Merge branch 'master' of https://github.com/nevion/opencv into cc

modules/imgproc/doc/structural_analysis_and_shape_descriptors.rst

@@ -118,6 +118,48 @@ These values are proved to be invariants to the image scale, rotation, and refle
 
 .. seealso:: :ocv:func:`matchShapes`
 
+connectedComponents
+-----------
+computes the connected components labeled image of boolean image I with 4 or 8 way connectivity - returns N, the total
+number of labels [0, N-1] where 0 represents the background label. L's value type determines the label type, an important
+consideration based on the total number of labels or alternatively the total number of pixels.
+
+.. ocv:function:: uint64 connectedComponents(Mat &L, const Mat &I, int connectivity = 8)
+
+.. ocv:function:: uint64 connectedComponentsWithStats(Mat &L, const Mat &I, std::vector<ConnectedComponentStats> &statsv, int connectivity = 8)
+
+    :param L: destitination Labeled image
+
+    :param I: the image to be labeled
+
+    :param connectivity: 8 or 4 for 8-way or 4-way connectivity respectively
+
+    :param statsv: statistics for each label, including the background label
+
+Statistics information such as bounding box, area, and centroid is exported via the ``ConnectComponentStats`` structure defined as: ::
+
+    class CV_EXPORTS ConnectedComponentStats
+    {
+        public:
+        //! lower left corner column
+        int lower_x;
+        //! lower left corner row
+        int lower_y;
+        //! upper right corner column
+        int upper_x;
+        //! upper right corner row
+        int upper_y;
+        //! centroid column
+        double centroid_x;
+        //! centroid row
+        double centroid_y;
+        //! sum of all columns where the image was non-zero
+        uint64 integral_x;
+        //! sum of all rows where the image was non-zero
+        uint64 integral_y;
+        //! count of all non-zero pixels
+        unsigned int area;
+    };
 
 findContours
 ----------------

modules/imgproc/include/opencv2/imgproc/imgproc.hpp

@@ -1102,6 +1102,15 @@ enum { TM_SQDIFF=0, TM_SQDIFF_NORMED=1, TM_CCORR=2, TM_CCORR_NORMED=3, TM_CCOEFF
 CV_EXPORTS_W void matchTemplate( InputArray image, InputArray templ,
                                  OutputArray result, int method );
 
+enum { CC_STAT_LEFT=0, CC_STAT_TOP=1, CC_STAT_WIDTH=2, CC_STAT_HEIGHT=3, CC_STAT_AREA=4, CC_STAT_MAX = 5};
+
+//! computes the connected components labeled image of boolean image I with 4 or 8 way connectivity - returns N, the total
+//number of labels [0, N-1] where 0 represents the background label. L's value type determines the label type, an important
+//consideration based on the total number of labels or alternatively the total number of pixels.
+CV_EXPORTS_W int connectedComponents(InputArray image, OutputArray labels, int connectivity = 8, int ltype=CV_32S);
+CV_EXPORTS_W int connectedComponentsWithStats(InputArray image, OutputArray labels, OutputArray stats, OutputArray centroids, int connectivity = 8, int ltype=CV_32S);
+
+
 //! mode of the contour retrieval algorithm
 enum
 {

modules/imgproc/test/test_connectedcomponents.cpp

+/*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 materials 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 implied warranties, including, but not limited to, the implied
+// 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"
+#include <string>
+
+using namespace cv;
+using namespace std;
+
+class CV_ConnectedComponentsTest : public cvtest::BaseTest
+{
+public:
+    CV_ConnectedComponentsTest();
+    ~CV_ConnectedComponentsTest();
+protected:
+    void run(int);
+};
+
+CV_ConnectedComponentsTest::CV_ConnectedComponentsTest() {}
+CV_ConnectedComponentsTest::~CV_ConnectedComponentsTest() {}
+
+void CV_ConnectedComponentsTest::run( int /* start_from */)
+{
+    string exp_path = string(ts->get_data_path()) + "connectedcomponents/ccomp_exp.png";
+    Mat exp = imread(exp_path, 0);
+    Mat orig = imread(string(ts->get_data_path()) + "connectedcomponents/concentric_circles.png", 0);
+
+    if (orig.empty())
+    {
+        ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_TEST_DATA );
+        return;
+    }
+
+    Mat bw = orig > 128;
+    Mat labelImage;
+    int nLabels = connectedComponents(bw, labelImage, 8, CV_32S);
+
+    for(int r = 0; r < labelImage.rows; ++r){
+        for(int c = 0; c < labelImage.cols; ++c){
+            int l = labelImage.at<int>(r, c);
+            bool pass = l >= 0 && l <= nLabels;
+            if(!pass){
+                ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );
+                return;
+            }
+        }
+    }
+
+    if( exp.empty() || orig.size() != exp.size() )
+    {
+        imwrite(exp_path, labelImage);
+        exp = labelImage;
+    }
+
+    if (0 != norm(labelImage > 0, exp > 0, NORM_INF))
+    {
+        ts->set_failed_test_info( cvtest::TS::FAIL_MISMATCH );
+        return;
+    }
+    if (nLabels != norm(labelImage, NORM_INF)+1)
+    {
+        ts->set_failed_test_info( cvtest::TS::FAIL_MISMATCH );
+        return;
+    }
+    ts->set_failed_test_info(cvtest::TS::OK);
+}
+
+TEST(Imgproc_ConnectedComponents, regression) { CV_ConnectedComponentsTest test; test.safe_run(); }
+

