Merge branch '2.4'

modules/gpu/test/test_core.cpp

@@ -2918,10 +2918,12 @@ PARAM_TEST_CASE(Norm, cv::gpu::DeviceInfo, cv::Size, MatDepth, NormCode, UseRoi)
 GPU_TEST_P(Norm, Accuracy)
 {
     cv::Mat src = randomMat(size, depth);
+    cv::Mat mask = randomMat(size, CV_8UC1, 0, 2);
 
-    double val = cv::gpu::norm(loadMat(src, useRoi), normCode);
+    cv::gpu::GpuMat d_buf;
+    double val = cv::gpu::norm(loadMat(src, useRoi), normCode, loadMat(mask, useRoi), d_buf);
 
-    double val_gold = cv::norm(src, normCode);
+    double val_gold = cv::norm(src, normCode, mask);
 
     EXPECT_NEAR(val_gold, val, depth < CV_32F ? 0.0 : 1.0);
 }
@@ -3538,4 +3540,70 @@ INSTANTIATE_TEST_CASE_P(GPU_Core, Reduce, testing::Combine(
     ALL_REDUCE_CODES,
     WHOLE_SUBMAT));
 
+//////////////////////////////////////////////////////////////////////////////
+// Normalize
+
+PARAM_TEST_CASE(Normalize, cv::gpu::DeviceInfo, cv::Size, MatDepth, NormCode, UseRoi)
+{
+    cv::gpu::DeviceInfo devInfo;
+    cv::Size size;
+    int type;
+    int norm_type;
+    bool useRoi;
+
+    double alpha;
+    double beta;
+
+    virtual void SetUp()
+    {
+        devInfo = GET_PARAM(0);
+        size = GET_PARAM(1);
+        type = GET_PARAM(2);
+        norm_type = GET_PARAM(3);
+        useRoi = GET_PARAM(4);
+
+        cv::gpu::setDevice(devInfo.deviceID());
+
+        alpha = 1;
+        beta = 0;
+    }
+
+};
+
+GPU_TEST_P(Normalize, WithOutMask)
+{
+    cv::Mat src = randomMat(size, type);
+
+    cv::gpu::GpuMat dst = createMat(size, type, useRoi);
+    cv::gpu::normalize(loadMat(src, useRoi), dst, alpha, beta, norm_type, type);
+
+    cv::Mat dst_gold;
+    cv::normalize(src, dst_gold, alpha, beta, norm_type, type);
+
+    EXPECT_MAT_NEAR(dst_gold, dst, 1e-6);
+}
+
+GPU_TEST_P(Normalize, WithMask)
+{
+    cv::Mat src = randomMat(size, type);
+    cv::Mat mask = randomMat(size, CV_8UC1, 0, 2);
+
+    cv::gpu::GpuMat dst = createMat(size, type, useRoi);
+    dst.setTo(cv::Scalar::all(0));
+    cv::gpu::normalize(loadMat(src, useRoi), dst, alpha, beta, norm_type, type, loadMat(mask, useRoi));
+
+    cv::Mat dst_gold(size, type);
+    dst_gold.setTo(cv::Scalar::all(0));
+    cv::normalize(src, dst_gold, alpha, beta, norm_type, type, mask);
+
+    EXPECT_MAT_NEAR(dst_gold, dst, 1e-6);
+}
+
+INSTANTIATE_TEST_CASE_P(GPU_Core, Normalize, testing::Combine(
+    ALL_DEVICES,
+    DIFFERENT_SIZES,
+    ALL_DEPTH,
+    testing::Values(NormCode(cv::NORM_L1), NormCode(cv::NORM_L2), NormCode(cv::NORM_INF), NormCode(cv::NORM_MINMAX)),
+    WHOLE_SUBMAT));
+
 #endif // HAVE_CUDA

modules/gpu/test/test_optflow.cpp

@@ -431,9 +431,9 @@ GPU_TEST_P(OpticalFlowDual_TVL1, Accuracy)
     cv::gpu::GpuMat d_flowy = createMat(frame0.size(), CV_32FC1, useRoi);
     d_alg(loadMat(frame0, useRoi), loadMat(frame1, useRoi), d_flowx, d_flowy);
 
