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

cmake/OpenCVCompilerOptimizations.cmake

@@ -5,13 +5,15 @@
 # AVX / AVX2 / AVX_512F
 # FMA3
 #
+# AVX512 details: https://en.wikipedia.org/wiki/AVX-512#CPUs_with_AVX-512
+#
 # CPU features groups:
 # AVX512_COMMON (Common instructions AVX-512F/CD for all CPUs that support AVX-512)
 # AVX512_KNL (Knights Landing with AVX-512F/CD/ER/PF)
 # AVX512_KNM (Knights Mill with AVX-512F/CD/ER/PF/4FMAPS/4VNNIW/VPOPCNTDQ)
 # AVX512_SKX (Skylake-X with AVX-512F/CD/BW/DQ/VL)
 # AVX512_CNL (Cannon Lake with AVX-512F/CD/BW/DQ/VL/IFMA/VBMI)
-# AVX512_CEL (Cascade Lake with AVX-512F/CD/BW/DQ/VL/IFMA/VBMI/VNNI)
+# AVX512_CLX (Cascade Lake with AVX-512F/CD/BW/DQ/VL/VNNI)
 # AVX512_ICL (Ice Lake with AVX-512F/CD/BW/DQ/VL/IFMA/VBMI/VNNI/VBMI2/BITALG/VPOPCNTDQ/VPCLMULQDQ*/GFNI*/VAES*)
 
 # ppc64le arch:
@@ -43,7 +45,7 @@
 # CPU_{opt}_ENABLED_DEFAULT=ON/OFF - has compiler support without additional flag (CPU_BASELINE_DETECT=ON only)
 
 set(CPU_ALL_OPTIMIZATIONS "SSE;SSE2;SSE3;SSSE3;SSE4_1;SSE4_2;POPCNT;AVX;FP16;AVX2;FMA3;AVX_512F")
-list(APPEND CPU_ALL_OPTIMIZATIONS "AVX512_COMMON;AVX512_KNL;AVX512_KNM;AVX512_SKX;AVX512_CNL;AVX512_CEL;AVX512_ICL")
+list(APPEND CPU_ALL_OPTIMIZATIONS "AVX512_COMMON;AVX512_KNL;AVX512_KNM;AVX512_SKX;AVX512_CNL;AVX512_CLX;AVX512_ICL")
 list(APPEND CPU_ALL_OPTIMIZATIONS NEON VFPV3 FP16)
 list(APPEND CPU_ALL_OPTIMIZATIONS MSA)
 list(APPEND CPU_ALL_OPTIMIZATIONS VSX VSX3)
@@ -163,15 +165,15 @@ elseif(" ${CMAKE_CXX_FLAGS} " MATCHES " -march=native | -xHost | /QxHost ")
 endif()
 
 if(X86 OR X86_64)
-  ocv_update(CPU_KNOWN_OPTIMIZATIONS "SSE;SSE2;SSE3;SSSE3;SSE4_1;POPCNT;SSE4_2;FP16;FMA3;AVX;AVX2;AVX_512F;AVX512_COMMON;AVX512_KNL;AVX512_KNM;AVX512_SKX;AVX512_CNL;AVX512_CEL;AVX512_ICL")
+  ocv_update(CPU_KNOWN_OPTIMIZATIONS "SSE;SSE2;SSE3;SSSE3;SSE4_1;POPCNT;SSE4_2;FP16;FMA3;AVX;AVX2;AVX_512F;AVX512_COMMON;AVX512_KNL;AVX512_KNM;AVX512_SKX;AVX512_CNL;AVX512_CLX;AVX512_ICL")
 
   ocv_update(CPU_AVX512_COMMON_GROUP "AVX_512F;AVX_512CD")
   ocv_update(CPU_AVX512_KNL_GROUP "AVX512_COMMON;AVX512_KNL_EXTRA")
   ocv_update(CPU_AVX512_KNM_GROUP "AVX512_KNL;AVX512_KNM_EXTRA;AVX_512VPOPCNTDQ")
   ocv_update(CPU_AVX512_SKX_GROUP "AVX512_COMMON;AVX_512VL;AVX_512BW;AVX_512DQ")
   ocv_update(CPU_AVX512_CNL_GROUP "AVX512_SKX;AVX_512IFMA;AVX_512VBMI")
-  ocv_update(CPU_AVX512_CEL_GROUP "AVX512_CNL;AVX_512VNNI")
+  ocv_update(CPU_AVX512_CLX_GROUP "AVX512_SKX;AVX_512VNNI")
-  ocv_update(CPU_AVX512_ICL_GROUP "AVX512_CEL;AVX_512VBMI2;AVX_512BITALG;AVX_512VPOPCNTDQ") # ? VPCLMULQDQ, GFNI, VAES
+  ocv_update(CPU_AVX512_ICL_GROUP "AVX512_SKX;AVX_512IFMA;AVX_512VBMI;AVX_512VNNI;AVX_512VBMI2;AVX_512BITALG;AVX_512VPOPCNTDQ") # ? VPCLMULQDQ, GFNI, VAES
 
