зеркало из https://github.com/microsoft/opencv.git
Fix Windows build issues
* No /arch:SSE3 in MSVC * Warnings fixed or suppressed
This commit is contained in:
Родитель
793e8b546d
Коммит
f2a02feffa
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@ -89,7 +89,7 @@ endif(WIN32)
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ocv_warnings_disable(CMAKE_C_FLAGS -Wno-unused-but-set-variable -Wmissing-prototypes -Wmissing-declarations -Wundef -Wunused -Wsign-compare
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-Wcast-align -Wshadow -Wno-maybe-uninitialized -Wno-pointer-to-int-cast -Wno-int-to-pointer-cast)
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ocv_warnings_disable(CMAKE_CXX_FLAGS -Wmissing-declarations -Wunused-parameter /wd4100 /wd4244 /wd4706 /wd4127 /wd4701 /wd4018 /wd4267 /wd4306 /wd4305 /wd4312 /wd4311)
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ocv_warnings_disable(CMAKE_CXX_FLAGS -Wmissing-declarations -Wunused-parameter /wd4100 /wd4244 /wd4706 /wd4127 /wd4701 /wd4018 /wd4267 /wd4306 /wd4305 /wd4312 /wd4311 /wd4703)
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if(UNIX AND (CMAKE_COMPILER_IS_GNUCXX OR CV_ICC))
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set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -fPIC")
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@ -189,11 +189,11 @@ OCV_OPTION(ENABLE_PROFILING "Enable profiling in the GCC compiler (Add
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OCV_OPTION(ENABLE_OMIT_FRAME_POINTER "Enable -fomit-frame-pointer for GCC" ON IF CMAKE_COMPILER_IS_GNUCXX )
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OCV_OPTION(ENABLE_POWERPC "Enable PowerPC for GCC" ON IF (CMAKE_COMPILER_IS_GNUCXX AND CMAKE_SYSTEM_PROCESSOR MATCHES powerpc.*) )
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OCV_OPTION(ENABLE_FAST_MATH "Enable -ffast-math (not recommended for GCC 4.6.x)" OFF IF (CMAKE_COMPILER_IS_GNUCXX AND (X86 OR X86_64)) )
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OCV_OPTION(ENABLE_SSE "Enable SSE instructions" ON IF (MSVC OR CMAKE_COMPILER_IS_GNUCXX AND (X86 OR X86_64)) )
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OCV_OPTION(ENABLE_SSE2 "Enable SSE2 instructions" ON IF (MSVC OR CMAKE_COMPILER_IS_GNUCXX AND (X86 OR X86_64)) )
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OCV_OPTION(ENABLE_SSE3 "Enable SSE3 instructions" ON IF (MSVC OR CV_ICC OR CMAKE_COMPILER_IS_GNUCXX AND (X86 OR X86_64)) )
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OCV_OPTION(ENABLE_SSE "Enable SSE instructions" ON IF ((MSVC OR CMAKE_COMPILER_IS_GNUCXX) AND (X86 OR X86_64)) )
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OCV_OPTION(ENABLE_SSE2 "Enable SSE2 instructions" ON IF ((MSVC OR CMAKE_COMPILER_IS_GNUCXX) AND (X86 OR X86_64)) )
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OCV_OPTION(ENABLE_SSE3 "Enable SSE3 instructions" ON IF ((CV_ICC OR CMAKE_COMPILER_IS_GNUCXX) AND (X86 OR X86_64)) )
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OCV_OPTION(ENABLE_SSSE3 "Enable SSSE3 instructions" OFF IF (CMAKE_COMPILER_IS_GNUCXX AND (X86 OR X86_64)) )
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OCV_OPTION(ENABLE_SSE41 "Enable SSE4.1 instructions" OFF IF (CV_ICC OR CMAKE_COMPILER_IS_GNUCXX AND (X86 OR X86_64)) )
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OCV_OPTION(ENABLE_SSE41 "Enable SSE4.1 instructions" OFF IF ((CV_ICC OR CMAKE_COMPILER_IS_GNUCXX) AND (X86 OR X86_64)) )
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OCV_OPTION(ENABLE_SSE42 "Enable SSE4.2 instructions" OFF IF (CMAKE_COMPILER_IS_GNUCXX AND (X86 OR X86_64)) )
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OCV_OPTION(ENABLE_NOISY_WARNINGS "Show all warnings even if they are too noisy" OFF )
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OCV_OPTION(OPENCV_WARNINGS_ARE_ERRORS "Treat warnings as errors" OFF )
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@ -59,7 +59,7 @@ CV_INIT_ALGORITHM(BriefDescriptorExtractor, "Feature2D.BRIEF",
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CV_INIT_ALGORITHM(FastFeatureDetector, "Feature2D.FAST",
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obj.info()->addParam(obj, "threshold", obj.threshold);
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obj.info()->addParam(obj, "nonmaxSuppression", obj.nonmaxSuppression);
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obj.info()->addParam(obj, "type", obj.type, static_cast<int>(FastFeatureDetector::TYPE_9_16)));
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obj.info()->addParam(obj, "type", obj.type));
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///////////////////////////////////////////////////////////////////////////////////////////////////////////
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@ -75,8 +75,8 @@ void CV_FastTest::run( int )
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vector<KeyPoint> keypoints1;
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vector<KeyPoint> keypoints2;
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FAST(gray1, keypoints1, 30, type);
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FAST(gray2, keypoints2, 30, type);
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FAST(gray1, keypoints1, 30, true, type);
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FAST(gray2, keypoints2, 30, true, type);
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for(size_t i = 0; i < keypoints1.size(); ++i)
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{
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@ -200,7 +200,7 @@ int CV_KDTreeTest_CPP::checkGetPoins( const Mat& data )
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int CV_KDTreeTest_CPP::checkFindBoxed()
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{
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vector<float> min( dims, minValue), max(dims, maxValue);
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vector<float> min( dims, static_cast<float>(minValue)), max(dims, static_cast<float>(maxValue));
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vector<int> indices;
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tr->findOrthoRange( min, max, indices );
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// TODO check indices
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@ -214,8 +214,8 @@ int CV_KDTreeTest_CPP::findNeighbors( Mat& points, Mat& neighbors )
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const int emax = 20;
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Mat neighbors2( neighbors.size(), CV_32SC1 );
