Merge pull request #3153 from stal12:4.x

Author: alalek

modules/cudaimgproc/doc/cudaimgproc.bib

@@ -0,0 +1,10 @@
+@article{Allegretti2019,
+  title={Optimized block-based algorithms to label connected components on GPUs},
+  author={Allegretti, Stefano and Bolelli, Federico and Grana, Costantino},
+  journal={IEEE Transactions on Parallel and Distributed Systems},
+  volume={31},
+  number={2},
+  pages={423--438},
+  year={2019},
+  publisher={IEEE}
+}

modules/cudaimgproc/include/opencv2/cudaimgproc.hpp

@@ -731,6 +731,50 @@ type.
 CV_EXPORTS_W void blendLinear(InputArray img1, InputArray img2, InputArray weights1, InputArray weights2,
                             OutputArray result, Stream& stream = Stream::Null());
 
+/////////////////// Connected Components Labeling /////////////////////
+
+//! Connected Components Algorithm
+enum ConnectedComponentsAlgorithmsTypes {
+    CCL_DEFAULT = -1, //!< BKE @cite Allegretti2019 algorithm for 8-way connectivity.
+    CCL_BKE = 0,  //!< BKE @cite Allegretti2019 algorithm for 8-way connectivity.
+};
+
+
+/** @brief Computes the Connected Components Labeled image of a binary image.
+
+The function takes as input a binary image and performs Connected Components Labeling. The output
+is an image where each Connected Component is assigned a unique label (integer value).
+ltype specifies the output label image type, an important consideration based on the total
+number of labels or alternatively the total number of pixels in the source image.
+ccltype specifies the connected components labeling algorithm to use, currently
+BKE @cite Allegretti2019 is supported, see the #ConnectedComponentsAlgorithmsTypes
+for details. Note that labels in the output are not required to be sequential.
+
+@param image The 8-bit single-channel image to be labeled.
+@param labels Destination labeled image.
+@param connectivity Connectivity to use for the labeling procedure. 8 for 8-way connectivity is supported.
+@param ltype Output image label type. Currently CV_32S is supported.
+@param ccltype Connected components algorithm type (see the #ConnectedComponentsAlgorithmsTypes).
+
+@note A sample program demonstrating Connected Components Labeling in CUDA can be found at\n
+opencv_contrib_source_code/modules/cudaimgproc/samples/connected_components.cpp
+
+*/
+CV_EXPORTS_AS(connectedComponentsWithAlgorithm) void connectedComponents(InputArray image, OutputArray labels,
+    int connectivity, int ltype, cv::cuda::ConnectedComponentsAlgorithmsTypes ccltype);
+
+
+/** @overload
+
+@param image The 8-bit single-channel image to be labeled.
+@param labels Destination labeled image.
+@param connectivity Connectivity to use for the labeling procedure. 8 for 8-way connectivity is supported.
+@param ltype Output image label type. Currently CV_32S is supported.
+*/
+CV_EXPORTS_W void connectedComponents(InputArray image, OutputArray labels,
+    int connectivity = 8, int ltype = CV_32S);
+
+
 //! @}
 
 }} // namespace cv { namespace cuda {

modules/cudaimgproc/samples/connected_components.cpp

@@ -0,0 +1,58 @@
+#include <iostream>
+
+#include <opencv2/core/utility.hpp>
+#include "opencv2/imgproc.hpp"
+#include "opencv2/imgcodecs.hpp"
+#include "opencv2/highgui.hpp"
+#include "opencv2/cudaimgproc.hpp"
+
+using namespace cv;
+using namespace std;
+using namespace cv::cuda;
+
+
+void colorLabels(const Mat1i& labels, Mat3b& colors) {
+    colors.create(labels.size());
+    for (int r = 0; r < labels.rows; ++r) {
+        int const* labels_row = labels.ptr<int>(r);
+        Vec3b* colors_row = colors.ptr<Vec3b>(r);
+        for (int c = 0; c < labels.cols; ++c) {
+            colors_row[c] = Vec3b(labels_row[c] * 131 % 255, labels_row[c] * 241 % 255, labels_row[c] * 251 % 255);
+        }
+    }
+}
+
+
+int main(int argc, const char** argv)
+{
+    CommandLineParser parser(argc, argv, "{@image|stuff.jpg|image for converting to a grayscale}");
+    parser.about("This program finds connected components in a binary image and assign each of them a different color.\n"
+        "The connected components labeling is performed in GPU.\n");
+    parser.printMessage();
+
+    String inputImage = parser.get<string>(0);
+    Mat1b img = imread(samples::findFile(inputImage), IMREAD_GRAYSCALE);
+    Mat1i labels;
+
+    if (img.empty())
+    {
+        cout << "Could not read input image file: " << inputImage << endl;
+        return EXIT_FAILURE;
+    }
+
+
+    GpuMat d_img, d_labels;
+    d_img.upload(img);
+
+    cuda::connectedComponents(d_img, d_labels, 8, CV_32S);
+
+    d_labels.download(labels);
+
+    Mat3b colors;
+    colorLabels(labels, colors);
+
+    imshow("Labels", colors);
+    waitKey(0);
+
+    return EXIT_SUCCESS;
+}

modules/cudaimgproc/src/connectedcomponents.cpp

@@ -0,0 +1,49 @@
+// 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 "precomp.hpp"
+
+using namespace cv;
+using namespace cv::cuda;
+
+#if !defined (HAVE_CUDA) || defined (CUDA_DISABLER)
+
+void cv::cuda::connectedComponents(InputArray img_, OutputArray labels_, int connectivity,
+    int ltype, ConnectedComponentsAlgorithmsTypes ccltype) { throw_no_cuda(); }
+
+#else /* !defined (HAVE_CUDA) */
+
+namespace cv { namespace cuda { namespace device { namespace imgproc {
+        void BlockBasedKomuraEquivalence(const cv::cuda::GpuMat& img, cv::cuda::GpuMat& labels);
+}}}}
+
+
+void cv::cuda::connectedComponents(InputArray img_, OutputArray labels_, int connectivity,
+    int ltype, ConnectedComponentsAlgorithmsTypes ccltype) {
+    const cv::cuda::GpuMat img = img_.getGpuMat();
+    cv::cuda::GpuMat& labels = labels_.getGpuMatRef();
+
+    CV_Assert(img.channels() == 1);
+    CV_Assert(connectivity == 8);
+    CV_Assert(ltype == CV_32S);
+    CV_Assert(ccltype == CCL_BKE || ccltype == CCL_DEFAULT);
+
+    int iDepth = img_.depth();
+    CV_Assert(iDepth == CV_8U || iDepth == CV_8S);
+
+    labels.create(img.size(), CV_MAT_DEPTH(ltype));
+
+    if ((ccltype == CCL_BKE || ccltype == CCL_DEFAULT) && connectivity == 8 && ltype == CV_32S) {
+        using cv::cuda::device::imgproc::BlockBasedKomuraEquivalence;
+        BlockBasedKomuraEquivalence(img, labels);
+    }
+
+}
+
+void cv::cuda::connectedComponents(InputArray img_, OutputArray labels_, int connectivity, int ltype) {
+    cv::cuda::connectedComponents(img_, labels_, connectivity, ltype, CCL_DEFAULT);
+}
+
+
+#endif /* !defined (HAVE_CUDA) */