   ocv_update(CPU_SSE_TEST_FILE "${OpenCV_SOURCE_DIR}/cmake/checks/cpu_sse.cpp")
   ocv_update(CPU_SSE2_TEST_FILE "${OpenCV_SOURCE_DIR}/cmake/checks/cpu_sse2.cpp")
@@ -189,12 +191,12 @@ if(X86 OR X86_64)
   ocv_update(CPU_AVX512_KNM_TEST_FILE "${OpenCV_SOURCE_DIR}/cmake/checks/cpu_avx512knm.cpp")
   ocv_update(CPU_AVX512_SKX_TEST_FILE "${OpenCV_SOURCE_DIR}/cmake/checks/cpu_avx512skx.cpp")
   ocv_update(CPU_AVX512_CNL_TEST_FILE "${OpenCV_SOURCE_DIR}/cmake/checks/cpu_avx512cnl.cpp")
-  ocv_update(CPU_AVX512_CEL_TEST_FILE "${OpenCV_SOURCE_DIR}/cmake/checks/cpu_avx512cel.cpp")
+  ocv_update(CPU_AVX512_CLX_TEST_FILE "${OpenCV_SOURCE_DIR}/cmake/checks/cpu_avx512clx.cpp")
   ocv_update(CPU_AVX512_ICL_TEST_FILE "${OpenCV_SOURCE_DIR}/cmake/checks/cpu_avx512icl.cpp")
 
   if(NOT OPENCV_CPU_OPT_IMPLIES_IGNORE)
-    ocv_update(CPU_AVX512_ICL_IMPLIES "AVX512_CEL")
+    ocv_update(CPU_AVX512_ICL_IMPLIES "AVX512_SKX")
-    ocv_update(CPU_AVX512_CEL_IMPLIES "AVX512_CNL")
+    ocv_update(CPU_AVX512_CLX_IMPLIES "AVX512_SKX")
     ocv_update(CPU_AVX512_CNL_IMPLIES "AVX512_SKX")
     ocv_update(CPU_AVX512_SKX_IMPLIES "AVX512_COMMON")
     ocv_update(CPU_AVX512_KNM_IMPLIES "AVX512_KNL")
@@ -251,7 +253,7 @@ if(X86 OR X86_64)
     ocv_intel_compiler_optimization_option(AVX512_KNM "-xKNM" "/Qx:KNM")
     ocv_intel_compiler_optimization_option(AVX512_SKX "-xSKYLAKE-AVX512" "/Qx:SKYLAKE-AVX512")
     ocv_intel_compiler_optimization_option(AVX512_CNL "-xCANNONLAKE" "/Qx:CANNONLAKE")
-    ocv_intel_compiler_optimization_option(AVX512_CEL "-xCASCADELAKE" "/Qx:CASCADELAKE")
+    ocv_intel_compiler_optimization_option(AVX512_CLX "-xCASCADELAKE" "/Qx:CASCADELAKE")
     ocv_intel_compiler_optimization_option(AVX512_ICL "-xICELAKE-CLIENT" "/Qx:ICELAKE-CLIENT")
   elseif(CV_GCC OR CV_CLANG)
     ocv_update(CPU_AVX2_FLAGS_ON "-mavx2")

cmake/OpenCVDetectInferenceEngine.cmake

@@ -80,9 +80,9 @@ endif()
 
 if(INF_ENGINE_TARGET)
   if(NOT INF_ENGINE_RELEASE)
-    message(WARNING "InferenceEngine version have not been set, 2019R2 will be used by default. Set INF_ENGINE_RELEASE variable if you experience build errors.")
+    message(WARNING "InferenceEngine version have not been set, 2019R3 will be used by default. Set INF_ENGINE_RELEASE variable if you experience build errors.")
   endif()
-  set(INF_ENGINE_RELEASE "2019020000" CACHE STRING "Force IE version, should be in form YYYYAABBCC (e.g. 2018R2.0.2 -> 2018020002)")
+  set(INF_ENGINE_RELEASE "2019030000" CACHE STRING "Force IE version, should be in form YYYYAABBCC (e.g. 2018R2.0.2 -> 2018020002)")
   set_target_properties(${INF_ENGINE_TARGET} PROPERTIES
     INTERFACE_COMPILE_DEFINITIONS "HAVE_INF_ENGINE=1;INF_ENGINE_RELEASE=${INF_ENGINE_RELEASE}"
   )

cmake/checks/cpu_avx512clx.cpp

@@ -3,9 +3,9 @@
 void test()
 {
     __m512i a, b, c;
-    a = _mm512_dpwssd_epi32(a, b, c);
+    a = _mm512_dpwssd_epi32(a, b, c);            // VNNI
 }
 #else
-#error "AVX512-CEL is not supported"
+#error "AVX512-CLX is not supported"
 #endif
 int main() { return 0; }