-    cv::OpticalFlowDual_TVL1 alg;
+    cv::Ptr<cv::DenseOpticalFlow> alg = cv::createOptFlow_DualTVL1();
     cv::Mat flow;
-    alg(frame0, frame1, flow);
+    alg->calc(frame0, frame1, flow);
     cv::Mat gold[2];
     cv::split(flow, gold);
 

modules/gpu/test/test_stream.cpp

@@ -0,0 +1,130 @@
+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
+//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+//
+//  By downloading, copying, installing or using the software you agree to this license.
+//  If you do not agree to this license, do not download, install,
+//  copy or use the software.
+//
+//
+//                           License Agreement
+//                For Open Source Computer Vision Library
+//
+// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
+// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+//
+// Redistribution and use in source and binary forms, with or without modification,
+// are permitted provided that the following conditions are met:
+//
+//   * Redistribution's of source code must retain the above copyright notice,
+//     this list of conditions and the following disclaimer.
+//
+//   * Redistribution's in binary form must reproduce the above copyright notice,
+//     this list of conditions and the following disclaimer in the documentation
+//     and/or other GpuMaterials provided with the distribution.
+//
+//   * The name of the copyright holders may not be used to endorse or promote products
+//     derived from this software without specific prior written permission.
+//
+// This software is provided by the copyright holders and contributors "as is" and
+// any express or bpied warranties, including, but not limited to, the bpied
+// warranties of merchantability and fitness for a particular purpose are disclaimed.
+// In no event shall the Intel Corporation or contributors be liable for any direct,
+// indirect, incidental, special, exemplary, or consequential damages
+// (including, but not limited to, procurement of substitute goods or services;
+// loss of use, data, or profits; or business interruption) however caused
+// and on any theory of liability, whether in contract, strict liability,
+// or tort (including negligence or otherwise) arising in any way out of
+// the use of this software, even if advised of the possibility of such damage.
+//
+//M*/
+
+#include "test_precomp.hpp"
+
+#ifdef HAVE_CUDA
+
+#if CUDA_VERSION >= 5000
+
+struct Async : testing::TestWithParam<cv::gpu::DeviceInfo>
+{
+    cv::gpu::CudaMem src;
+    cv::gpu::GpuMat d_src;
+
+    cv::gpu::CudaMem dst;
+    cv::gpu::GpuMat d_dst;
+
+    virtual void SetUp()
+    {
+        cv::gpu::DeviceInfo devInfo = GetParam();
+        cv::gpu::setDevice(devInfo.deviceID());
+
+        cv::Mat m = randomMat(cv::Size(128, 128), CV_8UC1);
+        src.create(m.size(), m.type(), cv::gpu::CudaMem::ALLOC_PAGE_LOCKED);
+        m.copyTo(src.createMatHeader());
+    }
+};
+
+void checkMemSet(cv::gpu::Stream&, int status, void* userData)
+{
+    ASSERT_EQ(cudaSuccess, status);
+
+    Async* test = reinterpret_cast<Async*>(userData);
+
+    cv::Mat src = test->src;
+    cv::Mat dst = test->dst;
+
+    cv::Mat dst_gold = cv::Mat::zeros(src.size(), src.type());
+
+    ASSERT_MAT_NEAR(dst_gold, dst, 0);
+}
+
+GPU_TEST_P(Async, MemSet)
+{
+    cv::gpu::Stream stream;
+
+    d_dst.upload(src);
+
+    stream.enqueueMemSet(d_dst, cv::Scalar::all(0));
+    stream.enqueueDownload(d_dst, dst);
+
+    Async* test = this;
+    stream.enqueueHostCallback(checkMemSet, test);
+
+    stream.waitForCompletion();
+}
+
+void checkConvert(cv::gpu::Stream&, int status, void* userData)
+{
+    ASSERT_EQ(cudaSuccess, status);
+
+    Async* test = reinterpret_cast<Async*>(userData);
+
+    cv::Mat src = test->src;
+    cv::Mat dst = test->dst;
+
+    cv::Mat dst_gold;
+    src.convertTo(dst_gold, CV_32S);
+
+    ASSERT_MAT_NEAR(dst_gold, dst, 0);
+}
+
+GPU_TEST_P(Async, Convert)
+{
+    cv::gpu::Stream stream;
+
+    stream.enqueueUpload(src, d_src);
+    stream.enqueueConvert(d_src, d_dst, CV_32S);
+    stream.enqueueDownload(d_dst, dst);
+
+    Async* test = this;
+    stream.enqueueHostCallback(checkConvert, test);
+
+    stream.waitForCompletion();
+}
+
+INSTANTIATE_TEST_CASE_P(GPU_Stream, Async, ALL_DEVICES);
+
+#endif
+
+#endif // HAVE_CUDA