];
int d_[one];
int imageWidth_;
Size imageSize_;
Size histSize_;
int histType_;
size_t* tab_;
tbb::mutex* histogramWriteLock_;
uchar* globalHistogram_;
};
class CalcHist2D_8uInvoker
{
public:
CalcHist2D_8uInvoker( const vector<uchar*>& _ptrs, const vector<int>& _deltas,
Size imsize, Mat& hist, int dims, const vector<size_t>& _tab,
tbb::mutex* lock )
: mask_(_ptrs[dims]),
mstep_(_deltas[dims*2 + 1]),
imageWidth_(imsize.width),
histSize_(hist.size()), histType_(hist.type()),
tab_((size_t*)&_tab[0]),
histogramWriteLock_(lock),
globalHistogram_(hist.data)
{
p_[0] = (uchar*)(&_ptrs[0])[0]; p_[1] = (uchar*)(&_ptrs[0])[1];
step_[0] = (&_deltas[0])[1]; step_[1] = (&_deltas[0])[3];
d_[0] = (&_deltas[0])[0]; d_[1] = (&_deltas[0])[2];
}
void operator()( const BlockedRange& range ) const
{
uchar* p0 = p_[0] + range.begin()*(step_[0] + imageWidth_*d_[0]);
uchar* p1 = p_[1] + range.begin()*(step_[1] + imageWidth_*d_[1]);
uchar* mask = mask_ + range.begin()*mstep_;
Mat localHist = Mat::zeros(histSize_, histType_);
uchar* localHistData = localHist.data;
tbb::mutex::scoped_lock lock;
for(int i = range.begin(); i < range.end(); i++, p0 += step_[0], p1 += step_[1])
{
if( !mask_ )
{
for( int x = 0; x < imageWidth_; x++, p0 += d_[0], p1 += d_[1] )
{
size_t idx = tab_[*p0] + tab_[*p1 + 256];
if( idx < OUT_OF_RANGE )
{
++*(int*)(localHistData + idx);
}
}
}
else
{
for( int x = 0; x < imageWidth_; x++, p0 += d_[0], p1 += d_[1] )
{
size_t idx;
if( mask[x] && (idx = tab_[*p0] + tab_[*p1 + 256]) < OUT_OF_RANGE )
{
++*(int*)(localHistData + idx);
}
}
mask += mstep_;
}
}
lock.acquire(*histogramWriteLock_);
for(int i = 0; i < histSize_.width*histSize_.height; i++)
{
((int*)globalHistogram_)[i] += ((int*)localHistData)[i];
}
lock.release();
}
static bool isFit( const Mat& histogram, const Size imageSize )
{
return ( (histogram.total() > 4*4 && histogram.total() <= 116*116
&& imageSize.width * imageSize.height >= 320*240)
|| (histogram.total() > 116*116 && imageSize.width * imageSize.height >= 1280*720) );
}
private:
uchar* p_[two];
uchar* mask_;
int step_[two];
int d_[two];
int mstep_;
int imageWidth_;
Size histSize_;
int histType_;
size_t* tab_;
tbb::mutex* histogramWriteLock_;
uchar* globalHistogram_;
};
class CalcHist3D_8uInvoker
{
public:
CalcHist3D_8uInvoker( const vector<uchar*>& _ptrs, const vector<int>& _deltas,
Size imsize, Mat& hist, int dims, const vector<size_t>& tab )
: mask_(_ptrs[dims]),
mstep_(_deltas[dims*2 + 1]),
histogramSize_(hist.size.p), histogramType_(hist.type()),
imageWidth_(imsize.width),
tab_((size_t*)&tab[0]),
globalHistogram_(hist.data)
{
p_[0] = (uchar*)(&_ptrs[0])[0]; p_[1] = (uchar*)(&_ptrs[0])[1]; p_[2] = (uchar*)(&_ptrs[0])[2];
step_[0] = (&_deltas[0])[1]; step_[1] = (&_deltas[0])[3]; step_[2] = (&_deltas[0])[5];
d_[0] = (&_deltas[0])[0]; d_[1] = (&_deltas[0])[2]; d_[2] = (&_deltas[0])[4];
}
void operator()( const BlockedRange& range ) const
{
uchar* p0 = p_[0] + range.begin()*(step_[0] + imageWidth_*d_[0]);
uchar* p1 = p_[1] + range.begin()*(step_[1] + imageWidth_*d_[1]);
uchar* p2 = p_[2] + range.begin()*(step_[2] + imageWidth_*d_[2]);
uchar* mask = mask_ + range.begin()*mstep_;
for(int i = range.begin(); i < range.end(); i++, p0 += step_[0], p1 += step_[1], p2 += step_[2] )
{
if( !mask_ )
{
for( int x = 0; x < imageWidth_; x++, p0 += d_[0], p1 += d_[1], p2 += d_[2] )
{
size_t idx = tab_[*p0] + tab_[*p1 + 256] + tab_[*p2 + 512];
if( idx < OUT_OF_RANGE )
{
( *(tbb::atomic<int>*)(globalHistogram_ + idx) ).fetch_and_add(1);
}
}
}
else
{
for( int x = 0; x < imageWidth_; x++, p0 += d_[0], p1 += d_[1], p2 += d_[2] )
{
size_t idx;
if( mask[x] && (idx = tab_[*p0] + tab_[*p1 + 256] + tab_[*p2 + 512]) < OUT_OF_RANGE )
{
(*(tbb::atomic<int>*)(globalHistogram_ + idx)).fetch_and_add(1);
}
}
mask += mstep_;
}
}
}
static bool isFit( const Mat& histogram, const Size imageSize )
{
return ( histogram.total() >= 128*128*128
&& imageSize.width * imageSize.width >= 320*240 );
}
private:
uchar* p_[three];
uchar* mask_;
int mstep_;
int step_[three];
int d_[three];
int* histogramSize_;
int histogramType_;
int imageWidth_;
size_t* tab_;
uchar* globalHistogram_;
};
static void
callCalcHist2D_8u( vector<uchar*>& _ptrs, const vector<int>& _deltas,
Size imsize, Mat& hist, int dims, vector<size_t>& _tab )
{
int grainSize = imsize.height / tbb::task_scheduler_init::default_num_threads();
tbb::mutex histogramWriteLock;
CalcHist2D_8uInvoker body(_ptrs, _deltas, imsize, hist, dims, _tab, &histogramWriteLock);
parallel_for(BlockedRange(0, imsize.height, grainSize), body);
}
static void
callCalcHist3D_8u( vector<uchar*>& _ptrs, const vector<int>& _deltas,
Size imsize, Mat& hist, int dims, vector<size_t>& _tab )
{
CalcHist3D_8uInvoker body(_ptrs, _deltas, imsize, hist, dims, _tab);
parallel_for(BlockedRange(0, imsize.height), body);
}
#endif
template<typename T> static void
calcHist_( vector<uchar*>& _ptrs, const vector<int>& _deltas,
@@ -234,6 +768,11 @@ calcHist_( vector<uchar*>& _ptrs, const vector<int>& _deltas,
if( dims == 1 )
{
#ifdef HAVE_TBB
calcHist1D_Invoker<T> body(_ptrs, _deltas, hist, _uniranges, size[0], dims, imsize);
parallel_for(BlockedRange(0, imsize.height), body);
return;
#endif
double a = uniranges[0], b = uniranges[1];
int sz = size[0], d0 = deltas[0], step0 = deltas[1];
const T* p0 = (const T*)ptrs[0];
@@ -259,6 +798,11 @@ calcHist_( vector<uchar*>& _ptrs, const vector<int>& _deltas,
}
else if( dims == 2 )
{
#ifdef HAVE_TBB
calcHist2D_Invoker<T> body(_ptrs, _deltas, hist, _uniranges, size, dims, imsize, hstep);
parallel_for(BlockedRange(0, imsize.height), body);
return;
#endif
double a0 = uniranges[0], b0 = uniranges[1], a1 = uniranges[2], b1 = uniranges[3];
int sz0 = size[0], sz1 = size[1];
int d0 = deltas[0], step0 = deltas[1],
@@ -290,6 +834,14 @@ calcHist_( vector<uchar*>& _ptrs, const vector<int>& _deltas,
}
else if( dims == 3 )
{
#ifdef HAVE_TBB
if( calcHist3D_Invoker<T>::isFit(hist, imsize) )
{
calcHist3D_Invoker<T> body(_ptrs, _deltas, imsize, hist, uniranges, dims, hstep, size);
parallel_for(BlockedRange(0, imsize.height), body);
return;
}
#endif
double a0 = uniranges[0], b0 = uniranges[1],
a1 = uniranges[2], b1 = uniranges[3],
a2 = uniranges[4], b2 = uniranges[5];
@@ -441,8 +993,20 @@ calcHist_8u( vector<uchar*>& _ptrs, const vector<int>& _deltas,
if( dims == 1 )
{
#ifdef HAVE_TBB