cmake/checks/cpu_avx512icl.cpp

@@ -3,9 +3,10 @@
 void test()
 {
     __m512i a, b, c;
-    a = _mm512_popcnt_epi8(a);
+    a = _mm512_popcnt_epi8(a);                   // BITALG
-    a = _mm512_shrdv_epi64(a, b, c);
+    a = _mm512_shrdv_epi64(a, b, c);             // VBMI2
-    a = _mm512_popcnt_epi64(a);
+    a = _mm512_popcnt_epi64(a);                  // VPOPCNTDQ
+    a = _mm512_dpwssd_epi32(a, b, c);            // VNNI
 }
 #else
 #error "AVX512-ICL is not supported"

doc/py_tutorials/py_setup/py_setup_in_ubuntu/py_setup_in_ubuntu.markdown

@@ -5,7 +5,7 @@ Goals
 -----
 
 In this tutorial We will learn to setup OpenCV-Python in Ubuntu System.
-Below steps are tested for Ubuntu 16.04 (64-bit) and Ubuntu 14.04 (32-bit).
+Below steps are tested for Ubuntu 16.04 and 18.04 (both 64-bit).
 
 OpenCV-Python can be installed in Ubuntu in two ways:
 - Install from pre-built binaries available in Ubuntu repositories
@@ -62,17 +62,36 @@ We need **CMake** to configure the installation, **GCC** for compilation, **Pyth
 
 ```
 sudo apt-get install cmake
-sudo apt-get install python-dev python-numpy
 sudo apt-get install gcc g++
 ```
+to support python2:
+
+```
+sudo apt-get install python-dev python-numpy
+```
+
+to support python3:
+
+```
+sudo apt-get install python3-dev python3-numpy
+```
 
 Next we need **GTK** support for GUI features, Camera support (v4l), Media Support
 (ffmpeg, gstreamer) etc.
 
 ```
-sudo apt-get install gtk2-devel
+sudo apt-get install libavcodec-dev libavformat-dev libswscale-dev
-sudo apt-get install ffmpeg-devel
+sudo apt-get install libgstreamer-plugins-base1.0-dev libgstreamer1.0-dev
-sudo apt-get install gstreamer-plugins-base-devel
+```
+
+to support gtk2:
+```
+sudo apt-get install libgtk2.0-dev
+```
+
+to support gtk3:
+```
+sudo apt-get install libgtk-3-dev
 ```
 
 ### Optional Dependencies
@@ -86,14 +105,15 @@ But it may be a little old.
 If you want to get latest libraries, you can install development files for system libraries of these formats.
 
 ```
-sudo apt-get install libpng-devel
+sudo apt-get install libpng-dev
-sudo apt-get install libjpeg-turbo-devel
+sudo apt-get install libjpeg-dev
-sudo apt-get install jasper-devel
+sudo apt-get install libopenexr-dev
-sudo apt-get install openexr-devel
+sudo apt-get install libtiff-dev
-sudo apt-get install libtiff-devel
+sudo apt-get install libwebp-dev
-sudo apt-get install libwebp-devel
 ```
 
+@note If you are using Ubuntu 16.04 you can also install ```libjasper-dev``` to add a system level support for the JPEG2000 format.
+
 ### Downloading OpenCV
 
 To download the latest source from OpenCV's [GitHub Repository](https://github.com/opencv/opencv).

modules/core/include/opencv2/core/cv_cpu_dispatch.h

@@ -113,12 +113,18 @@
 #  define CV_AVX_512IFMA 1
 #  define CV_AVX_512VBMI 1
 #endif
-#ifdef CV_CPU_COMPILE_AVX512_CEL
+#ifdef CV_CPU_COMPILE_AVX512_CLX
-#  define CV_AVX512_CEL 1
+#  define CV_AVX512_CLX 1
 #  define CV_AVX_512VNNI 1
 #endif
 #ifdef CV_CPU_COMPILE_AVX512_ICL
 #  define CV_AVX512_ICL 1
+#  undef CV_AVX_512IFMA
+#  define CV_AVX_512IFMA 1
+#  undef CV_AVX_512VBMI
+#  define CV_AVX_512VBMI 1
+#  undef CV_AVX_512VNNI
+#  define CV_AVX_512VNNI 1
 #  define CV_AVX_512VBMI2 1
 #  define CV_AVX_512BITALG 1
 #  define CV_AVX_512VPOPCNTDQ 1
@@ -311,8 +317,8 @@ struct VZeroUpperGuard {
 #ifndef CV_AVX512_CNL
 #  define CV_AVX512_CNL 0
 #endif
-#ifndef CV_AVX512_CEL
+#ifndef CV_AVX512_CLX
-#  define CV_AVX512_CEL 0
+#  define CV_AVX512_CLX 0
 #endif
 #ifndef CV_AVX512_ICL
 #  define CV_AVX512_ICL 0

modules/core/include/opencv2/core/cv_cpu_helper.h

@@ -357,26 +357,26 @@
 #endif
 #define __CV_CPU_DISPATCH_CHAIN_AVX512_CNL(fn, args, mode, ...)  CV_CPU_CALL_AVX512_CNL(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__))
 
