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Commit 97d602ff authored by Bellaktris's avatar Bellaktris
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some warnings and compmilation error fixed

parent cdba517e
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Showing with 50 additions and 63 deletions
modules/ximpgroc/CMakeLists.txt
View file @ 97d602ff
set(the_description "Advanced edge-detection algorithms")
ocv_warnings_disable(CMAKE_CXX_FLAGS -Wundef -Wshadow)
ocv_define_module(ximpgroc opencv_core opencv_imgproc OPTIONAL opencv_highgui)
modules/xphoto/CMakeLists.txt
View file @ 97d602ff
set(the_description "Addon to basic photo module")
ocv_warnings_disable(CMAKE_CXX_FLAGS -Wundef)
ocv_define_module(xphoto opencv_core opencv_imgproc opencv_stitching OPTIONAL opencv_photo opencv_highgui)
\ No newline at end of file
modules/xphoto/doc/colorbalance/whitebalance.rst
View file @ 97d602ff
......@@ -7,7 +7,7 @@ balanceWhite
------------
.. ocv:function:: (const Mat &src, Mat &dst, const int algorithmType,
const float inputMin = 0.0f, const float inputMax = 255.0f,
const float outputMin = 0.0f, const float outputMax = 255.0f);
const float outputMin = 0.0f, const float outputMax = 255.0f)
The function implements different algorithm of automatic white balance, i.e.
it tries to map image's white color to perceptual white (this can be violated
......@@ -20,6 +20,7 @@ due to specific illumination or camera settings).
smart histogram adjustments
(ignoring 4% pixels with minimal
and maximal values) for each channel.
:param inputMin : minimum value in the input image
:param inputMax : maximum value in the input image
:param outputMin : minimum value in the output image
......
modules/xphoto/doc/denoising/denoising.rst
View file @ 97d602ff
......@@ -5,7 +5,7 @@ Image denoising techniques
dctDenoising
------------
.. ocv:function:: (const Mat &src, Mat &dst, const float sigma);
.. ocv:function:: (const Mat &src, Mat &dst, const float sigma)
The function implements simple dct-based denoising,
link: http://www.ipol.im/pub/art/2011/ys-dct/.
......
modules/xphoto/src/algo.hpp
View file @ 97d602ff
......@@ -43,10 +43,11 @@
#include <vector>
#include <algorithm>
#include <cmath>
#include <limits>
template <typename Tp> static inline int min_idx(std::vector <Tp> vec)
{
return std::min_element(vec.begin(), vec.end()) - vec.begin();
return int( std::min_element(vec.begin(), vec.end()) - vec.begin() );
}
static inline int hamming_length(int x)
......
modules/xphoto/src/dct_image_denoising.cpp
View file @ 97d602ff
......@@ -128,21 +128,12 @@ namespace cv
{
CV_Assert( src.type() == CV_MAKE_TYPE(CV_32F, 3) );
float M[] = {cvInvSqrt(3), cvInvSqrt(3), cvInvSqrt(3),
cvInvSqrt(2), 0.0f, -cvInvSqrt(2),
cvInvSqrt(6), -2.0f*cvInvSqrt(6), cvInvSqrt(6)};
Mat m = Mat_<float>(3, 3) << (cvInvSqrt(3), cvInvSqrt(3), cvInvSqrt(3),
cvInvSqrt(2), 0.0f, -cvInvSqrt(2),
cvInvSqrt(6), -2.0f*cvInvSqrt(6), cvInvSqrt(6));
Mat_<Vec3f>::iterator outIt = dst.begin<Vec3f>();
cv::transform(src, dst, m);
for (Mat_<Vec3f>::const_iterator it = src.begin<Vec3f>(); it != src.end<Vec3f>(); ++it, ++outIt)
{
Vec3f rgb = *it;
*outIt = Vec3f(M[0]*rgb[0] + M[1]*rgb[1] + M[2]*rgb[2],
M[3]*rgb[0] + M[4]*rgb[1] + M[5]*rgb[2],
M[6]*rgb[0] + M[7]*rgb[1] + M[8]*rgb[2]);
}
/*************************************/
std::vector <Mat> mv;
split(dst, mv);
......@@ -150,15 +141,8 @@ namespace cv
grayDctDenoising(mv[i], mv[i], sigma, psize);
merge(mv, dst);
/*************************************/
for (Mat_<Vec3f>::iterator it = dst.begin<Vec3f>(); it != dst.end<Vec3f>(); ++it)
{
Vec3f rgb = *it;
*it = Vec3f(M[0]*rgb[0] + M[3]*rgb[1] + M[6]*rgb[2],
M[1]*rgb[0] + M[4]*rgb[1] + M[7]*rgb[2],
M[2]*rgb[0] + M[5]*rgb[1] + M[8]*rgb[2]);
}
cv::transform( dst, dst, m.inv() );
}
/*! This function implements simple dct-based image denoising,
......@@ -182,7 +166,8 @@ namespace cv
else if ( img.type() == CV_32FC1 )
grayDctDenoising( img, img, sigma, psize );
else
CV_Assert( false );
CV_Error_( CV_StsNotImplemented,
("Unsupported source image format (=%d)", img.type()) );
img.convertTo( dst, src.type() );
}
......
