trying to fix builds

pull/3103/head
Vadim Pisarevsky 10 years ago
parent 257463719b
commit 4530c7ad08
  1. 7
      modules/core/doc/operations_on_arrays.rst
  2. 5
      modules/core/src/lpsolver.cpp
  3. 1
      modules/highgui/include/opencv2/highgui/highgui_c.h
  4. 4
      modules/imgproc/src/filterengine.hpp
  5. 22
      modules/imgproc/test/test_contours.cpp
  6. 3
      modules/photo/doc/denoising.rst
  7. 2
      modules/photo/include/opencv2/photo.hpp

@ -3405,12 +3405,11 @@ and want to compute value of the "virtual" pixel ``Point(-5, 100)`` in a floatin
borderInterpolate(-5, img.cols, BORDER_WRAP));
Normally, the function is not called directly. It is used inside :ocv:class:`FilterEngine`
and :ocv:func:`copyMakeBorder` to compute tables for quick extrapolation.
Normally, the function is not called directly. It is used inside filtering functions
and also in :ocv:func:`copyMakeBorder`.
.. seealso::
:ocv:class:`FilterEngine`,
:ocv:func:`copyMakeBorder`
@ -3443,7 +3442,7 @@ Forms a border around an image.
The function copies the source image into the middle of the destination image. The areas to the
left, to the right, above and below the copied source image will be filled with extrapolated pixels.
This is not what :ocv:class:`FilterEngine` or filtering functions based on it do (they extrapolate
This is not what filtering functions based on it do (they extrapolate
pixels on-fly), but what other more complex functions, including your own, may do to simplify image
boundary handling.

@ -46,8 +46,9 @@
#define dprintf(x)
#define print_matrix(x)
namespace cv{
namespace cv
{
using std::vector;
#ifdef ALEX_DEBUG

@ -43,6 +43,7 @@
#define __OPENCV_HIGHGUI_H__
#include "opencv2/core/core_c.h"
#include "opencv2/imgproc/imgproc_c.h"
#include "opencv2/imgcodecs/imgcodecs_c.h"
#include "opencv2/videoio/videoio_c.h"

@ -48,8 +48,8 @@ enum
KERNEL_ASYMMETRICAL = 2, // kernel[i] == -kernel[ksize-i-1] , and the anchor is at the center
KERNEL_SMOOTH = 4, // all the kernel elements are non-negative and summed to 1
KERNEL_INTEGER = 8 // all the kernel coefficients are integer numbers
};
};
/*!
The Base Class for 1D or Row-wise Filters

@ -387,7 +387,27 @@ _exit_:
return code;
}
TEST(Imgproc_FindContours, accuracy) { CV_FindContourTest test; test.safe_run(); }
TEST(Core_Drawing, _914)
{
const int rows = 256;
const int cols = 256;
Mat img(rows, cols, CV_8UC1, Scalar(255));
line(img, Point(0, 10), Point(255, 10), Scalar(0), 2, 4);
line(img, Point(-5, 20), Point(260, 20), Scalar(0), 2, 4);
line(img, Point(10, 0), Point(10, 255), Scalar(0), 2, 4);
double x0 = 0.0/pow(2.0, -2.0);
double x1 = 255.0/pow(2.0, -2.0);
double y = 30.5/pow(2.0, -2.0);
line(img, Point(int(x0), int(y)), Point(int(x1), int(y)), Scalar(0), 2, 4, 2);
int pixelsDrawn = rows*cols - countNonZero(img);
ASSERT_EQ( (3*rows + cols)*3 - 3*9, pixelsDrawn);
}
/* End of file. */

@ -196,7 +196,7 @@ The function converts image to CIELAB colorspace and then separately denoise L a
:ocv:func:`fastNlMeansDenoisingColored`
denoise_TVL1
---------------------------------
@ -240,4 +240,3 @@ into play.
.. [ChambolleEtAl] A. Chambolle, V. Caselles, M. Novaga, D. Cremers and T. Pock, An Introduction to Total Variation for Image Analysis, http://hal.archives-ouvertes.fr/docs/00/43/75/81/PDF/preprint.pdf (pdf)
.. [Mordvintsev] Alexander Mordvintsev, ROF and TV-L1 denoising with Primal-Dual algorithm, http://znah.net/rof-and-tv-l1-denoising-with-primal-dual-algorithm.html (blog entry)

@ -92,7 +92,7 @@ CV_EXPORTS_W void fastNlMeansDenoisingColoredMulti( InputArrayOfArrays srcImgs,
int imgToDenoiseIndex, int temporalWindowSize,
float h = 3, float hColor = 3,
int templateWindowSize = 7, int searchWindowSize = 21);
CV_EXPORTS_W void denoise_TVL1(const std::vector<Mat>& observations,Mat& result, double lambda=1.0, int niters=30);
enum { LDR_SIZE = 256 };

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