-#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_AVX512_CEL
+#if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_AVX512_CLX
-#  define CV_TRY_AVX512_CEL 1
+#  define CV_TRY_AVX512_CLX 1
-#  define CV_CPU_FORCE_AVX512_CEL 1
+#  define CV_CPU_FORCE_AVX512_CLX 1
-#  define CV_CPU_HAS_SUPPORT_AVX512_CEL 1
+#  define CV_CPU_HAS_SUPPORT_AVX512_CLX 1
-#  define CV_CPU_CALL_AVX512_CEL(fn, args) return (cpu_baseline::fn args)
+#  define CV_CPU_CALL_AVX512_CLX(fn, args) return (cpu_baseline::fn args)
-#  define CV_CPU_CALL_AVX512_CEL_(fn, args) return (opt_AVX512_CEL::fn args)
+#  define CV_CPU_CALL_AVX512_CLX_(fn, args) return (opt_AVX512_CLX::fn args)
-#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_AVX512_CEL
+#elif !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_DISPATCH_COMPILE_AVX512_CLX
-#  define CV_TRY_AVX512_CEL 1
+#  define CV_TRY_AVX512_CLX 1
-#  define CV_CPU_FORCE_AVX512_CEL 0
+#  define CV_CPU_FORCE_AVX512_CLX 0
-#  define CV_CPU_HAS_SUPPORT_AVX512_CEL (cv::checkHardwareSupport(CV_CPU_AVX512_CEL))
+#  define CV_CPU_HAS_SUPPORT_AVX512_CLX (cv::checkHardwareSupport(CV_CPU_AVX512_CLX))
-#  define CV_CPU_CALL_AVX512_CEL(fn, args) if (CV_CPU_HAS_SUPPORT_AVX512_CEL) return (opt_AVX512_CEL::fn args)
+#  define CV_CPU_CALL_AVX512_CLX(fn, args) if (CV_CPU_HAS_SUPPORT_AVX512_CLX) return (opt_AVX512_CLX::fn args)
-#  define CV_CPU_CALL_AVX512_CEL_(fn, args) if (CV_CPU_HAS_SUPPORT_AVX512_CEL) return (opt_AVX512_CEL::fn args)
+#  define CV_CPU_CALL_AVX512_CLX_(fn, args) if (CV_CPU_HAS_SUPPORT_AVX512_CLX) return (opt_AVX512_CLX::fn args)
 #else
-#  define CV_TRY_AVX512_CEL 0
+#  define CV_TRY_AVX512_CLX 0
-#  define CV_CPU_FORCE_AVX512_CEL 0
+#  define CV_CPU_FORCE_AVX512_CLX 0
-#  define CV_CPU_HAS_SUPPORT_AVX512_CEL 0
+#  define CV_CPU_HAS_SUPPORT_AVX512_CLX 0
-#  define CV_CPU_CALL_AVX512_CEL(fn, args)
+#  define CV_CPU_CALL_AVX512_CLX(fn, args)
-#  define CV_CPU_CALL_AVX512_CEL_(fn, args)
+#  define CV_CPU_CALL_AVX512_CLX_(fn, args)
 #endif
-#define __CV_CPU_DISPATCH_CHAIN_AVX512_CEL(fn, args, mode, ...)  CV_CPU_CALL_AVX512_CEL(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__))
+#define __CV_CPU_DISPATCH_CHAIN_AVX512_CLX(fn, args, mode, ...)  CV_CPU_CALL_AVX512_CLX(fn, args); __CV_EXPAND(__CV_CPU_DISPATCH_CHAIN_ ## mode(fn, args, __VA_ARGS__))
 
 #if !defined CV_DISABLE_OPTIMIZATION && defined CV_ENABLE_INTRINSICS && defined CV_CPU_COMPILE_AVX512_ICL
 #  define CV_TRY_AVX512_ICL 1

modules/core/include/opencv2/core/cvdef.h

@@ -255,7 +255,7 @@ namespace cv { namespace debug_build_guard { } using namespace debug_build_guard
 #define CV_CPU_AVX512_KNL       258
 #define CV_CPU_AVX512_KNM       259
 #define CV_CPU_AVX512_CNL       260
-#define CV_CPU_AVX512_CEL       261
+#define CV_CPU_AVX512_CLX       261
 #define CV_CPU_AVX512_ICL       262
 
 // when adding to this list remember to update the following enum
@@ -306,7 +306,7 @@ enum CpuFeatures {
     CPU_AVX512_KNL      = 258, //!< Knights Landing with AVX-512F/CD/ER/PF
     CPU_AVX512_KNM      = 259, //!< Knights Mill with AVX-512F/CD/ER/PF/4FMAPS/4VNNIW/VPOPCNTDQ
     CPU_AVX512_CNL      = 260, //!< Cannon Lake with AVX-512F/CD/BW/DQ/VL/IFMA/VBMI
-    CPU_AVX512_CEL      = 261, //!< Cascade Lake with AVX-512F/CD/BW/DQ/VL/IFMA/VBMI/VNNI
+    CPU_AVX512_CLX      = 261, //!< Cascade Lake with AVX-512F/CD/BW/DQ/VL/VNNI
     CPU_AVX512_ICL      = 262, //!< Ice Lake with AVX-512F/CD/BW/DQ/VL/IFMA/VBMI/VNNI/VBMI2/BITALG/VPOPCNTDQ
 