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int j;
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vector<float> min(points.cols, minValue);
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vector<float> max(points.cols, maxValue);
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vector<float> min(points.cols, static_cast<float>(minValue));
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vector<float> max(points.cols, static_cast<float>(maxValue));
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for( int pi = 0; pi < points.rows; pi++ )
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{
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// 1st way
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@ -54,7 +54,7 @@ static
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Mat generateHomography(float angle)
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{
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// angle - rotation around Oz in degrees
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float angleRadian = angle * CV_PI / 180.;
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float angleRadian = static_cast<float>(angle * CV_PI / 180);
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Mat H = Mat::eye(3, 3, CV_32FC1);
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H.at<float>(0,0) = H.at<float>(1,1) = std::cos(angleRadian);
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H.at<float>(0,1) = -std::sin(angleRadian);
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@ -69,8 +69,8 @@ Mat rotateImage(const Mat& srcImage, float angle, Mat& dstImage, Mat& dstMask)
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// angle - rotation around Oz in degrees
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float diag = std::sqrt(static_cast<float>(srcImage.cols * srcImage.cols + srcImage.rows * srcImage.rows));
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Mat LUShift = Mat::eye(3, 3, CV_32FC1); // left up
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LUShift.at<float>(0,2) = -srcImage.cols/2;
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LUShift.at<float>(1,2) = -srcImage.rows/2;
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LUShift.at<float>(0,2) = static_cast<float>(-srcImage.cols/2);
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LUShift.at<float>(1,2) = static_cast<float>(-srcImage.rows/2);
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Mat RDShift = Mat::eye(3, 3, CV_32FC1); // right down
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RDShift.at<float>(0,2) = diag/2;
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RDShift.at<float>(1,2) = diag/2;
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@ -114,7 +114,7 @@ void scaleKeyPoints(const vector<KeyPoint>& src, vector<KeyPoint>& dst, float sc
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static
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float calcCirclesIntersectArea(const Point2f& p0, float r0, const Point2f& p1, float r1)
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{
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float c = norm(p0 - p1), sqr_c = c * c;
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float c = static_cast<float>(norm(p0 - p1)), sqr_c = c * c;
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float sqr_r0 = r0 * r0;
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float sqr_r1 = r1 * r1;
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@ -125,7 +125,7 @@ float calcCirclesIntersectArea(const Point2f& p0, float r0, const Point2f& p1, f
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float minR = std::min(r0, r1);
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float maxR = std::max(r0, r1);
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if(c + minR <= maxR)
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return CV_PI * minR * minR;
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return static_cast<float>(CV_PI * minR * minR);
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float cos_halfA0 = (sqr_r0 + sqr_c - sqr_r1) / (2 * r0 * c);
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float cos_halfA1 = (sqr_r1 + sqr_c - sqr_r0) / (2 * r1 * c);
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@ -133,15 +133,15 @@ float calcCirclesIntersectArea(const Point2f& p0, float r0, const Point2f& p1, f
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float A0 = 2 * acos(cos_halfA0);
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float A1 = 2 * acos(cos_halfA1);
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return 0.5 * sqr_r0 * (A0 - sin(A0)) +
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0.5 * sqr_r1 * (A1 - sin(A1));
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return 0.5f * sqr_r0 * (A0 - sin(A0)) +
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0.5f * sqr_r1 * (A1 - sin(A1));
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}
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static
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float calcIntersectRatio(const Point2f& p0, float r0, const Point2f& p1, float r1)
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{
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float intersectArea = calcCirclesIntersectArea(p0, r0, p1, r1);
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float unionArea = CV_PI * (r0 * r0 + r1 * r1) - intersectArea;
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float unionArea = static_cast<float>(CV_PI) * (r0 * r0 + r1 * r1) - intersectArea;
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return intersectArea / unionArea;
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}
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@ -160,7 +160,7 @@ void matchKeyPoints(const vector<KeyPoint>& keypoints0, const Mat& H,
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matches.clear();
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vector<uchar> usedMask(keypoints1.size(), 0);
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for(size_t i0 = 0; i0 < keypoints0.size(); i0++)
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for(int i0 = 0; i0 < static_cast<int>(keypoints0.size()); i0++)
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{
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int nearestPointIndex = -1;
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float maxIntersectRatio = 0.f;
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@ -176,7 +176,7 @@ void matchKeyPoints(const vector<KeyPoint>& keypoints0, const Mat& H,
