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Merge branch '2.4'

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This commit is contained in:
Andrey Kamaev
2013-01-30 15:12:50 +04:00
parent 78a338159d 52b32ba8f0
commit 7572b4d400
31 changed files with 816 additions and 421 deletions
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1
doc/tutorials/features2d/feature_description/feature_description.rst
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@@ -32,6 +32,7 @@ This tutorial code's is shown lines below. You can also download it from `here <
#include "opencv2/core/core.hpp"
#include "opencv2/features2d/features2d.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/nonfree/features2d.hpp"
using namespace cv;

123
doc/tutorials/features2d/trackingmotion/generic_corner_detector/generic_corner_detector.rst
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@@ -22,127 +22,8 @@ Code
This tutorial code's is shown lines below. You can also download it from `here <http://code.opencv.org/projects/opencv/repository/revisions/master/raw/samples/cpp/tutorial_code/TrackingMotion/cornerDetector_Demo.cpp>`_
.. code-block:: cpp
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <iostream>
#include <stdio.h>
#include <stdlib.h>
using namespace cv;
using namespace std;
/// Global variables
Mat src, src_gray;
Mat myHarris_dst; Mat myHarris_copy; Mat Mc;
Mat myShiTomasi_dst; Mat myShiTomasi_copy;
int myShiTomasi_qualityLevel = 50;
int myHarris_qualityLevel = 50;
int max_qualityLevel = 100;
double myHarris_minVal; double myHarris_maxVal;
double myShiTomasi_minVal; double myShiTomasi_maxVal;
RNG rng(12345);
char* myHarris_window = "My Harris corner detector";
char* myShiTomasi_window = "My Shi Tomasi corner detector";
/// Function headers
void myShiTomasi_function( int, void* );
void myHarris_function( int, void* );
/** @function main */
int main( int argc, char** argv )
{
/// Load source image and convert it to gray
src = imread( argv[1], 1 );
cvtColor( src, src_gray, CV_BGR2GRAY );
/// Set some parameters
int blockSize = 3; int apertureSize = 3;
/// My Harris matrix -- Using cornerEigenValsAndVecs
myHarris_dst = Mat::zeros( src_gray.size(), CV_32FC(6) );
Mc = Mat::zeros( src_gray.size(), CV_32FC1 );
cornerEigenValsAndVecs( src_gray, myHarris_dst, blockSize, apertureSize, BORDER_DEFAULT );
/* calculate Mc */
for( int j = 0; j < src_gray.rows; j++ )
{ for( int i = 0; i < src_gray.cols; i++ )
{
float lambda_1 = myHarris_dst.at<float>( j, i, 0 );
float lambda_2 = myHarris_dst.at<float>( j, i, 1 );
Mc.at<float>(j,i) = lambda_1*lambda_2 - 0.04*pow( ( lambda_1 + lambda_2 ), 2 );
}
}
minMaxLoc( Mc, &myHarris_minVal, &myHarris_maxVal, 0, 0, Mat() );
/* Create Window and Trackbar */
namedWindow( myHarris_window, CV_WINDOW_AUTOSIZE );
createTrackbar( " Quality Level:", myHarris_window, &myHarris_qualityLevel, max_qualityLevel,
myHarris_function );
myHarris_function( 0, 0 );
/// My Shi-Tomasi -- Using cornerMinEigenVal
myShiTomasi_dst = Mat::zeros( src_gray.size(), CV_32FC1 );
cornerMinEigenVal( src_gray, myShiTomasi_dst, blockSize, apertureSize, BORDER_DEFAULT );
minMaxLoc( myShiTomasi_dst, &myShiTomasi_minVal, &myShiTomasi_maxVal, 0, 0, Mat() );
/* Create Window and Trackbar */
namedWindow( myShiTomasi_window, CV_WINDOW_AUTOSIZE );
createTrackbar( " Quality Level:", myShiTomasi_window, &myShiTomasi_qualityLevel, max_qualityLevel,
myShiTomasi_function );
myShiTomasi_function( 0, 0 );
waitKey(0);
return(0);
}
/** @function myShiTomasi_function */
void myShiTomasi_function( int, void* )
{
myShiTomasi_copy = src.clone();
if( myShiTomasi_qualityLevel < 1 ) { myShiTomasi_qualityLevel = 1; }
for( int j = 0; j < src_gray.rows; j++ )
{ for( int i = 0; i < src_gray.cols; i++ )
{
if( myShiTomasi_dst.at<float>(j,i) > myShiTomasi_minVal + ( myShiTomasi_maxVal -
myShiTomasi_minVal )*myShiTomasi_qualityLevel/max_qualityLevel )
{ circle( myShiTomasi_copy, Point(i,j), 4, Scalar( rng.uniform(0,255),
rng.uniform(0,255), rng.uniform(0,255) ), -1, 8, 0 ); }
}
}
imshow( myShiTomasi_window, myShiTomasi_copy );
}
/** @function myHarris_function */
void myHarris_function( int, void* )
{
myHarris_copy = src.clone();
if( myHarris_qualityLevel < 1 ) { myHarris_qualityLevel = 1; }
for( int j = 0; j < src_gray.rows; j++ )
{ for( int i = 0; i < src_gray.cols; i++ )
{
if( Mc.at<float>(j,i) > myHarris_minVal + ( myHarris_maxVal - myHarris_minVal )
*myHarris_qualityLevel/max_qualityLevel )
{ circle( myHarris_copy, Point(i,j), 4, Scalar( rng.uniform(0,255), rng.uniform(0,255),
rng.uniform(0,255) ), -1, 8, 0 ); }
}
}
imshow( myHarris_window, myHarris_copy );
}
.. literalinclude:: ../../../../../samples/cpp/tutorial_code/TrackingMotion/cornerDetector_Demo.cpp
:language: cpp
Explanation
============