if( CalcHist1D_8uInvoker::isFit(hist, imsize) )
{
int treadsNumber = tbb::task_scheduler_init::default_num_threads();
int grainSize = imsize.height/treadsNumber;
tbb::mutex histogramWriteLock;
CalcHist1D_8uInvoker body(_ptrs, _deltas, imsize, hist, dims, _tab, &histogramWriteLock);
parallel_for(BlockedRange(0, imsize.height, grainSize), body);
return;
}
#endif
int d0 = deltas[0], step0 = deltas[1];
int matH[256] = {0};
int matH[256] = { 0, };
const uchar* p0 = (const uchar*)ptrs[0];
for( ; imsize.height--; p0 += step0, mask += mstep )
@@ -489,6 +1053,13 @@ calcHist_8u( vector<uchar*>& _ptrs, const vector<int>& _deltas,
}
else if( dims == 2 )
{
#ifdef HAVE_TBB
if( CalcHist2D_8uInvoker::isFit(hist, imsize) )
{
callCalcHist2D_8u(_ptrs, _deltas, imsize, hist, dims, _tab);
return;
}
#endif
int d0 = deltas[0], step0 = deltas[1],
d1 = deltas[2], step1 = deltas[3];
const uchar* p0 = (const uchar*)ptrs[0];
@@ -514,6 +1085,13 @@ calcHist_8u( vector<uchar*>& _ptrs, const vector<int>& _deltas,
}
else if( dims == 3 )
{
#ifdef HAVE_TBB
if( CalcHist3D_8uInvoker::isFit(hist, imsize) )
{
callCalcHist3D_8u(_ptrs, _deltas, imsize, hist, dims, _tab);
return;
}
#endif
int d0 = deltas[0], step0 = deltas[1],
d1 = deltas[2], step1 = deltas[3],
d2 = deltas[4], step2 = deltas[5];
@@ -2404,61 +2982,206 @@ cvCalcProbDensity( const CvHistogram* hist, const CvHistogram* hist_mask,
}
}
class EqualizeHistCalcHist_Invoker
{
public:
enum {HIST_SZ = 256};
#ifdef HAVE_TBB
typedef tbb::mutex* MutextPtr;
#else
typedef void* MutextPtr;
#endif
EqualizeHistCalcHist_Invoker(cv::Mat& src, int* histogram, MutextPtr histogramLock)
: src_(src), globalHistogram_(histogram), histogramLock_(histogramLock)
{ }
void operator()( const cv::BlockedRange& rowRange ) const
{
int localHistogram[HIST_SZ] = {0, };
const size_t sstep = src_.step;
int width = src_.cols;
int height = rowRange.end() - rowRange.begin();
if (src_.isContinuous())
{
width *= height;
height = 1;
}
for (const uchar* ptr = src_.ptr<uchar>(rowRange.begin()); height--; ptr += sstep)
{
int x = 0;
for (; x <= width - 4; x += 4)
{
int t0 = ptr[x], t1 = ptr[x+1];
localHistogram[t0]++; localHistogram[t1]++;
t0 = ptr[x+2]; t1 = ptr[x+3];
localHistogram[t0]++; localHistogram[t1]++;
}
for (; x < width; ++x, ++ptr)
localHistogram[ptr[x]]++;
}
#ifdef HAVE_TBB
tbb::mutex::scoped_lock lock(*histogramLock_);
#endif
for( int i = 0; i < HIST_SZ; i++ )
globalHistogram_[i] += localHistogram[i];
}
static bool isWorthParallel( const cv::Mat& src )
{
#ifdef HAVE_TBB
return ( src.total() >= 640*480 );
#else
(void)src;
return false;
#endif
}
private:
EqualizeHistCalcHist_Invoker& operator=(const EqualizeHistCalcHist_Invoker&);
cv::Mat& src_;
int* globalHistogram_;
MutextPtr histogramLock_;
};
class EqualizeHistLut_Invoker
{
public:
EqualizeHistLut_Invoker( cv::Mat& src, cv::Mat& dst, int* lut )
: src_(src),
dst_(dst),
lut_(lut)
{ }
void operator()( const cv::BlockedRange& rowRange ) const
{
const size_t sstep = src_.step;
const size_t dstep = dst_.step;
int width = src_.cols;
int height = rowRange.end() - rowRange.begin();
int* lut = lut_;
if (src_.isContinuous() && dst_.isContinuous())
{
width *= height;
height = 1;
}
const uchar* sptr = src_.ptr<uchar>(rowRange.begin());
uchar* dptr = dst_.ptr<uchar>(rowRange.begin());
for (; height--; sptr += sstep, dptr += dstep)
{
int x = 0;
for (; x <= width - 4; x += 4)
{
int v0 = sptr[x];
int v1 = sptr[x+1];
int x0 = lut[v0];
int x1 = lut[v1];
dptr[x] = (uchar)x0;
dptr[x+1] = (uchar)x1;
v0 = sptr[x+2];
v1 = sptr[x+3];
x0 = lut[v0];
x1 = lut[v1];
dptr[x+2] = (uchar)x0;
dptr[x+3] = (uchar)x1;
}
for (; x < width; ++x)
dptr[x] = (uchar)lut[sptr[x]];
}
}
static bool isWorthParallel( const cv::Mat& src )
{
#ifdef HAVE_TBB
return ( src.total() >= 640*480 );
#else
(void)src;
return false;
#endif
}
private:
EqualizeHistLut_Invoker& operator=(const EqualizeHistLut_Invoker&);
cv::Mat& src_;
cv::Mat& dst_;
int* lut_;
};
CV_IMPL void cvEqualizeHist( const CvArr* srcarr, CvArr* dstarr )
{
CvMat sstub, *src = cvGetMat(srcarr, &sstub);
CvMat dstub, *dst = cvGetMat(dstarr, &dstub);
CV_Assert( CV_ARE_SIZES_EQ(src, dst) && CV_ARE_TYPES_EQ(src, dst) &&
CV_MAT_TYPE(src->type) == CV_8UC1 );
CvSize size = cvGetMatSize(src);
if( CV_IS_MAT_CONT(src->type & dst->type) )
{
size.width *= size.height;
size.height = 1;
cv::equalizeHist(cv::cvarrToMat(srcarr), cv::cvarrToMat(dstarr));
}
int x, y;
const int hist_sz = 256;
int hist[hist_sz];
memset(hist, 0, sizeof(hist));
for( y = 0; y < size.height; y++ )
{
const uchar* sptr = src->data.ptr + src->step*y;
for( x = 0; x < size.width; x++ )
hist[sptr[x]]++;
}
float scale = 255.f/(size.width*size.height);
int sum = 0;
uchar lut[hist_sz+1];
for( int i = 0; i < hist_sz; i++ )
{
sum += hist[i];
int val = cvRound(sum*scale);
lut[i] = CV_CAST_8U(val);
}
lut[0] = 0;
for( y = 0; y < size.height; y++ )
{
const uchar* sptr = src->data.ptr + src->step*y;
uchar* dptr = dst->data.ptr + dst->step*y;
for( x = 0; x < size.width; x++ )
dptr[x] = lut[sptr[x]];
}
}
void cv::equalizeHist( InputArray _src, OutputArray _dst )
{
Mat src = _src.getMat();
CV_Assert( src.type() == CV_8UC1 );
_dst.create( src.size(), src.type() );
Mat dst = _dst.getMat();
CvMat _csrc = src, _cdst = dst;
cvEqualizeHist( &_csrc, &_cdst );
if(src.empty())
return;
#ifdef HAVE_TBB
tbb::mutex histogramLockInstance;
EqualizeHistCalcHist_Invoker::MutextPtr histogramLock = &histogramLockInstance;
#else
EqualizeHistCalcHist_Invoker::MutextPtr histogramLock = 0;
#endif
const int hist_sz = EqualizeHistCalcHist_Invoker::HIST_SZ;
int hist[hist_sz] = {0,};
int lut[hist_sz];
EqualizeHistCalcHist_Invoker calcBody(src, hist, histogramLock);
EqualizeHistLut_Invoker lutBody(src, dst, lut);
cv::BlockedRange heightRange(0, src.rows);
if(EqualizeHistCalcHist_Invoker::isWorthParallel(src))
parallel_for(heightRange, calcBody);
else
calcBody(heightRange);
int i = 0;
while (!hist[i]) ++i;
int total = (int)src.total();
if (hist[i] == total)
{
dst.setTo(i);
return;
}
float scale = (hist_sz - 1.f)/(total - hist[i]);
int sum = 0;
for (lut[i++] = 0; i < hist_sz; ++i)
{
sum += hist[i];
lut[i] = saturate_cast<uchar>(sum * scale);
}
if(EqualizeHistLut_Invoker::isWorthParallel(src))
parallel_for(heightRange, lutBody);
else
lutBody(heightRange);
}
/* Implementation of RTTI and Generic Functions for CvHistogram */