modules/python/src2/cv2.cpp

@@ -410,7 +410,7 @@ static bool pyopencv_to(PyObject* obj, bool& value, const char* name = "<unknown
 
 static PyObject* pyopencv_from(size_t value)
 {
-    return PyLong_FromUnsignedLong((unsigned long)value);
+    return PyLong_FromSize_t(value);
 }
 
 static bool pyopencv_to(PyObject* obj, size_t& value, const char* name = "<unknown>")
@@ -497,9 +497,16 @@ static bool pyopencv_to(PyObject* obj, float& value, const char* name = "<unknow
 
 static PyObject* pyopencv_from(int64 value)
 {
-    return PyFloat_FromDouble((double)value);
+    return PyLong_FromLongLong(value);
 }
 
+#if !defined(__LP64__)
+static PyObject* pyopencv_from(uint64 value)
+{
+    return PyLong_FromUnsignedLongLong(value);
+}
+#endif
+
 static PyObject* pyopencv_from(const string& value)
 {
     return PyString_FromString(value.empty() ? "" : value.c_str());

samples/cpp/connected_components.cpp

@@ -11,25 +11,21 @@ int threshval = 100;
 static void on_trackbar(int, void*)
 {
     Mat bw = threshval < 128 ? (img < threshval) : (img > threshval);
-
-    vector<vector<Point> > contours;
-    vector<Vec4i> hierarchy;
-
-    findContours( bw, contours, hierarchy, CV_RETR_CCOMP, CV_CHAIN_APPROX_SIMPLE );
-
-    Mat dst = Mat::zeros(img.size(), CV_8UC3);
-
-    if( !contours.empty() && !hierarchy.empty() )
-    {
-        // iterate through all the top-level contours,
-        // draw each connected component with its own random color
-        int idx = 0;
-        for( ; idx >= 0; idx = hierarchy[idx][0] )
-        {
-            Scalar color( (rand()&255), (rand()&255), (rand()&255) );
-            drawContours( dst, contours, idx, color, CV_FILLED, 8, hierarchy );
-        }
+    Mat labelImage(img.size(), CV_32S);
+    int nLabels = connectedComponents(bw, labelImage, 8);
+    std::vector<Vec3b> colors(nLabels);
+    colors[0] = Vec3b(0, 0, 0);//background
+    for(int label = 1; label < nLabels; ++label){
+        colors[label] = Vec3b( (rand()&255), (rand()&255), (rand()&255) );
     }
+    Mat dst(img.size(), CV_8UC3);
+    for(int r = 0; r < dst.rows; ++r){
+        for(int c = 0; c < dst.cols; ++c){
+            int label = labelImage.at<int>(r, c);
+            Vec3b &pixel = dst.at<Vec3b>(r, c);
+            pixel = colors[label];
+         }
+     }
 
     imshow( "Connected Components", dst );
 }
@@ -45,14 +41,14 @@ static void help()
 
 const char* keys =
 {
-    "{@image |stuff.jpg|image for converting to a grayscale}"
+    "{@image|stuff.jpg|image for converting to a grayscale}"
 };
 
 int main( int argc, const char** argv )
 {
     help();
     CommandLineParser parser(argc, argv, keys);
-    string inputImage = parser.get<string>(1);
+    string inputImage = parser.get<string>("@image");
     img = imread(inputImage.c_str(), 0);
 
     if(img.empty())