mirror of
https://github.com/opencv/opencv.git
synced 2026-07-30 15:53:03 +04:00
fixed some warnings under win64
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@@ -124,8 +124,8 @@ private:
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bool initMemory(NCVTestReport &report)
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{
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this->allocatorGPU.reset(new NCVMemStackAllocator(devProp.textureAlignment));
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this->allocatorCPU.reset(new NCVMemStackAllocator(devProp.textureAlignment));
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this->allocatorGPU.reset(new NCVMemStackAllocator(static_cast<Ncv32u>(devProp.textureAlignment)));
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this->allocatorCPU.reset(new NCVMemStackAllocator(static_cast<Ncv32u>(devProp.textureAlignment)));
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if (!this->allocatorGPU.get()->isInitialized() ||
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!this->allocatorCPU.get()->isInitialized())
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@@ -146,9 +146,9 @@ private:
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report.statsNums["MemGPU"] = maxGPUsize;
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report.statsNums["MemCPU"] = maxCPUsize;
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this->allocatorGPU.reset(new NCVMemStackAllocator(NCVMemoryTypeDevice, maxGPUsize, devProp.textureAlignment));
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this->allocatorGPU.reset(new NCVMemStackAllocator(NCVMemoryTypeDevice, maxGPUsize, static_cast<Ncv32u>(devProp.textureAlignment)));
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this->allocatorCPU.reset(new NCVMemStackAllocator(NCVMemoryTypeHostPinned, maxCPUsize, devProp.textureAlignment));
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this->allocatorCPU.reset(new NCVMemStackAllocator(NCVMemoryTypeHostPinned, maxCPUsize, static_cast<Ncv32u>(devProp.textureAlignment)));
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if (!this->allocatorGPU.get()->isInitialized() ||
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!this->allocatorCPU.get()->isInitialized())
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@@ -35,7 +35,7 @@ public:
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//Ncv32u maxWpitch = alignUp(maxWidth * sizeof(T), devProp.textureAlignment);
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allocatorCPU.reset(new NCVMemNativeAllocator(NCVMemoryTypeHostPinned, devProp.textureAlignment));
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allocatorCPU.reset(new NCVMemNativeAllocator(NCVMemoryTypeHostPinned, static_cast<Ncv32u>(devProp.textureAlignment)));
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data.reset(new NCVMatrixAlloc<T>(*this->allocatorCPU.get(), maxWidth, maxHeight));
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ncvAssertPrintReturn(data.get()->isMemAllocated(), "NCVTestSourceProvider ctor:: Matrix not allocated", );
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@@ -70,7 +70,7 @@ public:
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ncvAssertPrintReturn(cudaSuccess == cudaGetDevice(&devId), "Error returned from cudaGetDevice", );
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ncvAssertPrintReturn(cudaSuccess == cudaGetDeviceProperties(&devProp, devId), "Error returned from cudaGetDeviceProperties", );
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allocatorCPU.reset(new NCVMemNativeAllocator(NCVMemoryTypeHostPinned, devProp.textureAlignment));
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allocatorCPU.reset(new NCVMemNativeAllocator(NCVMemoryTypeHostPinned, static_cast<Ncv32u>(devProp.textureAlignment)));
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data.reset(new NCVMatrixAlloc<T>(*this->allocatorCPU.get(), image.cols, image.rows));
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ncvAssertPrintReturn(data.get()->isMemAllocated(), "NCVTestSourceProvider ctor:: Matrix not allocated", );
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@@ -132,7 +132,7 @@ bool TestHypothesesFilter::process()
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}
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NCV_SKIP_COND_END
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Ncv32u numHypothesesSrc = h_vecSrc.length();
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Ncv32u numHypothesesSrc = static_cast<Ncv32u>(h_vecSrc.length());
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NCV_SKIP_COND_BEGIN
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ncvStat = ncvGroupRectangles_host(h_vecSrc, numHypothesesSrc, this->minNeighbors, this->eps, NULL);
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ncvAssertReturn(ncvStat == NCV_SUCCESS, false);