215
modules/imgproc/src/imgwarp.cpp
View File

@@ -1241,16 +1241,206 @@ static void resizeGeneric_( const Mat& src, Mat& dst,
template <typename T, typename WT>
struct ResizeAreaFastNoVec
{
ResizeAreaFastNoVec(int /*_scale_x*/, int /*_scale_y*/,
int /*_cn*/, int /*_step*//*, const int**/ /*_ofs*/) { }
int operator() (const T* /*S*/, T* /*D*/, int /*w*/) const { return 0; }
ResizeAreaFastNoVec(int, int) { }
ResizeAreaFastNoVec(int, int, int, int) { }
int operator() (const T*, T*, int) const
{ return 0; }
};
template<typename T>
#if CV_SSE2
class ResizeAreaFastVec_SIMD_8u
{
public:
ResizeAreaFastVec_SIMD_8u(int _cn, int _step) :
cn(_cn), step(_step)
{
use_simd = checkHardwareSupport(CV_CPU_SSE2);
}
int operator() (const uchar* S, uchar* D, int w) const
{
if (!use_simd)
return 0;
int dx = 0;
const uchar* S0 = S;
const uchar* S1 = S0 + step;
__m128i zero = _mm_setzero_si128();
__m128i delta2 = _mm_set1_epi16(2);
if (cn == 1)
{
__m128i masklow = _mm_set1_epi16(0x00ff);
for ( ; dx < w - 8; dx += 8, S0 += 16, S1 += 16, D += 8)
{
__m128i r0 = _mm_loadu_si128((const __m128i*)S0);
__m128i r1 = _mm_loadu_si128((const __m128i*)S1);
__m128i s0 = _mm_add_epi16(_mm_srli_epi16(r0, 8), _mm_and_si128(r0, masklow));
__m128i s1 = _mm_add_epi16(_mm_srli_epi16(r1, 8), _mm_and_si128(r1, masklow));
s0 = _mm_add_epi16(_mm_add_epi16(s0, s1), delta2);
s0 = _mm_packus_epi16(_mm_srli_epi16(s0, 2), zero);
_mm_storel_epi64((__m128i*)D, s0);
}
}
else if (cn == 3)
for ( ; dx < w - 6; dx += 6, S0 += 12, S1 += 12, D += 6)
{
__m128i r0 = _mm_loadu_si128((const __m128i*)S0);
__m128i r1 = _mm_loadu_si128((const __m128i*)S1);
__m128i r0_16l = _mm_unpacklo_epi8(r0, zero);
__m128i r0_16h = _mm_unpacklo_epi8(_mm_srli_si128(r0, 6), zero);
__m128i r1_16l = _mm_unpacklo_epi8(r1, zero);
__m128i r1_16h = _mm_unpacklo_epi8(_mm_srli_si128(r1, 6), zero);
__m128i s0 = _mm_add_epi16(r0_16l, _mm_srli_si128(r0_16l, 6));
__m128i s1 = _mm_add_epi16(r1_16l, _mm_srli_si128(r1_16l, 6));
s0 = _mm_add_epi16(s1, _mm_add_epi16(s0, delta2));
s0 = _mm_packus_epi16(_mm_srli_epi16(s0, 2), zero);
_mm_storel_epi64((__m128i*)D, s0);
s0 = _mm_add_epi16(r0_16h, _mm_srli_si128(r0_16h, 6));
s1 = _mm_add_epi16(r1_16h, _mm_srli_si128(r1_16h, 6));
s0 = _mm_add_epi16(s1, _mm_add_epi16(s0, delta2));
s0 = _mm_packus_epi16(_mm_srli_epi16(s0, 2), zero);
_mm_storel_epi64((__m128i*)(D+3), s0);
}
else
{
CV_Assert(cn == 4);
for ( ; dx < w - 8; dx += 8, S0 += 16, S1 += 16, D += 8)
{
__m128i r0 = _mm_loadu_si128((const __m128i*)S0);
__m128i r1 = _mm_loadu_si128((const __m128i*)S1);
__m128i r0_16l = _mm_unpacklo_epi8(r0, zero);
__m128i r0_16h = _mm_unpackhi_epi8(r0, zero);
__m128i r1_16l = _mm_unpacklo_epi8(r1, zero);
__m128i r1_16h = _mm_unpackhi_epi8(r1, zero);
__m128i s0 = _mm_add_epi16(r0_16l, _mm_srli_si128(r0_16l, 8));
__m128i s1 = _mm_add_epi16(r1_16l, _mm_srli_si128(r1_16l, 8));
s0 = _mm_add_epi16(s1, _mm_add_epi16(s0, delta2));
s0 = _mm_packus_epi16(_mm_srli_epi16(s0, 2), zero);
_mm_storel_epi64((__m128i*)D, s0);
s0 = _mm_add_epi16(r0_16h, _mm_srli_si128(r0_16h, 8));
s1 = _mm_add_epi16(r1_16h, _mm_srli_si128(r1_16h, 8));
s0 = _mm_add_epi16(s1, _mm_add_epi16(s0, delta2));
s0 = _mm_packus_epi16(_mm_srli_epi16(s0, 2), zero);
_mm_storel_epi64((__m128i*)(D+4), s0);
}
}
return dx;
}
private:
int cn;
bool use_simd;
int step;
};
class ResizeAreaFastVec_SIMD_16u
{
public:
ResizeAreaFastVec_SIMD_16u(int _cn, int _step) :
cn(_cn), step(_step)
{
use_simd = checkHardwareSupport(CV_CPU_SSE2);
}
int operator() (const ushort* S, ushort* D, int w) const
{
if (!use_simd)
return 0;
int dx = 0;
const ushort* S0 = (const ushort*)S;
const ushort* S1 = (const ushort*)((const uchar*)(S) + step);
__m128i masklow = _mm_set1_epi32(0x0000ffff);
__m128i zero = _mm_setzero_si128();
__m128i delta2 = _mm_set1_epi32(2);
#define _mm_packus_epi32(a, zero) _mm_packs_epi32(_mm_srai_epi32(_mm_slli_epi32(a, 16), 16), zero)
if (cn == 1)
{
for ( ; dx < w - 4; dx += 4, S0 += 8, S1 += 8, D += 4)
{