modules/xphoto/src/inpainting.cpp
View file @ 97d602ff
......@@ -64,16 +64,16 @@ namespace cv
static void shiftMapInpaint(const Mat &src, const Mat &mask, Mat &dst)
{
const int nTransform = 60; // number of dominant transforms for stitching
const int psize = 8; // single ANNF patch size
//const int psize = 8; // single ANNF patch size
/** ANNF computation **/
srand( time(NULL) );
srand( unsigned int(time(NULL)) );
std::vector <Matx33f> transforms; // dominant transforms
for (int i = 0; i < nTransform; ++i)
{
float dx = rand()%src.cols - src.cols/2;
float dy = rand()%src.rows - src.rows/2;
float dx = float( rand()%src.cols - src.cols/2 );
float dy = float( rand()%src.rows - src.rows/2 );
transforms.push_back( Matx33f( 1, 0, dx,
0, 1, dy,
0, 0, 1) );
......@@ -117,7 +117,8 @@ namespace cv
shiftMapInpaint <Tp, cn>(src, mask, dst);
break;
default:
CV_Assert( false );
CV_Error_( CV_StsNotImplemented,
("Unsupported algorithm type (=%d)", algorithmType) );
break;
}
}
......@@ -196,7 +197,9 @@ namespace cv
inpaint <double, 4>( src, mask, dst, algorithmType );
break;
default:
CV_Assert( false );
CV_Error_( CV_StsNotImplemented,
("Unsupported source image format (=%d)",
src.type()) );
break;
}
}
......
modules/xphoto/src/photomontage.hpp
View file @ 97d602ff
......@@ -90,7 +90,7 @@ protected:
virtual void setWeights(GCGraph <double> &graph, const cv::Point &pA, const cv::Point &pB, const int lA, const int lB, const int lX);
public:
Photomontage(const std::vector <cv::Mat> &images, const std::vector <cv::Mat> &masks, bool multiscale = true);
Photomontage(const std::vector <cv::Mat> &images, const std::vector <cv::Mat> &masks);
virtual ~Photomontage(){};
void assignLabeling(cv::Mat &img);
......@@ -109,36 +109,36 @@ setWeights(GCGraph <double> &graph, const cv::Point &pA, const cv::Point &pB, co
if (lA == lB)
{
/** Link from A to B **/
double weightAB = dist( images[lA].at<Tp>(pA),
images[lA].at<Tp>(pB),
images[lX].at<Tp>(pA),
images[lX].at<Tp>(pB) );
graph.addEdges(pA.y*width + pA.x, pB.y*width + pB.x, weightAB, weightAB);
double weightAB = dist( typename images[lA].at<Tp>(pA),
typename images[lA].at<Tp>(pB),
typename images[lX].at<Tp>(pA),
typename images[lX].at<Tp>(pB) );
graph.addEdges( int(pA.y*width + pA.x), int(pB.y*width + pB.x), weightAB, weightAB);
}
else
{
int X = graph.addVtx();
/** Link from X to sink **/
double weightXS = dist( images[lA].at<Tp>(pA),
images[lA].at<Tp>(pB),
images[lB].at<Tp>(pA),
images[lB].at<Tp>(pB) );
double weightXS = dist( typename images[lA].at<Tp>(pA),
typename images[lA].at<Tp>(pB),
typename images[lB].at<Tp>(pA),
typename images[lB].at<Tp>(pB) );
graph.addTermWeights(X, 0, weightXS);
/** Link from A to X **/
double weightAX = dist( images[lA].at<Tp>(pA),
images[lA].at<Tp>(pB),
images[lX].at<Tp>(pA),
images[lX].at<Tp>(pB) );