     CPU_MAX_FEATURE     = 512  // see CV_HARDWARE_MAX_FEATURE

modules/core/src/softfloat.cpp

@@ -2065,14 +2065,18 @@ static int_fast64_t f64_to_i64(float64_t a, uint_fast8_t roundingMode, bool exac
     if (exp) sig |= UINT64_C(0x0010000000000000);
     shiftDist = 0x433 - exp;
     if (shiftDist <= 0) {
-        uint_fast64_t z = sig << -shiftDist;
+        bool isValid = shiftDist >= -11;
-        if ((shiftDist < -11) || (z & UINT64_C(0x8000000000000000)))
+        if (isValid)
         {
+            uint_fast64_t z = sig << -shiftDist;
+            if (0 == (z & UINT64_C(0x8000000000000000)))
+            {
+                return sign ? -(int_fast64_t)z : (int_fast64_t)z;
+            }
+        }
         raiseFlags(flag_invalid);
         return sign ? i64_fromNegOverflow : i64_fromPosOverflow;
     }
-        return sign ? -(int_fast64_t)z : (int_fast64_t)z;
-    }
     else {
         if (shiftDist < 64)
             return

modules/core/src/system.cpp

@@ -370,11 +370,12 @@ struct HWFeatures
 
         g_hwFeatureNames[CPU_MSA] = "CPU_MSA";
 
+        g_hwFeatureNames[CPU_AVX512_COMMON] = "AVX512-COMMON";
         g_hwFeatureNames[CPU_AVX512_SKX] = "AVX512-SKX";
         g_hwFeatureNames[CPU_AVX512_KNL] = "AVX512-KNL";
         g_hwFeatureNames[CPU_AVX512_KNM] = "AVX512-KNM";
         g_hwFeatureNames[CPU_AVX512_CNL] = "AVX512-CNL";
-        g_hwFeatureNames[CPU_AVX512_CEL] = "AVX512-CEL";
+        g_hwFeatureNames[CPU_AVX512_CLX] = "AVX512-CLX";
         g_hwFeatureNames[CPU_AVX512_ICL] = "AVX512-ICL";
     }
 
@@ -485,9 +486,11 @@ struct HWFeatures
                                           have[CV_CPU_AVX_5124VNNIW] && have[CV_CPU_AVX_512VPOPCNTDQ];
                 have[CV_CPU_AVX512_SKX] = have[CV_CPU_AVX_512BW] && have[CV_CPU_AVX_512DQ] && have[CV_CPU_AVX_512VL];
                 have[CV_CPU_AVX512_CNL] = have[CV_CPU_AVX512_SKX] && have[CV_CPU_AVX_512IFMA] && have[CV_CPU_AVX_512VBMI];
-                have[CV_CPU_AVX512_CEL] = have[CV_CPU_AVX512_CNL] && have[CV_CPU_AVX_512VNNI];
+                have[CV_CPU_AVX512_CLX] = have[CV_CPU_AVX512_SKX] && have[CV_CPU_AVX_512VNNI];
-                have[CV_CPU_AVX512_ICL] = have[CV_CPU_AVX512_CEL] && have[CV_CPU_AVX_512VBMI2] &&
+                have[CV_CPU_AVX512_ICL] = have[CV_CPU_AVX512_SKX] &&
-                                          have[CV_CPU_AVX_512BITALG] && have[CV_CPU_AVX_512VPOPCNTDQ];
+                                          have[CV_CPU_AVX_512IFMA] && have[CV_CPU_AVX_512VBMI] &&
+                                          have[CV_CPU_AVX_512VNNI] &&
+                                          have[CV_CPU_AVX_512VBMI2] && have[CV_CPU_AVX_512BITALG] && have[CV_CPU_AVX_512VPOPCNTDQ];
             }
             else
             {
@@ -495,7 +498,7 @@ struct HWFeatures
                 have[CV_CPU_AVX512_KNM] = false;
                 have[CV_CPU_AVX512_SKX] = false;
                 have[CV_CPU_AVX512_CNL] = false;
-                have[CV_CPU_AVX512_CEL] = false;
+                have[CV_CPU_AVX512_CLX] = false;
                 have[CV_CPU_AVX512_ICL] = false;
             }
         }
@@ -572,8 +575,16 @@ struct HWFeatures
         have[CV_CPU_VSX3] = (CV_VSX3);
     #endif
 
+        bool skip_baseline_check = false;
+#ifndef NO_GETENV
+        if (getenv("OPENCV_SKIP_CPU_BASELINE_CHECK"))
+        {
+            skip_baseline_check = true;
+        }
+#endif
         int baseline_features[] = { CV_CPU_BASELINE_FEATURES };
-        if (!checkFeatures(baseline_features, sizeof(baseline_features) / sizeof(baseline_features[0])))
+        if (!checkFeatures(baseline_features, sizeof(baseline_features) / sizeof(baseline_features[0]))
+            && !skip_baseline_check)
         {
             fprintf(stderr, "\n"
                     "******************************************************************\n"
@@ -600,12 +611,12 @@ struct HWFeatures
             {
                 if (have[feature])
                 {
-                    if (dump) fprintf(stderr, "%s - OK\n", getHWFeatureNameSafe(feature));
+                    if (dump) fprintf(stderr, "    ID=%3d (%s) - OK\n", feature, getHWFeatureNameSafe(feature));
                 }
                 else
                 {
                     result = false;
-                    if (dump) fprintf(stderr, "%s - NOT AVAILABLE\n", getHWFeatureNameSafe(feature));
+                    if (dump) fprintf(stderr, "    ID=%3d (%s) - NOT AVAILABLE\n", feature, getHWFeatureNameSafe(feature));
                 }
             }
         }