__m128i r0 = _mm_loadu_si128((const __m128i*)S0);
__m128i r1 = _mm_loadu_si128((const __m128i*)S1);
__m128i s0 = _mm_add_epi32(_mm_srli_epi32(r0, 16), _mm_and_si128(r0, masklow));
__m128i s1 = _mm_add_epi32(_mm_srli_epi32(r1, 16), _mm_and_si128(r1, masklow));
s0 = _mm_add_epi32(_mm_add_epi32(s0, s1), delta2);
s0 = _mm_srli_epi32(s0, 2);
s0 = _mm_packus_epi32(s0, zero);
_mm_storel_epi64((__m128i*)D, s0);
}
}
else if (cn == 3)
for ( ; dx < w - 3; dx += 3, S0 += 6, S1 += 6, D += 3)
{
__m128i r0 = _mm_loadu_si128((const __m128i*)S0);
__m128i r1 = _mm_loadu_si128((const __m128i*)S1);
__m128i r0_16l = _mm_unpacklo_epi16(r0, zero);
__m128i r0_16h = _mm_unpacklo_epi16(_mm_srli_si128(r0, 6), zero);
__m128i r1_16l = _mm_unpacklo_epi16(r1, zero);
__m128i r1_16h = _mm_unpacklo_epi16(_mm_srli_si128(r1, 6), zero);
__m128i s0 = _mm_add_epi16(r0_16l, r0_16h);
__m128i s1 = _mm_add_epi16(r1_16l, r1_16h);
s0 = _mm_add_epi32(s1, _mm_add_epi32(s0, delta2));
s0 = _mm_packus_epi32(_mm_srli_epi32(s0, 2), zero);
_mm_storel_epi64((__m128i*)D, s0);
}
else
{
CV_Assert(cn == 4);
for ( ; dx < w - 4; dx += 4, S0 += 8, S1 += 8, D += 4)
{
__m128i r0 = _mm_loadu_si128((const __m128i*)S0);
__m128i r1 = _mm_loadu_si128((const __m128i*)S1);
__m128i r0_32l = _mm_unpacklo_epi16(r0, zero);
__m128i r0_32h = _mm_unpackhi_epi16(r0, zero);
__m128i r1_32l = _mm_unpacklo_epi16(r1, zero);
__m128i r1_32h = _mm_unpackhi_epi16(r1, zero);
__m128i s0 = _mm_add_epi32(r0_32l, r0_32h);
__m128i s1 = _mm_add_epi32(r1_32l, r1_32h);
s0 = _mm_add_epi32(s1, _mm_add_epi32(s0, delta2));
s0 = _mm_packus_epi32(_mm_srli_epi32(s0, 2), zero);
_mm_storel_epi64((__m128i*)D, s0);
}
}
#undef _mm_packus_epi32
return dx;
}
private:
int cn;
int step;
bool use_simd;
};
#else
typedef ResizeAreaFastNoVec<uchar, uchar> ResizeAreaFastVec_SIMD_8u;
typedef ResizeAreaFastNoVec<ushort, ushort> ResizeAreaFastVec_SIMD_16u;
#endif
template<typename T, typename SIMDVecOp>
struct ResizeAreaFastVec
{
ResizeAreaFastVec(int _scale_x, int _scale_y, int _cn, int _step/*, const int* _ofs*/) :
scale_x(_scale_x), scale_y(_scale_y), cn(_cn), step(_step)/*, ofs(_ofs)*/
ResizeAreaFastVec(int _scale_x, int _scale_y, int _cn, int _step) :
scale_x(_scale_x), scale_y(_scale_y), cn(_cn), step(_step), vecOp(_cn, _step)
{
fast_mode = scale_x == 2 && scale_y == 2 && (cn == 1 || cn == 3 || cn == 4);
}
@@ -1261,7 +1451,7 @@ struct ResizeAreaFastVec
return 0;
const T* nextS = (const T*)((const uchar*)S + step);
int dx = 0;
int dx = vecOp(S, D, w);
if (cn == 1)
for( ; dx < w; ++dx )
@@ -1279,7 +1469,7 @@ struct ResizeAreaFastVec
}
else
{
assert(cn == 4);
CV_Assert(cn == 4);
for( ; dx < w; dx += 4 )
{
int index = dx*2;
@@ -1298,6 +1488,7 @@ private:
int cn;
bool fast_mode;
int step;
SIMDVecOp vecOp;
};
template <typename T, typename WT, typename VecOp>
@@ -1702,10 +1893,10 @@ void cv::resize( InputArray _src, OutputArray _dst, Size dsize,
static ResizeAreaFastFunc areafast_tab[] =
{
resizeAreaFast_<uchar, int, ResizeAreaFastVec<uchar> >,
resizeAreaFast_<uchar, int, ResizeAreaFastVec<uchar, ResizeAreaFastVec_SIMD_8u> >,
0,
resizeAreaFast_<ushort, float, ResizeAreaFastVec<ushort> >,
resizeAreaFast_<short, float, ResizeAreaFastVec<short> >,
resizeAreaFast_<ushort, float, ResizeAreaFastVec<ushort, ResizeAreaFastVec_SIMD_16u> >,
resizeAreaFast_<short, float, ResizeAreaFastVec<short, ResizeAreaFastNoVec<short, float> > >,
0,
resizeAreaFast_<float, float, ResizeAreaFastNoVec<float, float> >,
resizeAreaFast_<double, double, ResizeAreaFastNoVec<double, double> >,
@@ -1764,9 +1955,7 @@ void cv::resize( InputArray _src, OutputArray _dst, Size dsize,
// in case of scale_x && scale_y is equal to 2
// INTER_AREA (fast) also is equal to INTER_LINEAR
if( interpolation == INTER_LINEAR && is_area_fast && iscale_x == 2 && iscale_y == 2 )
{
interpolation = INTER_AREA;
}
// true "area" interpolation is only implemented for the case (scale_x <= 1 && scale_y <= 1).
// In other cases it is emulated using some variant of bilinear interpolation