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if(intersectRatio > maxIntersectRatio)
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{
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maxIntersectRatio = intersectRatio;
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nearestPointIndex = i1;
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nearestPointIndex = static_cast<int>(i1);
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}
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}
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@ -222,7 +222,7 @@ protected:
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const int maxAngle = 360, angleStep = 15;
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for(int angle = 0; angle < maxAngle; angle += angleStep)
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{
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Mat H = rotateImage(image0, angle, image1, mask1);
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Mat H = rotateImage(image0, static_cast<float>(angle), image1, mask1);
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vector<KeyPoint> keypoints1;
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featureDetector->detect(image1, keypoints1, mask1);
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@ -339,10 +339,10 @@ protected:
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const int maxAngle = 360, angleStep = 15;
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for(int angle = 0; angle < maxAngle; angle += angleStep)
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{
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Mat H = rotateImage(image0, angle, image1, mask1);
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Mat H = rotateImage(image0, static_cast<float>(angle), image1, mask1);
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vector<KeyPoint> keypoints1;
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rotateKeyPoints(keypoints0, H, angle, keypoints1);
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rotateKeyPoints(keypoints0, H, static_cast<float>(angle), keypoints1);
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Mat descriptors1;
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descriptorExtractor->compute(image1, keypoints1, descriptors1);
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@ -457,7 +457,7 @@ protected:
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keyPointMatchesCount++;
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// Check does this inlier have consistent sizes
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const float maxSizeDiff = 0.8;//0.9f; // grad
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const float maxSizeDiff = 0.8f;//0.9f; // grad
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float size0 = keypoints0[matches[m].trainIdx].size;
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float size1 = osiKeypoints1[matches[m].queryIdx].size;
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CV_Assert(size0 > 0 && size1 > 0);
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@ -545,7 +545,7 @@ protected:
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resize(image0, image1, Size(), 1./scale, 1./scale);
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vector<KeyPoint> keypoints1;
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scaleKeyPoints(keypoints0, keypoints1, 1./scale);
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scaleKeyPoints(keypoints0, keypoints1, 1.0f/scale);
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Mat descriptors1;
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descriptorExtractor->compute(image1, keypoints1, descriptors1);
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@ -23,8 +23,8 @@ void generateMap(cv::Mat& map_x, cv::Mat& map_y, int remapMode)
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case HALF_SIZE:
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if (i > map_x.cols*0.25 && i < map_x.cols*0.75 && j > map_x.rows*0.25 && j < map_x.rows*0.75)
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{
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map_x.at<float>(j,i) = 2 * (i - map_x.cols * 0.25) + 0.5;
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map_y.at<float>(j,i) = 2 * (j - map_x.rows * 0.25) + 0.5;
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map_x.at<float>(j,i) = 2 * (i - map_x.cols * 0.25f) + 0.5f;
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map_y.at<float>(j,i) = 2 * (j - map_x.rows * 0.25f) + 0.5f;
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}
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else
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{
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@ -33,16 +33,16 @@ void generateMap(cv::Mat& map_x, cv::Mat& map_y, int remapMode)
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}
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break;
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case UPSIDE_DOWN:
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map_x.at<float>(j,i) = i;
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map_y.at<float>(j,i) = map_x.rows - j;
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map_x.at<float>(j,i) = static_cast<float>(i);
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map_y.at<float>(j,i) = static_cast<float>(map_x.rows - j);
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break;
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case REFLECTION_X:
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map_x.at<float>(j,i) = map_x.cols - i;
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map_y.at<float>(j,i) = j;
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map_x.at<float>(j,i) = static_cast<float>(map_x.cols - i);
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map_y.at<float>(j,i) = static_cast<float>(j);
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break;
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case REFLECTION_BOTH:
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map_x.at<float>(j,i) = map_x.cols - i;
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map_y.at<float>(j,i) = map_x.rows - j;
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map_x.at<float>(j,i) = static_cast<float>(map_x.cols - i);
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map_y.at<float>(j,i) = static_cast<float>(map_x.rows - j);
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break;
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} // end of switch