modules/dnn/misc/python/test/test_dnn.py

@@ -64,11 +64,19 @@ def printParams(backend, target):
 
 testdata_required = bool(os.environ.get('OPENCV_DNN_TEST_REQUIRE_TESTDATA', False))
 
+g_dnnBackendsAndTargets = None
+
 class dnn_test(NewOpenCVTests):
 
     def setUp(self):
         super(dnn_test, self).setUp()
 
+        global g_dnnBackendsAndTargets
+        if g_dnnBackendsAndTargets is None:
+            g_dnnBackendsAndTargets = self.initBackendsAndTargets()
+        self.dnnBackendsAndTargets = g_dnnBackendsAndTargets
+
+    def initBackendsAndTargets(self):
         self.dnnBackendsAndTargets = [
             [cv.dnn.DNN_BACKEND_OPENCV, cv.dnn.DNN_TARGET_CPU],
         ]
@@ -86,6 +94,7 @@ class dnn_test(NewOpenCVTests):
                     self.dnnBackendsAndTargets.append([cv.dnn.DNN_BACKEND_INFERENCE_ENGINE, cv.dnn.DNN_TARGET_OPENCL])
                 if self.checkIETarget(cv.dnn.DNN_BACKEND_INFERENCE_ENGINE, cv.dnn.DNN_TARGET_OPENCL_FP16):
                     self.dnnBackendsAndTargets.append([cv.dnn.DNN_BACKEND_INFERENCE_ENGINE, cv.dnn.DNN_TARGET_OPENCL_FP16])
+        return self.dnnBackendsAndTargets
 
     def find_dnn_file(self, filename, required=True):
         if not required:

modules/dnn/src/layers/pooling_layer.cpp

@@ -163,6 +163,8 @@ public:
     {
         if (backendId == DNN_BACKEND_INFERENCE_ENGINE)
         {
+            if (computeMaxIdx)
+                return false;
 #ifdef HAVE_INF_ENGINE
             if (kernel_size.size() == 3)
                 return preferableTarget == DNN_TARGET_CPU;

modules/dnn/src/op_inf_engine.hpp

@@ -22,10 +22,11 @@
 #define INF_ENGINE_RELEASE_2018R5 2018050000
 #define INF_ENGINE_RELEASE_2019R1 2019010000
 #define INF_ENGINE_RELEASE_2019R2 2019020000
+#define INF_ENGINE_RELEASE_2019R3 2019030000
 
 #ifndef INF_ENGINE_RELEASE
-#warning("IE version have not been provided via command-line. Using 2019R2 by default")
+#warning("IE version have not been provided via command-line. Using 2019R3 by default")
-#define INF_ENGINE_RELEASE INF_ENGINE_RELEASE_2019R2
+#define INF_ENGINE_RELEASE INF_ENGINE_RELEASE_2019R3
 #endif
 
 #define INF_ENGINE_VER_MAJOR_GT(ver) (((INF_ENGINE_RELEASE) / 10000) > ((ver) / 10000))

modules/dnn/test/test_common.hpp

@@ -19,6 +19,7 @@
 #define CV_TEST_TAG_DNN_SKIP_IE_2019R1           "dnn_skip_ie_2019r1"
 #define CV_TEST_TAG_DNN_SKIP_IE_2019R1_1         "dnn_skip_ie_2019r1_1"
 #define CV_TEST_TAG_DNN_SKIP_IE_2019R2           "dnn_skip_ie_2019r2"
+#define CV_TEST_TAG_DNN_SKIP_IE_2019R3           "dnn_skip_ie_2019r3"
 #define CV_TEST_TAG_DNN_SKIP_IE_OPENCL           "dnn_skip_ie_ocl"
 #define CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16      "dnn_skip_ie_ocl_fp16"
 #define CV_TEST_TAG_DNN_SKIP_IE_MYRIAD_2         "dnn_skip_ie_myriad2"

modules/dnn/test/test_common.impl.hpp

@@ -324,6 +324,8 @@ void initDNNTests()
 # endif
 #elif INF_ENGINE_VER_MAJOR_EQ(2019020000)
         CV_TEST_TAG_DNN_SKIP_IE_2019R2,
+#elif INF_ENGINE_VER_MAJOR_EQ(2019030000)
+        CV_TEST_TAG_DNN_SKIP_IE_2019R3,
 #endif
         CV_TEST_TAG_DNN_SKIP_IE
     );

modules/dnn/test/test_halide_layers.cpp

@@ -554,9 +554,9 @@ TEST_P(ReLU, Accuracy)
     Backend backendId = get<0>(get<1>(GetParam()));
     Target targetId = get<1>(get<1>(GetParam()));
 