427
modules/imgproc/test/test_color.cpp
View File

@@ -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;
@@ -1731,91 +1733,94 @@ TEST(Imgproc_ColorBayerVNG, regression)
}
}
// creating Bayer pattern
template <typename T, int depth>
static void calculateBayerPattern(const Mat& src, Mat& bayer, const char* pattern)
{
Size ssize = src.size();
const int scn = 1;
bayer.create(ssize, CV_MAKETYPE(depth, scn));
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<T>(y, x) = static_cast<T>(src.at<Vec3b>(y, x)[1]);
else if (x % 2)
bayer.at<T>(y, x) = static_cast<T>(src.at<Vec3b>(y, x)[0]);
else
bayer.at<T>(y, x) = static_cast<T>(src.at<Vec3b>(y, x)[2]);
}
}
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<T>(y, x) = static_cast<T>(src.at<Vec3b>(y, x)[1]);
else if (x % 2 == 0)
bayer.at<T>(y, x) = static_cast<T>(src.at<Vec3b>(y, x)[0]);
else
bayer.at<T>(y, x) = static_cast<T>(src.at<Vec3b>(y, x)[2]);
}
}
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<T>(y, x) = static_cast<T>(src.at<Vec3b>(y, x)[1]);
else if (x % 2 == 0)
bayer.at<T>(y, x) = static_cast<T>(src.at<Vec3b>(y, x)[0]);
else
bayer.at<T>(y, x) = static_cast<T>(src.at<Vec3b>(y, x)[2]);
}
}
else
{
for (int y = 0; y < ssize.height; ++y)
for (int x = 0; x < ssize.width; ++x)
{
if ((x + y) % 2 == 0)
bayer.at<T>(y, x) = static_cast<T>(src.at<Vec3b>(y, x)[1]);
else if (x % 2)
bayer.at<T>(y, x) = static_cast<T>(src.at<Vec3b>(y, x)[0]);
else
bayer.at<T>(y, x) = static_cast<T>(src.at<Vec3b>(y, x)[2]);
}
}
}
TEST(Imgproc_ColorBayerVNG_Strict, regression)
{
cvtest::TS& ts = *cvtest::TS::ptr();
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/";
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();
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();
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"))
{
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];
else if (x % 2)
bayer.at<uchar>(y, x) = src.at<Vec3b>(y, x)[0];
else
bayer.at<uchar>(y, x) = src.at<Vec3b>(y, x)[2];
}
type = CV_BayerBG2BGR_VNG;
}
else if (!strcmp(pattern[i], "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];
else if (x % 2 == 0)
bayer.at<uchar>(y, x) = src.at<Vec3b>(y, x)[0];
else
bayer.at<uchar>(y, x) = src.at<Vec3b>(y, x)[2];
}
type = CV_BayerGB2BGR_VNG;
}
else if (!strcmp(pattern[i], "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];
else if (x % 2 == 0)
bayer.at<uchar>(y, x) = src.at<Vec3b>(y, x)[0];
else
bayer.at<uchar>(y, x) = src.at<Vec3b>(y, x)[2];
}
type = CV_BayerRG2BGR_VNG;
}
else
{
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];
else if (x % 2)
bayer.at<uchar>(y, x) = src.at<Vec3b>(y, x)[0];
else
bayer.at<uchar>(y, x) = src.at<Vec3b>(y, x)[2];
}
type = CV_BayerGR2BGR_VNG;
}
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);
// src *= 255.0f;
// recons *= 255.0f;
// imshow("Test", src);
// imshow("OpenCV", recons);
// waitKey();
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);
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);
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();
}
}
}
}

