Merge remote-tracking branch 'upstream/3.4' into merge-3.4

modules/core/src/lda.cpp

@@ -903,19 +903,19 @@ public:
     // given in src. This function is a port of the EigenvalueSolver in JAMA,
     // which has been released to public domain by The MathWorks and the
     // National Institute of Standards and Technology (NIST).
-    EigenvalueDecomposition(InputArray src, bool fallbackSymmetric = true) :
+    EigenvalueDecomposition() :
         n(0),
         d(NULL), e(NULL), ort(NULL),
         V(NULL), H(NULL)
     {
-        compute(src, fallbackSymmetric);
+        // nothing
     }
 
     // This function computes the Eigenvalue Decomposition for a general matrix
     // given in src. This function is a port of the EigenvalueSolver in JAMA,
     // which has been released to public domain by The MathWorks and the
     // National Institute of Standards and Technology (NIST).
-    void compute(InputArray src, bool fallbackSymmetric)
+    void compute(InputArray src, bool fallbackSymmetric = true)
     {
         CV_INSTRUMENT_REGION();
 
@@ -970,7 +970,8 @@ void eigenNonSymmetric(InputArray _src, OutputArray _evals, OutputArray _evects)
     else
         src64f = src;
 
-    EigenvalueDecomposition eigensystem(src64f, false);
+    EigenvalueDecomposition eigensystem;
+    eigensystem.compute(src64f, false);
 
     // EigenvalueDecomposition returns transposed and non-sorted eigenvalues
     std::vector<double> eigenvalues64f;
@@ -1146,7 +1147,8 @@ void LDA::lda(InputArrayOfArrays _src, InputArray _lbls) {
     // M = inv(Sw)*Sb
     Mat M;
     gemm(Swi, Sb, 1.0, Mat(), 0.0, M);
-    EigenvalueDecomposition es(M);
+    EigenvalueDecomposition es;
+    es.compute(M);
     _eigenvalues = es.eigenvalues();
     _eigenvectors = es.eigenvectors();
     // reshape eigenvalues, so they are stored by column

modules/core/src/system.cpp

@@ -94,7 +94,7 @@ void* allocSingletonBuffer(size_t size) { return fastMalloc(size); }
 #include <cstdlib>        // std::abort
 #endif
 
-#if defined __ANDROID__ || defined __linux__ || defined __FreeBSD__ || defined __HAIKU__ || defined __Fuchsia__
+#if defined __ANDROID__ || defined __linux__ || defined __FreeBSD__ || defined __OpenBSD__ || defined __HAIKU__ || defined __Fuchsia__
 #  include <unistd.h>
 #  include <fcntl.h>
 #  include <elf.h>

modules/dnn/CMakeLists.txt

@@ -94,7 +94,7 @@ set(perf_path "${CMAKE_CURRENT_LIST_DIR}/perf")
 file(GLOB_RECURSE perf_srcs "${perf_path}/*.cpp")
 file(GLOB_RECURSE perf_hdrs "${perf_path}/*.hpp" "${perf_path}/*.h")
 ocv_add_perf_tests(${INF_ENGINE_TARGET}
-    FILES test_common "${CMAKE_CURRENT_LIST_DIR}/test/test_common.cpp"
+    FILES test_common "${CMAKE_CURRENT_LIST_DIR}/test/test_common.hpp" "${CMAKE_CURRENT_LIST_DIR}/test/test_common.impl.hpp"
     FILES Src ${perf_srcs}
     FILES Include ${perf_hdrs}
 )

modules/dnn/perf/perf_common.cpp

+// This file is part of OpenCV project.
+// It is subject to the license terms in the LICENSE file found in the top-level directory
+// of this distribution and at http://opencv.org/license.html.
+
+#include "perf_precomp.hpp"
+#include "../test/test_common.impl.hpp"  // shared with accuracy tests

modules/dnn/test/test_ie_models.cpp

@@ -177,34 +177,17 @@ TEST_P(DNNTestOpenVINO, models)
 {
     Target target = (dnn::Target)(int)get<0>(GetParam());
     std::string modelName = get<1>(GetParam());
+    std::string precision = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? "FP16" : "FP32";
 