-#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2019020000)
+#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2019020000)
     if (backendId == DNN_BACKEND_INFERENCE_ENGINE && targetId == DNN_TARGET_MYRIAD && negativeSlope < 0)
-        applyTestTag(CV_TEST_TAG_DNN_SKIP_IE, CV_TEST_TAG_DNN_SKIP_IE_2019R2);
+        applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_2019R3, CV_TEST_TAG_DNN_SKIP_IE_2019R2, CV_TEST_TAG_DNN_SKIP_IE);
 #endif
 
     LayerParams lp;

modules/dnn/test/test_onnx_importer.cpp

@@ -86,8 +86,8 @@ TEST_P(Test_ONNX_layers, InstanceNorm)
 
 TEST_P(Test_ONNX_layers, MaxPooling)
 {
-    testONNXModels("maxpooling");
+    testONNXModels("maxpooling", npy, 0, 0, false, false);
-    testONNXModels("two_maxpooling");
+    testONNXModels("two_maxpooling", npy, 0, 0, false, false);
 }
 
 TEST_P(Test_ONNX_layers, Convolution)
@@ -212,7 +212,7 @@ TEST_P(Test_ONNX_layers, MaxPooling3D)
 #endif
     if (target != DNN_TARGET_CPU)
         throw SkipTestException("Only CPU is supported");
-    testONNXModels("max_pool3d");
+    testONNXModels("max_pool3d", npy, 0, 0, false, false);
 }
 
 TEST_P(Test_ONNX_layers, AvePooling3D)
@@ -422,13 +422,22 @@ TEST_P(Test_ONNX_nets, Googlenet)
 TEST_P(Test_ONNX_nets, CaffeNet)
 {
     applyTestTag(target == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_512MB : CV_TEST_TAG_MEMORY_1GB);
+#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2019030000)
+    if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD
+        && getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X)
+        applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD_X, CV_TEST_TAG_DNN_SKIP_IE_2019R3);
+#endif
     testONNXModels("caffenet", pb);
 }
 
 TEST_P(Test_ONNX_nets, RCNN_ILSVRC13)
 {
     applyTestTag(target == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_512MB : CV_TEST_TAG_MEMORY_1GB);
-
+#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2019030000)
+    if (backend == DNN_BACKEND_INFERENCE_ENGINE && target == DNN_TARGET_MYRIAD
+        && getInferenceEngineVPUType() == CV_DNN_INFERENCE_ENGINE_VPU_TYPE_MYRIAD_X)
+        applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD_X, CV_TEST_TAG_DNN_SKIP_IE_2019R3);
+#endif
     // Reference output values are in range [-4.992, -1.161]
     testONNXModels("rcnn_ilsvrc13", pb, 0.0045);
 }

modules/dnn/test/test_tf_importer.cpp

@@ -146,13 +146,13 @@ TEST_P(Test_TensorFlow_layers, padding)
     runTensorFlowNet("padding_valid");
     runTensorFlowNet("spatial_padding");
     runTensorFlowNet("mirror_pad");
-#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_EQ(2019020000)
+#if defined(INF_ENGINE_RELEASE) && INF_ENGINE_VER_MAJOR_GE(2019020000)
     if (backend == DNN_BACKEND_INFERENCE_ENGINE)
     {
         if (target == DNN_TARGET_MYRIAD)
-            applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_2019R2);
+            applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD, CV_TEST_TAG_DNN_SKIP_IE_2019R3, CV_TEST_TAG_DNN_SKIP_IE_2019R2);
         if (target == DNN_TARGET_OPENCL_FP16)
-            applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, CV_TEST_TAG_DNN_SKIP_IE_2019R2);
+            applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16, CV_TEST_TAG_DNN_SKIP_IE_2019R3, CV_TEST_TAG_DNN_SKIP_IE_2019R2);
     }
 #endif
     runTensorFlowNet("keras_pad_concat");

modules/dnn/test/test_torch_importer.cpp

@@ -337,9 +337,15 @@ TEST_P(Test_Torch_nets, ENet_accuracy)
 {
     applyTestTag(target == DNN_TARGET_CPU ? "" : CV_TEST_TAG_MEMORY_512MB);
     checkBackend();
-    if (backend == DNN_BACKEND_INFERENCE_ENGINE ||
+    if (backend == DNN_BACKEND_OPENCV && target == DNN_TARGET_OPENCL_FP16)
-        (backend == DNN_BACKEND_OPENCV && target == DNN_TARGET_OPENCL_FP16))
+        throw SkipTestException("");
-        applyTestTag(target == DNN_TARGET_OPENCL ? CV_TEST_TAG_DNN_SKIP_IE_OPENCL : CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16);
+    if (backend == DNN_BACKEND_INFERENCE_ENGINE && target != DNN_TARGET_CPU)
+    {
+        if (target == DNN_TARGET_OPENCL_FP16) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL_FP16);
+        if (target == DNN_TARGET_OPENCL)      applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_OPENCL);
+        if (target == DNN_TARGET_MYRIAD)      applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD);
+        throw SkipTestException("");
+    }
 
