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

Author: alalek

.github/ISSUE_TEMPLATE.md

@@ -1,3 +1,10 @@
+<!--
+If you have a question rather than reporting a bug please go to https://forum.opencv.org where you get much faster responses.
+If you need further assistance please read [How To Contribute](https://github.com/opencv/opencv/wiki/How_to_contribute).
+
+This is a template helping you to create an issue which can be processed as quickly as possible. This is the bug reporting section for the OpenCV library.
+-->
+
 ##### System information (version)
 <!-- Example
 - OpenCV => 4.2

doc/js_tutorials/js_setup/js_setup/js_setup.markdown

@@ -294,20 +294,20 @@ So, make sure [docker](https://www.docker.com/) is installed in your system and
 @code{.bash}
 git clone https://github.com/opencv/opencv.git
 cd opencv
-docker run --rm -v $(pwd):/src -u $(id -u):$(id -g) emscripten/emsdk emcmake python3 ./dev/platforms/js/build_js.py build_js
+docker run --rm -v $(pwd):/src -u $(id -u):$(id -g) emscripten/emsdk emcmake python3 ./platforms/js/build_js.py build_js
 @endcode
 
 In Windows use the following PowerShell command:
 
 @code{.bash}
-docker run --rm --workdir /src -v "$(get-location):/src" "emscripten/emsdk" emcmake python3 ./dev/platforms/js/build_js.py build_js
+docker run --rm --workdir /src -v "$(get-location):/src" "emscripten/emsdk" emcmake python3 ./platforms/js/build_js.py build_js
 @endcode
 
 @warning
 The example uses latest version of emscripten. If the build fails you should try a version that is known to work fine which is `2.0.10` using the following command:
 
 @code{.bash}
-docker run --rm -v $(pwd):/src -u $(id -u):$(id -g) emscripten/emsdk:2.0.10 emcmake python3 ./dev/platforms/js/build_js.py build_js
+docker run --rm -v $(pwd):/src -u $(id -u):$(id -g) emscripten/emsdk:2.0.10 emcmake python3 ./platforms/js/build_js.py build_js
 @endcode
 
 ### Building the documentation with Docker
@@ -331,5 +331,5 @@ docker build . -t opencv-js-doc
 Now run the build command again, this time using the new image and passing `--build_doc`:
 
 @code{.bash}
-docker run --rm -v $(pwd):/src -u $(id -u):$(id -g) "opencv-js-doc" emcmake python3 ./dev/platforms/js/build_js.py build_js --build_doc
+docker run --rm -v $(pwd):/src -u $(id -u):$(id -g) "opencv-js-doc" emcmake python3 ./platforms/js/build_js.py build_js --build_doc
 @endcode

doc/py_tutorials/py_imgproc/py_pyramids/py_pyramids.markdown

@@ -88,27 +88,27 @@ B = cv.imread('orange.jpg')
 # generate Gaussian pyramid for A
 G = A.copy()
 gpA = [G]
-for i in xrange(6):
+for i in range(6):
     G = cv.pyrDown(G)
     gpA.append(G)
 
 # generate Gaussian pyramid for B
 G = B.copy()
 gpB = [G]
-for i in xrange(6):
+for i in range(6):
     G = cv.pyrDown(G)
     gpB.append(G)
 
 # generate Laplacian Pyramid for A
 lpA = [gpA[5]]
-for i in xrange(5,0,-1):
+for i in range(5,0,-1):
     GE = cv.pyrUp(gpA[i])
     L = cv.subtract(gpA[i-1],GE)
     lpA.append(L)
 
 # generate Laplacian Pyramid for B
 lpB = [gpB[5]]
-for i in xrange(5,0,-1):
+for i in range(5,0,-1):
     GE = cv.pyrUp(gpB[i])
     L = cv.subtract(gpB[i-1],GE)
     lpB.append(L)
@@ -122,7 +122,7 @@ for la,lb in zip(lpA,lpB):
 
 # now reconstruct
 ls_ = LS[0]
-for i in xrange(1,6):
+for i in range(1,6):
     ls_ = cv.pyrUp(ls_)
     ls_ = cv.add(ls_, LS[i])
 

doc/py_tutorials/py_imgproc/py_thresholding/py_thresholding.markdown

@@ -47,7 +47,7 @@ ret,thresh5 = cv.threshold(img,127,255,cv.THRESH_TOZERO_INV)
 titles = ['Original Image','BINARY','BINARY_INV','TRUNC','TOZERO','TOZERO_INV']
 images = [img, thresh1, thresh2, thresh3, thresh4, thresh5]
 
-for i in xrange(6):
+for i in range(6):
     plt.subplot(2,3,i+1),plt.imshow(images[i],'gray',vmin=0,vmax=255)
     plt.title(titles[i])
     plt.xticks([]),plt.yticks([])
@@ -98,7 +98,7 @@ titles = ['Original Image', 'Global Thresholding (v = 127)',
             'Adaptive Mean Thresholding', 'Adaptive Gaussian Thresholding']
 images = [img, th1, th2, th3]
 