 #ifdef INF_ENGINE_RELEASE
-#if INF_ENGINE_RELEASE <= 2018030000
-    if (target == DNN_TARGET_MYRIAD && (modelName == "landmarks-regression-retail-0001" ||
-                                        modelName == "semantic-segmentation-adas-0001" ||
-                                        modelName == "face-reidentification-retail-0001"))
-        throw SkipTestException("");
-#elif INF_ENGINE_RELEASE == 2018040000
-    if (modelName == "single-image-super-resolution-0034" ||
-        (target == DNN_TARGET_MYRIAD && (modelName == "license-plate-recognition-barrier-0001" ||
-                                         modelName == "landmarks-regression-retail-0009" ||
-                                          modelName == "semantic-segmentation-adas-0001")))
-        throw SkipTestException("");
-#elif INF_ENGINE_RELEASE == 2018050000
-    if (modelName == "single-image-super-resolution-0063" ||
-        modelName == "single-image-super-resolution-1011" ||
-        modelName == "single-image-super-resolution-1021" ||
-        (target == DNN_TARGET_OPENCL_FP16 && modelName == "face-reidentification-retail-0095") ||
-        (target == DNN_TARGET_MYRIAD && (modelName == "license-plate-recognition-barrier-0001" ||
-                                         modelName == "semantic-segmentation-adas-0001")))
-        throw SkipTestException("");
-#endif
-#endif
-
-    std::string precision = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? "FP16" : "FP32";
+#if INF_ENGINE_RELEASE <= 2018050000
     std::string prefix = utils::fs::join("intel_models",
                          utils::fs::join(modelName,
                          utils::fs::join(precision, modelName)));
+#endif
+#endif
+
+    initDLDTDataPath();
     std::string xmlPath = findDataFile(prefix + ".xml");
     std::string binPath = findDataFile(prefix + ".bin");
 
@@ -221,49 +204,21 @@ TEST_P(DNNTestOpenVINO, models)
     {
         auto dstIt = cvOutputsMap.find(srcIt.first);
         CV_Assert(dstIt != cvOutputsMap.end());
-        double normInfIE = cvtest::norm(srcIt.second, cv::NORM_INF);
         double normInf = cvtest::norm(srcIt.second, dstIt->second, cv::NORM_INF);
-        double eps = 0;
-        if (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD)
-        {
-            double fp16_eps = 1.0/1024;
-            eps = fp16_eps * 1/*ULP*/ * std::max(normInfIE, 1.0);
-        }
-        EXPECT_LE(normInf, eps) << "IE: " << normInfIE;
-    }
-}
-
-static testing::internal::ParamGenerator<String> intelModels()
-{
-    initDLDTDataPath();
-    std::vector<String> modelsNames;
-
-    std::string path;
-    try
-    {
-        path = findDataDirectory("intel_models", false);
-    }
-    catch (...)
-    {
-        std::cerr << "ERROR: Can't find OpenVINO models. Check INTEL_CVSDK_DIR environment variable (run setup.sh)" << std::endl;
-        return ValuesIn(modelsNames);  // empty list
+        EXPECT_EQ(normInf, 0);
     }
-
-    cv::utils::fs::glob_relative(path, "", modelsNames, false, true);
-
-    modelsNames.erase(
-        std::remove_if(modelsNames.begin(), modelsNames.end(),
-                       [&](const String& dir){ return !utils::fs::isDirectory(utils::fs::join(path, dir)); }),
-        modelsNames.end()
-    );
-    CV_Assert(!modelsNames.empty());
-
-    return ValuesIn(modelsNames);
 }
 
 INSTANTIATE_TEST_CASE_P(/**/,
     DNNTestOpenVINO,
-    Combine(testing::ValuesIn(getAvailableTargets(DNN_BACKEND_INFERENCE_ENGINE)), intelModels())
+    Combine(testing::ValuesIn(getAvailableTargets(DNN_BACKEND_INFERENCE_ENGINE)),
+            testing::Values(
+              "age-gender-recognition-retail-0013",
+              "face-person-detection-retail-0002",
+              "head-pose-estimation-adas-0001",
+              "person-detection-retail-0002",
+              "vehicle-detection-adas-0002"
+            ))
 );
 
 }}

modules/imgcodecs/src/bitstrm.cpp

@@ -175,8 +175,11 @@ void  RBaseStream::setPos( int pos )
     }
 
     int offset = pos % m_block_size;
+    int old_block_pos = m_block_pos;
     m_block_pos = pos - offset;
     m_current = m_start + offset;
+    if (old_block_pos != m_block_pos)
+        readBlock();
 }