     Net net;
     {

modules/imgproc/misc/java/test/ImgprocTest.java

@@ -807,7 +807,7 @@ public class ImgprocTest extends OpenCVTestCase {
         points.put(0, 0, 0, 0, 2, 3, 3, 4, 5, 8);
 
         Mat linePoints = new Mat(4, 1, CvType.CV_32FC1);
-        linePoints.put(0, 0, 0.53196341, 0.84676737, 2.496531, 3.7467217);
+        linePoints.put(0, 0, 0.53198653, 0.84675282, 2.5, 3.75);
 
         Imgproc.fitLine(points, dst, Imgproc.CV_DIST_L12, 0, 0.01, 0.01);
 

modules/imgproc/src/linefit.cpp

@@ -408,8 +408,14 @@ static void fitLine2D( const Point2f * points, int count, int dist,
             }
             /* calculate distances */
             err = calcDist2D( points, count, _line, r );
-            if( err < EPS )
+
+            if (err < min_err)
+            {
+                min_err = err;
+                memcpy(line, _line, 4 * sizeof(line[0]));
+                if (err < EPS)
                     break;
+            }
 
             /* calculate weights */
             if( calc_weights )
@@ -550,8 +556,13 @@ static void fitLine3D( Point3f * points, int count, int dist,
             }
             /* calculate distances */
             err = calcDist3D( points, count, _line, r );
-            //if( err < FLT_EPSILON*count )
+            if (err < min_err)
-            //    break;
+            {
+                min_err = err;
+                memcpy(line, _line, 6 * sizeof(line[0]));
+                if (err < EPS)
+                    break;
+            }
 
             /* calculate weights */
             if( calc_weights )

modules/imgproc/test/test_convhull.cpp

@@ -1609,6 +1609,8 @@ int CV_FitLineTest::validate_test_results( int test_case_idx )
     int k, max_k = 0;
     double vec_diff = 0, t;
 
+    //std::cout << dims << " " << Mat(1, dims*2, CV_32FC1, line.data()) << " " << Mat(1, dims, CV_32FC1, line0.data()) << std::endl;
+
     for( k = 0; k < dims*2; k++ )
     {
         if( cvIsNaN(line[k]) || cvIsInf(line[k]) )
@@ -2038,5 +2040,38 @@ INSTANTIATE_TEST_CASE_P(Imgproc, ConvexityDefects_regression_5908,
                 testing::Values(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10)
         ));
 
+TEST(Imgproc_FitLine, regression_15083)
+{
+    int points2i_[] = {
+        432, 654,
+        370, 656,
+        390, 656,
+        410, 656,
+        348, 658
+    };
+    Mat points(5, 1, CV_32SC2, points2i_);
+
+    Vec4f lineParam;
+    fitLine(points, lineParam, DIST_L1, 0, 0.01, 0.01);
+    EXPECT_GE(fabs(lineParam[0]), fabs(lineParam[1]) * 4) << lineParam;
+}
+
+TEST(Imgproc_FitLine, regression_4903)
+{
+    float points2f_[] = {
+        1224.0, 576.0,
+        1234.0, 683.0,
+        1215.0, 471.0,
+        1184.0, 137.0,
+        1079.0, 377.0,
+        1239.0, 788.0,
+    };
+    Mat points(6, 1, CV_32FC2, points2f_);
+
+    Vec4f lineParam;
+    fitLine(points, lineParam, DIST_WELSCH, 0, 0.01, 0.01);
+    EXPECT_GE(fabs(lineParam[1]), fabs(lineParam[0]) * 4) << lineParam;
+}
+
 }} // namespace
 /* End of file. */

modules/objdetect/src/qrcode.cpp

@@ -359,22 +359,26 @@ bool QRDetect::localization()
 
     bool suare_flag = false, local_points_flag = false;
     double triangle_sides[3];
+    double triangle_perim, square_area, img_square_area;
+    if (localization_points.size() == 3)
+    {
         triangle_sides[0] = norm(localization_points[0] - localization_points[1]);
         triangle_sides[1] = norm(localization_points[1] - localization_points[2]);
         triangle_sides[2] = norm(localization_points[2] - localization_points[0]);
 
-    double triangle_perim = (triangle_sides[0] + triangle_sides[1] + triangle_sides[2]) / 2;
+        triangle_perim = (triangle_sides[0] + triangle_sides[1] + triangle_sides[2]) / 2;
 
-    double square_area = sqrt((triangle_perim * (triangle_perim - triangle_sides[0])
+        square_area = sqrt((triangle_perim * (triangle_perim - triangle_sides[0])
                                            * (triangle_perim - triangle_sides[1])
                                            * (triangle_perim - triangle_sides[2]))) * 2;
-    double img_square_area = bin_barcode.cols * bin_barcode.rows;
+        img_square_area = bin_barcode.cols * bin_barcode.rows;
 
         if (square_area > (img_square_area * 0.2))
         {
             suare_flag = true;
         }
-    if (localization_points.size() != 3)
+    }
+    else
     {
         local_points_flag = true;
     }