19
modules/java/generator/gen_javadoc.py
View File

@@ -3,6 +3,19 @@
import os, sys, re, string, glob
from optparse import OptionParser
# Black list for classes and methods that does not implemented in Java API
# Created to exclude referencies to them in @see tag
JAVADOC_ENTITY_BLACK_LIST = set(["org.opencv.core.Core#abs", \
"org.opencv.core.Core#theRNG", \
"org.opencv.core.Core#extractImageCOI", \
"org.opencv.core.PCA", \
"org.opencv.core.SVD", \
"org.opencv.core.RNG", \
"org.opencv.imgproc.Imgproc#createMorphologyFilter", \
"org.opencv.imgproc.Imgproc#createLinearFilter", \
"org.opencv.imgproc.Imgproc#createSeparableLinearFilter", \
"org.opencv.imgproc.FilterEngine"])
class JavadocGenerator(object):
def __init__(self, definitions = {}, modules= [], javadoc_marker = "//javadoc:"):
self.definitions = definitions
@@ -214,9 +227,9 @@ class JavadocGenerator(object):
for see in decl["seealso"]:
seedecl = self.definitions.get(see,None)
if seedecl:
doc += prefix + " * @see " + self.getJavaName(seedecl, "#") + "\n"
else:
doc += prefix + " * @see " + see.replace("::",".") + "\n"
javadoc_name = self.getJavaName(seedecl, "#")
if (javadoc_name not in JAVADOC_ENTITY_BLACK_LIST):
doc += prefix + " * @see " + javadoc_name + "\n"
prefix = " *\n"
#doc += prefix + " * File: " + decl["file"] + " (line " + str(decl["line"]) + ")\n"

2
modules/java/generator/src/java/android+CameraBridgeViewBase.java
View File

@@ -344,7 +344,7 @@ public abstract class CameraBridgeViewBase extends SurfaceView implements Surfac
* @param supportedSizes
* @param surfaceWidth
* @param surfaceHeight
* @return
* @return optimal frame size
*/
protected Size calculateCameraFrameSize(List<?> supportedSizes, ListItemAccessor accessor, int surfaceWidth, int surfaceHeight) {
int calcWidth = 0;

2
modules/java/generator/src/java/android+OpenCVLoader.java
View File

@@ -31,7 +31,7 @@ public class OpenCVLoader
* @param Version OpenCV library version.
* @param AppContext application context for connecting to the service.
* @param Callback object, that implements LoaderCallbackInterface for handling the connection status.
* @return Returns true if initialization of OpenCV is successful.
* @return Returns true if initialization of OpenCV is successful.
*/
public static boolean initAsync(String Version, Context AppContext,
LoaderCallbackInterface Callback)

4
modules/ml/test/test_save_load.cpp
View File

@@ -64,11 +64,11 @@ int CV_SLMLTest::run_test_case( int testCaseIdx )
if( code == cvtest::TS::OK )
{
get_error( testCaseIdx, CV_TEST_ERROR, &test_resps1 );
fname1 = tempfile();
fname1 = tempfile(".yml.gz");
save( fname1.c_str() );
load( fname1.c_str() );
get_error( testCaseIdx, CV_TEST_ERROR, &test_resps2 );
fname2 = tempfile();
fname2 = tempfile(".yml.gz");
save( fname2.c_str() );
}
else

4
modules/nonfree/perf/perf_surf.cpp
View File

@@ -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);
}

8
modules/objdetect/include/opencv2/objdetect/objdetect.hpp
View File

@@ -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);

6
modules/objdetect/perf/perf_cascadeclassifier.cpp
View File

@@ -14,11 +14,7 @@ PERF_TEST_P(ImageName_MinSize, CascadeClassifierLBPFrontalFace,
testing::Combine(testing::Values( std::string("cv/shared/lena.png"),
std::string("cv/shared/1_itseez-0000289.png"),
std::string("cv/shared/1_itseez-0000492.png"),
std::string("cv/shared/1_itseez-0000573.png"),
std::string("cv/shared/1_itseez-0000892.png"),
std::string("cv/shared/1_itseez-0001238.png"),
std::string("cv/shared/1_itseez-0001438.png"),
std::string("cv/shared/1_itseez-0002524.png")),
std::string("cv/shared/1_itseez-0000573.png")),
testing::Values(24, 30, 40, 50, 60, 70, 80, 90)
)
)

2
modules/objdetect/src/objdetect_init.cpp
View File

@@ -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)
{

57
modules/objdetect/src/softcascade.cpp
View File

@@ -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

24
modules/stitching/perf/perf_stich.cpp
View File

@@ -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);
}

2
modules/stitching/src/matchers.cpp
View File

@@ -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);

4
modules/ts/include/opencv2/ts/ts_gtest.h
View File

@@ -433,8 +433,8 @@
// Defines this to true iff Google Test can use POSIX regular expressions.
#ifndef GTEST_HAS_POSIX_RE
# if GTEST_OS_LINUX_ANDROID
// On Android, <regex.h> is only available starting with Gingerbread.
# define GTEST_HAS_POSIX_RE (__ANDROID_API__ >= 9)
// On Android, <regex.h> is only available starting with Froyo.
# define GTEST_HAS_POSIX_RE (__ANDROID_API__ >= 8)
# else
# define GTEST_HAS_POSIX_RE (!GTEST_OS_WINDOWS)
#endif

112
modules/ts/misc/run.py
View File

@@ -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)