-for i in xrange(4):
+for i in range(4):
     plt.subplot(2,2,i+1),plt.imshow(images[i],'gray')
     plt.title(titles[i])
     plt.xticks([]),plt.yticks([])
@@ -153,7 +153,7 @@ titles = ['Original Noisy Image','Histogram','Global Thresholding (v=127)',
           'Original Noisy Image','Histogram',"Otsu's Thresholding",
           'Gaussian filtered Image','Histogram',"Otsu's Thresholding"]
 
-for i in xrange(3):
+for i in range(3):
     plt.subplot(3,3,i*3+1),plt.imshow(images[i*3],'gray')
     plt.title(titles[i*3]), plt.xticks([]), plt.yticks([])
     plt.subplot(3,3,i*3+2),plt.hist(images[i*3].ravel(),256)
@@ -196,7 +196,7 @@ bins = np.arange(256)
 fn_min = np.inf
 thresh = -1
 
-for i in xrange(1,256):
+for i in range(1,256):
     p1,p2 = np.hsplit(hist_norm,[i]) # probabilities
     q1,q2 = Q[i],Q[255]-Q[i] # cum sum of classes
     if q1 < 1.e-6 or q2 < 1.e-6:

doc/py_tutorials/py_imgproc/py_transforms/py_fourier_transform/py_fourier_transform.markdown

@@ -268,7 +268,7 @@ fft_filters = [np.fft.fft2(x) for x in filters]
 fft_shift = [np.fft.fftshift(y) for y in fft_filters]
 mag_spectrum = [np.log(np.abs(z)+1) for z in fft_shift]
 
-for i in xrange(6):
+for i in range(6):
     plt.subplot(2,3,i+1),plt.imshow(mag_spectrum[i],cmap = 'gray')
     plt.title(filter_name[i]), plt.xticks([]), plt.yticks([])
 

doc/py_tutorials/py_photo/py_non_local_means/py_non_local_means.markdown

@@ -108,7 +108,7 @@ from matplotlib import pyplot as plt
 cap = cv.VideoCapture('vtest.avi')
 
 # create a list of first 5 frames
-img = [cap.read()[1] for i in xrange(5)]
+img = [cap.read()[1] for i in range(5)]
 
 # convert all to grayscale
 gray = [cv.cvtColor(i, cv.COLOR_BGR2GRAY) for i in img]

modules/core/include/opencv2/core/bindings_utils.hpp

@@ -64,6 +64,20 @@ String dumpString(const String& argument)
     return cv::format("String: %s", argument.c_str());
 }
 
+CV_WRAP static inline
+String testOverloadResolution(int value, const Point& point = Point(42, 24))
+{
+    return format("overload (int=%d, point=(x=%d, y=%d))", value, point.x,
+                  point.y);
+}
+
+CV_WRAP static inline
+String testOverloadResolution(const Rect& rect)
+{
+    return format("overload (rect=(x=%d, y=%d, w=%d, h=%d))", rect.x, rect.y,
+                  rect.width, rect.height);
+}
+
 CV_WRAP static inline
 AsyncArray testAsyncArray(InputArray argument)
 {

modules/core/src/ocl.cpp

@@ -3382,16 +3382,24 @@ struct Kernel::Impl
             haveTempSrcUMats = true;  // UMat is created on RAW memory (without proper lifetime management, even from Mat)
     }
 
-    void addImage(const Image2D& image)
+    /// Preserve image lifetime (while it is specified as Kernel argument)
+    void registerImageArgument(int arg, const Image2D& image)
     {
-        images.push_back(image);
+        CV_CheckGE(arg, 0, "");
+        CV_CheckLT(arg, (int)MAX_ARRS, "");
+        if (arg < (int)shadow_images.size() && shadow_images[arg].ptr() != image.ptr())  // TODO future: replace ptr => impl (more strong check)
+        {
+            CV_Check(arg, !isInProgress, "ocl::Kernel: clearing of pending Image2D arguments is not allowed");
+        }
+        shadow_images.reserve(MAX_ARRS);
+        shadow_images.resize(std::max(shadow_images.size(), (size_t)arg + 1));
+        shadow_images[arg] = image;
     }
 
     void finit(cl_event e)
     {
         CV_UNUSED(e);
         cleanupUMats();
-        images.clear();
         isInProgress = false;
         release();
     }
@@ -3416,7 +3424,7 @@ struct Kernel::Impl
     bool isInProgress;
     bool isAsyncRun;  // true if kernel was scheduled in async mode
     int nu;
-    std::list<Image2D> images;
+    std::vector<Image2D> shadow_images;
     bool haveTempDstUMats;
     bool haveTempSrcUMats;
 };
@@ -3558,9 +3566,11 @@ int Kernel::set(int i, const void* value, size_t sz)
 
 int Kernel::set(int i, const Image2D& image2D)
 {
-    p->addImage(image2D);
     cl_mem h = (cl_mem)image2D.ptr();
-    return set(i, &h, sizeof(h));
+    int res = set(i, &h, sizeof(h));
+    if (res >= 0)
+        p->registerImageArgument(i, image2D);
+    return res;
 }
 
 int Kernel::set(int i, const UMat& m)

modules/highgui/src/window_w32.cpp

@@ -249,7 +249,7 @@ CV_IMPL int cvInitSystem( int, char** )
     // check initialization status
     if( !wasInitialized )
     {
-        // Initialize the stogare
+        // Initialize the storage
         hg_windows = 0;
 