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@@ -1486,7 +1486,7 @@ struct BitwiseNot : testing::TestWithParam< std::tr1::tuple<cv::gpu::DeviceInfo,
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for (int i = 0; i < mat.rows; ++i)
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{
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cv::Mat row(1, mat.cols * mat.elemSize(), CV_8U, (void*)mat.ptr(i));
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cv::Mat row(1, static_cast<int>(mat.cols * mat.elemSize()), CV_8U, (void*)mat.ptr(i));
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rng.fill(row, cv::RNG::UNIFORM, cv::Scalar(0), cv::Scalar(255));
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}
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@@ -1547,10 +1547,10 @@ struct BitwiseOr : testing::TestWithParam< std::tr1::tuple<cv::gpu::DeviceInfo,
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for (int i = 0; i < mat1.rows; ++i)
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{
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cv::Mat row1(1, mat1.cols * mat1.elemSize(), CV_8U, (void*)mat1.ptr(i));
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cv::Mat row1(1, static_cast<int>(mat1.cols * mat1.elemSize()), CV_8U, (void*)mat1.ptr(i));
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rng.fill(row1, cv::RNG::UNIFORM, cv::Scalar(0), cv::Scalar(255));
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cv::Mat row2(1, mat2.cols * mat2.elemSize(), CV_8U, (void*)mat2.ptr(i));
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cv::Mat row2(1, static_cast<int>(mat2.cols * mat2.elemSize()), CV_8U, (void*)mat2.ptr(i));
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rng.fill(row2, cv::RNG::UNIFORM, cv::Scalar(0), cv::Scalar(255));
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}
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@@ -1611,10 +1611,10 @@ struct BitwiseAnd : testing::TestWithParam< std::tr1::tuple<cv::gpu::DeviceInfo,
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for (int i = 0; i < mat1.rows; ++i)
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{
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cv::Mat row1(1, mat1.cols * mat1.elemSize(), CV_8U, (void*)mat1.ptr(i));
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cv::Mat row1(1, static_cast<int>(mat1.cols * mat1.elemSize()), CV_8U, (void*)mat1.ptr(i));
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rng.fill(row1, cv::RNG::UNIFORM, cv::Scalar(0), cv::Scalar(255));
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cv::Mat row2(1, mat2.cols * mat2.elemSize(), CV_8U, (void*)mat2.ptr(i));
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cv::Mat row2(1, static_cast<int>(mat2.cols * mat2.elemSize()), CV_8U, (void*)mat2.ptr(i));
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rng.fill(row2, cv::RNG::UNIFORM, cv::Scalar(0), cv::Scalar(255));
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}
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@@ -1675,10 +1675,10 @@ struct BitwiseXor : testing::TestWithParam< std::tr1::tuple<cv::gpu::DeviceInfo,
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for (int i = 0; i < mat1.rows; ++i)
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{
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cv::Mat row1(1, mat1.cols * mat1.elemSize(), CV_8U, (void*)mat1.ptr(i));
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cv::Mat row1(1, static_cast<int>(mat1.cols * mat1.elemSize()), CV_8U, (void*)mat1.ptr(i));
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rng.fill(row1, cv::RNG::UNIFORM, cv::Scalar(0), cv::Scalar(255));
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cv::Mat row2(1, mat2.cols * mat2.elemSize(), CV_8U, (void*)mat2.ptr(i));
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cv::Mat row2(1, static_cast<int>(mat2.cols * mat2.elemSize()), CV_8U, (void*)mat2.ptr(i));
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rng.fill(row2, cv::RNG::UNIFORM, cv::Scalar(0), cv::Scalar(255));
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}
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@@ -143,7 +143,7 @@ TEST_P(SURF, Accuracy)
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cv::BruteForceMatcher< cv::L2<float> > matcher;
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std::vector<cv::DMatch> matches;
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matcher.match(cv::Mat(keypoints_gold.size(), 64, CV_32FC1, &descriptors_gold[0]), descriptors, matches);
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matcher.match(cv::Mat(static_cast<int>(keypoints_gold.size()), 64, CV_32FC1, &descriptors_gold[0]), descriptors, matches);
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int validCount = 0;
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