1
modules/ts/src/ts_gtest.cpp
View File

@@ -1340,6 +1340,7 @@ GTEST_API_ bool IsAsciiWhiteSpace(char ch);
GTEST_API_ bool IsAsciiWordChar(char ch);
GTEST_API_ bool IsValidEscape(char ch);
GTEST_API_ bool AtomMatchesChar(bool escaped, char pattern, char ch);
GTEST_API_ std::string FormatRegexSyntaxError(const char* regex, int index);
GTEST_API_ bool ValidateRegex(const char* regex);
GTEST_API_ bool MatchRegexAtHead(const char* regex, const char* str);
GTEST_API_ bool MatchRepetitionAndRegexAtHead(

61
modules/ts/src/ts_perf.cpp
View File

@@ -20,7 +20,8 @@ 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}"
@@ -45,6 +46,7 @@ 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;
@@ -307,23 +309,25 @@ double Regression::getElem(cv::Mat& m, int y, int x, int cn)
void Regression::write(cv::Mat m)
{
if (!m.empty() && m.dims < 2) return;
double min, max;
cv::minMaxLoc(m, &min, &max);
cv::minMaxIdx(m, &min, &max);
write() << "min" << min << "max" << max;
write() << "last" << "{" << "x" << m.cols-1 << "y" << m.rows-1
<< "val" << getElem(m, m.rows-1, m.cols-1, m.channels()-1) << "}";
write() << "last" << "{" << "x" << m.size.p[1] - 1 << "y" << m.size.p[0] - 1
<< "val" << getElem(m, m.size.p[0] - 1, m.size.p[1] - 1, m.channels() - 1) << "}";
int x, y, cn;
x = regRNG.uniform(0, m.cols);
y = regRNG.uniform(0, m.rows);
x = regRNG.uniform(0, m.size.p[1]);
y = regRNG.uniform(0, m.size.p[0]);
cn = regRNG.uniform(0, m.channels());
write() << "rng1" << "{" << "x" << x << "y" << y;
if(cn > 0) write() << "cn" << cn;
write() << "val" << getElem(m, y, x, cn) << "}";
x = regRNG.uniform(0, m.cols);
y = regRNG.uniform(0, m.rows);
x = regRNG.uniform(0, m.size.p[1]);
y = regRNG.uniform(0, m.size.p[0]);
cn = regRNG.uniform(0, m.channels());
write() << "rng2" << "{" << "x" << x << "y" << y;
if (cn > 0) write() << "cn" << cn;
@@ -341,8 +345,10 @@ static double evalEps(double expected, double actual, double _eps, ERROR_TYPE er
void Regression::verify(cv::FileNode node, cv::Mat actual, double _eps, std::string argname, ERROR_TYPE err)
{
if (!actual.empty() && actual.dims < 2) return;
double actual_min, actual_max;
cv::minMaxLoc(actual, &actual_min, &actual_max);
cv::minMaxIdx(actual, &actual_min, &actual_max);
double expect_min = (double)node["min"];
double eps = evalEps(expect_min, actual_min, _eps, err);
@@ -355,12 +361,12 @@ void Regression::verify(cv::FileNode node, cv::Mat actual, double _eps, std::str
<< argname << " has unexpected maximal value" << std::endl;
cv::FileNode last = node["last"];
double actual_last = getElem(actual, actual.rows - 1, actual.cols - 1, actual.channels() - 1);
double actual_last = getElem(actual, actual.size.p[0] - 1, actual.size.p[1] - 1, actual.channels() - 1);
int expect_cols = (int)last["x"] + 1;
int expect_rows = (int)last["y"] + 1;
ASSERT_EQ(expect_cols, actual.cols)
ASSERT_EQ(expect_cols, actual.size.p[1])
<< argname << " has unexpected number of columns" << std::endl;
ASSERT_EQ(expect_rows, actual.rows)
ASSERT_EQ(expect_rows, actual.size.p[0])
<< argname << " has unexpected number of rows" << std::endl;
double expect_last = (double)last["val"];
@@ -374,6 +380,8 @@ void Regression::verify(cv::FileNode node, cv::Mat actual, double _eps, std::str
int cn1 = rng1["cn"];
double expect_rng1 = (double)rng1["val"];
// it is safe to use x1 and y1 without checks here because we have already
// verified that mat size is the same as recorded
double actual_rng1 = getElem(actual, y1, x1, cn1);
eps = evalEps(expect_rng1, actual_rng1, _eps, err);
@@ -492,10 +500,10 @@ void Regression::verify(cv::FileNode node, cv::InputArray array, double eps, ERR
std::cout << " Expected: " << std::endl << expected << std::endl << " Actual:" << std::endl << actual << std::endl;
double max;
cv::minMaxLoc(diff.reshape(1), 0, &max);
cv::minMaxIdx(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)
@@ -505,7 +513,7 @@ 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";
}
}
}
@@ -546,10 +554,10 @@ void Regression::verify(cv::FileNode node, cv::InputArray array, double eps, ERR
std::cout << " Expected: " << std::endl << expected << std::endl << " Actual:" << std::endl << actual << std::endl;
double max;
cv::minMaxLoc(diff.reshape(1), 0, &max);
cv::minMaxIdx(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)
@@ -559,7 +567,7 @@ 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";
}
}
}
@@ -599,10 +607,15 @@ 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
{
@@ -660,6 +673,7 @@ 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");
@@ -974,7 +988,7 @@ 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))
@@ -1153,12 +1167,17 @@ void TestBase::RunPerfTestBody()
if (e.code == CV_GpuApiCallError)
cv::gpu::resetDevice();
#endif
FAIL() << "Expected: PerfTestBody() doesn't throw an exception.\n Actual: it throws:\n " << e.what();
FAIL() << "Expected: PerfTestBody() doesn't throw an exception.\n Actual: it throws cv::Exception:\n " << e.what();
}
catch(std::exception e)
{
metrics.terminationReason = performance_metrics::TERM_EXCEPTION;
FAIL() << "Expected: PerfTestBody() doesn't throw an exception.\n Actual: it throws std::exception:\n " << e.what();
}
catch(...)
{
metrics.terminationReason = performance_metrics::TERM_EXCEPTION;
FAIL() << "Expected: PerfTestBody() doesn't throw an exception.\n Actual: it throws.";
FAIL() << "Expected: PerfTestBody() doesn't throw an exception.\n Actual: it throws...";
}
}

2
modules/video/perf/perf_tvl1optflow.cpp
View File

@@ -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);
}

2
modules/video/test/test_backgroundsubtractor_gbh.cpp
View File

@@ -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");
/**

39
modules/video/test/test_tvl1optflow.cpp
View File

@@ -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 = 0.02;
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
}