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}
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@ -1619,7 +1619,7 @@ PERF_TEST_P(Sz_DoSort, ImgProc_HoughLines, Combine(GPU_TYPICAL_MAT_SIZES, Bool()
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const bool doSort = GET_PARAM(1);
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const float rho = 1.0f;
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const float theta = CV_PI / 180.0f;
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const float theta = static_cast<float>(CV_PI / 180.0);
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const int threshold = 300;
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cv::RNG rng(123456789);
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@ -31,6 +31,11 @@ struct GreedyLabeling
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int d = a - b;
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return lo <= d && d <= hi;
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}
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private:
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InInterval& operator=(const InInterval&);
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};
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GreedyLabeling(cv::Mat img)
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@ -45,7 +50,7 @@ struct GreedyLabeling
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int cc = -1;
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int* dist_labels = (int*)labels.data;
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int pitch = labels.step1();
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int pitch = static_cast<int>(labels.step1());
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unsigned char* source = (unsigned char*)image.data;
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int width = image.cols;
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@ -82,7 +87,7 @@ struct GreedyLabeling
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*top++ = dot::make(p.x, p.y + 1);
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//top
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if( p.y > 0 && dl[-pitch] == -1 && inInt(sp[0], sp[-image.step1()]))
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if( p.y > 0 && dl[-pitch] == -1 && inInt(sp[0], sp[-static_cast<int>(image.step1())]))
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*top++ = dot::make(p.x, p.y - 1);
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p = *--top;
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@ -427,7 +427,7 @@ PERF_TEST_P(Video_Cn_LearningRate, Video_MOG, Combine(Values("gpu/video/768x576.
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{
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string inputFile = perf::TestBase::getDataPath(GET_PARAM(0));
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int cn = GET_PARAM(1);
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double learningRate = GET_PARAM(2);
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float learningRate = static_cast<float>(GET_PARAM(2));
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cv::VideoCapture cap(inputFile);
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ASSERT_TRUE(cap.isOpened());
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@ -7,6 +7,7 @@
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#include <fstream>
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#include <iostream>
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#include <memory>
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#include <functional>
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#if defined WIN32 || defined _WIN32
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#define WIN32_LEAN_AND_MEAN
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@ -86,7 +86,7 @@ int main(int argc, const char** argv)
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break;
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case MOG:
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mog(d_frame, d_fgmask, 0.01);
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mog(d_frame, d_fgmask, 0.01f);
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break;
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case MOG2:
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@ -127,7 +127,7 @@ int main(int argc, const char** argv)
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break;
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case MOG:
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mog(d_frame, d_fgmask, 0.01);
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mog(d_frame, d_fgmask, 0.01f);
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mog.getBackgroundImage(d_bgimg);
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break;
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@ -162,7 +162,7 @@ int main(int argc, const char** argv)
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if (!bgimg.empty())
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imshow("mean background image", bgimg);
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char key = waitKey(30);
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int key = waitKey(30);
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if (key == 27)
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break;
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}
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@ -1341,7 +1341,7 @@ TEST(MOG)
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cv::gpu::MOG_GPU d_mog;
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cv::gpu::GpuMat d_foreground;
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d_mog(d_frame, d_foreground, 0.01);
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d_mog(d_frame, d_foreground, 0.01f);
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while (!TestSystem::instance().stop())
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{
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@ -1350,7 +1350,7 @@ TEST(MOG)
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TestSystem::instance().gpuOn();
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d_mog(d_frame, d_foreground, 0.01);
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d_mog(d_frame, d_foreground, 0.01f);
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TestSystem::instance().gpuOff();
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}
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