         // Register the class

modules/python/src2/cv2.cpp

@@ -34,6 +34,7 @@
 
 #include "opencv2/core/utils/configuration.private.hpp"
 #include "opencv2/core/utils/logger.hpp"
+#include "opencv2/core/utils/tls.hpp"
 
 #include "pyopencv_generated_include.h"
 #include "opencv2/core/types_c.h"
@@ -141,6 +142,51 @@ class PyEnsureGIL
     PyGILState_STATE _state;
 };
 
+/**
+ * Light weight RAII wrapper for `PyObject*` owning references.
+ * In comparisson to C++11 `std::unique_ptr` with custom deleter, it provides
+ * implicit conversion functions that might be useful to initialize it with
+ * Python functions those returns owning references through the `PyObject**`
+ * e.g. `PyErr_Fetch` or directly pass it to functions those want to borrow
+ * reference to object (doesn't extend object lifetime) e.g. `PyObject_Str`.
+ */
+class PySafeObject
+{
+public:
+    PySafeObject() : obj_(NULL) {}
+
+    explicit PySafeObject(PyObject* obj) : obj_(obj) {}
+
+    ~PySafeObject()
+    {
+        Py_CLEAR(obj_);
+    }
+
+    operator PyObject*()
+    {
+        return obj_;
+    }
+
+    operator PyObject**()
+    {
+        return &obj_;
+    }
+
+    PyObject* release()
+    {
+        PyObject* obj = obj_;
+        obj_ = NULL;
+        return obj;
+    }
+
+private:
+    PyObject* obj_;
+
+    // Explicitly disable copy operations
+    PySafeObject(const PySafeObject*); // = delete
+    PySafeObject& operator=(const PySafeObject&); // = delete
+};
+
 static void pyRaiseCVException(const cv::Exception &e)
 {
     PyObject_SetAttrString(opencv_error, "file", PyString_FromString(e.file.c_str()));
@@ -293,6 +339,74 @@ bool parseNumpyScalar(PyObject* obj, T& value)
     return false;
 }
 
+TLSData<std::vector<std::string> > conversionErrorsTLS;
+
+inline void pyPrepareArgumentConversionErrorsStorage(std::size_t size)
+{
+    std::vector<std::string>& conversionErrors = conversionErrorsTLS.getRef();
+    conversionErrors.clear();
+    conversionErrors.reserve(size);
+}
+
+void pyRaiseCVOverloadException(const std::string& functionName)
+{
+    const std::vector<std::string>& conversionErrors = conversionErrorsTLS.getRef();
+    const std::size_t conversionErrorsCount = conversionErrors.size();
+    if (conversionErrorsCount > 0)
+    {
+        // In modern std libraries small string optimization is used = no dynamic memory allocations,
+        // but it can be applied only for string with length < 18 symbols (in GCC)
+        const std::string bullet = "\n - ";
+
+        // Estimate required buffer size - save dynamic memory allocations = faster
+        std::size_t requiredBufferSize = bullet.size() * conversionErrorsCount;
+        for (std::size_t i = 0; i < conversionErrorsCount; ++i)
+        {
+            requiredBufferSize += conversionErrors[i].size();
+        }
+
+        // Only string concatenation is required so std::string is way faster than
+        // std::ostringstream
+        std::string errorMessage("Overload resolution failed:");
+        errorMessage.reserve(errorMessage.size() + requiredBufferSize);
+        for (std::size_t i = 0; i < conversionErrorsCount; ++i)
+        {
+            errorMessage += bullet;
+            errorMessage += conversionErrors[i];
+        }
+        cv::Exception exception(CV_StsBadArg, errorMessage, functionName, "", -1);
+        pyRaiseCVException(exception);
+    }
+    else
+    {
+        cv::Exception exception(CV_StsInternal, "Overload resolution failed, but no errors reported",
+                                functionName, "", -1);
+        pyRaiseCVException(exception);
+    }
+}
+
+void pyPopulateArgumentConversionErrors()
+{
+    if (PyErr_Occurred())
+    {
+        PySafeObject exception_type;
+        PySafeObject exception_value;
+        PySafeObject exception_traceback;
+        PyErr_Fetch(exception_type, exception_value, exception_traceback);
+        PyErr_NormalizeException(exception_type, exception_value,
+                                 exception_traceback);
+
+        PySafeObject exception_message(PyObject_Str(exception_value));
+        std::string message;
+        getUnicodeString(exception_message, message);
+#ifdef CV_CXX11
+        conversionErrorsTLS.getRef().push_back(std::move(message));
+#else
+        conversionErrorsTLS.getRef().push_back(message);
+#endif
+    }
+}
+
 } // namespace
 
 typedef std::vector<uchar> vector_uchar;