60
samples/android/tutorial-5-cameracontrol/src/org/opencv/samples/tutorial5/Sample5CameraControl.java
View File

@@ -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;
@@ -9,23 +11,31 @@ 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.hardware.Camera.Size;
import android.os.Bundle;
import android.os.Environment;
import android.util.Log;
import android.view.Menu;
import android.view.MenuItem;
import android.view.MotionEvent;
import android.view.SubMenu;
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";
private SampleJavaCameraView mOpenCvCameraView;
private List<Size> mResolutionList;
private MenuItem[] mEffectMenuItems;
private SubMenu mColorEffectsMenu;
private MenuItem[] mResolutionMenuItems;
private SubMenu mResolutionMenu;
private BaseLoaderCallback mLoaderCallback = new BaseLoaderCallback(this) {
@Override
@@ -100,28 +110,68 @@ 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;
}
mColorEffectsMenu = menu.addSubMenu("Color Effect");
mEffectMenuItems = new MenuItem[effects.size()];
int idx = 0;
ListIterator<String> itr = effects.listIterator();
while(itr.hasNext()) {
String element = itr.next();
mEffectMenuItems[idx] = menu.add(element);
ListIterator<String> effectItr = effects.listIterator();
while(effectItr.hasNext()) {
String element = effectItr.next();
mEffectMenuItems[idx] = mColorEffectsMenu.add(1, idx, Menu.NONE, element);
idx++;
}
mResolutionMenu = menu.addSubMenu("Resolution");
mResolutionList = mOpenCvCameraView.getResolutionList();
mResolutionMenuItems = new MenuItem[mResolutionList.size()];
ListIterator<Size> resolutionItr = mResolutionList.listIterator();
idx = 0;
while(resolutionItr.hasNext()) {
Size element = resolutionItr.next();
mResolutionMenuItems[idx] = mResolutionMenu.add(2, idx, Menu.NONE,
Integer.valueOf(element.width).toString() + "x" + Integer.valueOf(element.height).toString());
idx++;
}
return true;
}
public boolean onOptionsItemSelected(MenuItem item) {
Log.i(TAG, "called onOptionsItemSelected; selected item: " + item);
if (item.getGroupId() == 1)
{
mOpenCvCameraView.setEffect((String) item.getTitle());
Toast.makeText(this, mOpenCvCameraView.getEffect(), Toast.LENGTH_SHORT).show();
}
else if (item.getGroupId() == 2)
{
int id = item.getItemId();
Size resolution = mResolutionList.get(id);
mOpenCvCameraView.setResolution(resolution);
resolution = mOpenCvCameraView.getResolution();
String caption = Integer.valueOf(resolution.width).toString() + "x" + Integer.valueOf(resolution.height).toString();
Toast.makeText(this, caption, 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;
}
}

21
samples/android/tutorial-5-cameracontrol/src/org/opencv/samples/tutorial5/SampleJavaCameraView.java
View File

@@ -10,6 +10,7 @@ import android.graphics.Bitmap;
import android.graphics.BitmapFactory;
import android.hardware.Camera;
import android.hardware.Camera.PictureCallback;
import android.hardware.Camera.Size;
import android.util.AttributeSet;
import android.util.Log;
@@ -25,6 +26,10 @@ public class SampleJavaCameraView extends JavaCameraView {
return mCamera.getParameters().getSupportedColorEffects();
}
public boolean isEffectSupported() {
return (mCamera.getParameters().getColorEffect() != null);
}
public String getEffect() {
return mCamera.getParameters().getColorEffect();
}
@@ -35,6 +40,21 @@ public class SampleJavaCameraView extends JavaCameraView {
mCamera.setParameters(params);
}
public List<Size> getResolutionList() {
return mCamera.getParameters().getSupportedPreviewSizes();
}
public void setResolution(Size resolution) {
disconnectCamera();
mMaxHeight = resolution.height;
mMaxWidth = resolution.width;
connectCamera(getWidth(), getHeight());
}
public Size getResolution() {
return mCamera.getParameters().getPreviewSize();
}
public void takePicture(final String fileName) {
Log.i(TAG, "Tacking picture");
PictureCallback callback = new PictureCallback() {
@@ -48,6 +68,7 @@ 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();

6
samples/cpp/detector_descriptor_evaluation.cpp
View File

@@ -535,7 +535,7 @@ void DetectorQualityEvaluator::readAlgorithm ()
{
defaultDetector = FeatureDetector::create( algName );
specificDetector = FeatureDetector::create( algName );
if( defaultDetector == 0 )
if( defaultDetector.empty() )
{
printf( "Algorithm can not be read\n" );
exit(-1);
@@ -769,14 +769,14 @@ void DescriptorQualityEvaluator::readAlgorithm( )
defaultDescMatcher = GenericDescriptorMatcher::create( algName );
specificDescMatcher = GenericDescriptorMatcher::create( algName );
if( defaultDescMatcher == 0 )
if( defaultDescMatcher.empty() )
{
Ptr<DescriptorExtractor> extractor = DescriptorExtractor::create( algName );
Ptr<DescriptorMatcher> matcher = DescriptorMatcher::create( matcherName );
defaultDescMatcher = new VectorDescriptorMatch( extractor, matcher );
specificDescMatcher = new VectorDescriptorMatch( extractor, matcher );
if( extractor == 0 || matcher == 0 )
if( extractor.empty() || matcher.empty() )
{
printf("Algorithm can not be read\n");
exit(-1);

2
samples/cpp/generic_descriptor_match.cpp
View File

@@ -32,7 +32,7 @@ int main(int argc, char** argv)
std::string params_filename = std::string(argv[4]);
Ptr<GenericDescriptorMatcher> descriptorMatcher = GenericDescriptorMatcher::create(alg_name, params_filename);
if( descriptorMatcher == 0 )
if( descriptorMatcher.empty() )
{
printf ("Cannot create descriptor\n");
return 0;

2
samples/ocl/CMakeLists.txt
View File

@@ -55,7 +55,7 @@ if(BUILD_EXAMPLES AND OCV_DEPENDENCIES_FOUND)
endforeach()
endif()
if (NOT WIN32)
if (INSTALL_C_EXAMPLES AND NOT WIN32)
file(GLOB install_list *.c *.cpp *.jpg *.png *.data makefile.* build_all.sh *.dsp *.cmd )
install(FILES ${install_list}
DESTINATION share/opencv/samples/${project}