10
doc/tutorials/introduction/load_save_image/load_save_image.rst
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@@ -15,7 +15,7 @@ In this tutorial you will learn how to:
.. container:: enumeratevisibleitemswithsquare
* Load an image using :imread:`imread <>`
* Transform an image from RGB to Grayscale format by using :cvt_color:`cvtColor <>`
* Transform an image from BGR to Grayscale format by using :cvt_color:`cvtColor <>`
* Save your transformed image in a file on disk (using :imwrite:`imwrite <>`)
Code
@@ -45,7 +45,7 @@ Here it is:
}
Mat gray_image;
cvtColor( image, gray_image, CV_RGB2GRAY );
cvtColor( image, gray_image, CV_BGR2GRAY );
imwrite( "../../images/Gray_Image.jpg", gray_image );
@@ -68,11 +68,11 @@ Explanation
* Creating a Mat object to store the image information
* Load an image using :imread:`imread <>`, located in the path given by *imageName*. Fort this example, assume you are loading a RGB image.
#. Now we are going to convert our image from RGB to Grayscale format. OpenCV has a really nice function to do this kind of transformations:
#. Now we are going to convert our image from BGR to Grayscale format. OpenCV has a really nice function to do this kind of transformations:
.. code-block:: cpp
cvtColor( image, gray_image, CV_RGB2GRAY );
cvtColor( image, gray_image, CV_BGR2GRAY );
As you can see, :cvt_color:`cvtColor <>` takes as arguments:
@@ -80,7 +80,7 @@ Explanation
* a source image (*image*)
* a destination image (*gray_image*), in which we will save the converted image.
* an additional parameter that indicates what kind of transformation will be performed. In this case we use **CV_RGB2GRAY** (self-explanatory).
* an additional parameter that indicates what kind of transformation will be performed. In this case we use **CV_BGR2GRAY** (because of :imread:`imread <>` has BGR default channel order in case of color images).
#. So now we have our new *gray_image* and want to save it on disk (otherwise it will get lost after the program ends). To save it, we will use a function analagous to :imread:`imread <>`: :imwrite:`imwrite <>`