graph.addEdges(pA.y*width + pA.x, X, weightAX, weightAX);
double weightAX = dist( typename images[lA].at<Tp>(pA),
typename images[lA].at<Tp>(pB),
typename images[lX].at<Tp>(pA),
typename images[lX].at<Tp>(pB) );
graph.addEdges( int(pA.y*width + pA.x), X, weightAX, weightAX);
/** Link from X to B **/
double weightXB = dist( images[lX].at<Tp>(pA),
images[lX].at<Tp>(pB),
images[lB].at<Tp>(pA),
images[lB].at<Tp>(pB) );
graph.addEdges(X, pB.y*width + pB.x, weightXB, weightXB);
double weightXB = dist( typename images[lX].at<Tp>(pA),
typename images[lX].at<Tp>(pB),
typename images[lB].at<Tp>(pA),
typename images[lB].at<Tp>(pB) );
graph.addEdges(X, int(pB.y*width + pB.x), weightXB, weightXB);
}
}
......@@ -151,8 +151,8 @@ singleExpansion(const int alpha)
/** Terminal links **/
for (int i = 0; i < height; ++i)
{
const uchar *maskAlphaRow = masks[alpha].ptr <uchar>(i);
const int *labelRow = (const int *) x_i.ptr <int>(i);
typename const uchar *maskAlphaRow = masks[alpha].ptr <uchar>(i);
typename const int *labelRow = (const int *) x_i.ptr <int>(i);
for (int j = 0; j < width; ++j)
graph.addTermWeights( graph.addVtx(),
......@@ -163,8 +163,8 @@ singleExpansion(const int alpha)
/** Neighbor links **/
for (int i = 0; i < height - 1; ++i)
{
const int *currentRow = (const int *) x_i.ptr <int>(i);
const int *nextRow = (const int *) x_i.ptr <int>(i + 1);
typename const int *currentRow = (const int *) x_i.ptr <int>(i);
typename const int *nextRow = (const int *) x_i.ptr <int>(i + 1);
for (int j = 0; j < width - 1; ++j)
{
......@@ -188,8 +188,8 @@ singleExpansion(const int alpha)
labelings[alpha].create( height, width, CV_32SC1 );
for (int i = 0; i < height; ++i)
{
const int *inRow = (const int *) x_i.ptr <int>(i);
int *outRow = (int *) labelings[alpha].ptr <int>(i);
typename const int *inRow = (const int *) x_i.ptr <int>(i);
typename int *outRow = (int *) labelings[alpha].ptr <int>(i);
for (int j = 0; j < width; ++j)
outRow[j] = graph.inSourceSegment(i*width + j) ? inRow[j] : alpha;
......@@ -242,11 +242,11 @@ assignResImage(cv::Mat &img)
}
template <typename Tp> Photomontage <Tp>::
Photomontage(const std::vector <cv::Mat> &images, const std::vector <cv::Mat> &masks, const bool multiscale)
Photomontage(const std::vector <cv::Mat> &images, const std::vector <cv::Mat> &masks)
:
images(images), masks(masks), height(images[0].rows), width(images[0].cols),
images(images), masks(masks), height(int(images[0].rows)), width(int(images[0].cols)),
type(images[0].type()), x_i(height, width, CV_32SC1), channels(images[0].channels()),
lsize(images.size()), labelings(images.size()), distances(images.size())
lsize(int(images.size())), labelings(images.size()), distances(images.size())
{
CV_Assert(images[0].depth() != CV_8U && masks[0].depth() == CV_8U);
}
......
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