commit x64 compilation from lulu cause the other branch dont seems to compile properly at home
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@ -40,8 +40,8 @@
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//
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//M*/
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#ifndef __OPENCV_PHOTO_HPP__
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#define __OPENCV_PHOTO_HPP__
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#ifndef OPENCV_PHOTO_HPP
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#define OPENCV_PHOTO_HPP
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#include "opencv2/core.hpp"
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#include "opencv2/imgproc.hpp"
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@ -89,7 +89,7 @@ enum
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/** @brief Restores the selected region in an image using the region neighborhood.
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@param src Input 8-bit 1-channel or 3-channel image.
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@param src Input 8-bit, 16-bit unsigned or 32-bit float 1-channel or 8-bit 3-channel image.
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@param inpaintMask Inpainting mask, 8-bit 1-channel image. Non-zero pixels indicate the area that
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needs to be inpainted.
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@param dst Output image with the same size and type as src .
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@ -107,7 +107,7 @@ objects from still images or video. See <http://en.wikipedia.org/wiki/Inpainting
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- An example using the inpainting technique can be found at
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opencv_source_code/samples/cpp/inpaint.cpp
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- (Python) An example using the inpainting technique can be found at
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opencv_source_code/samples/python2/inpaint.py
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opencv_source_code/samples/python/inpaint.py
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*/
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CV_EXPORTS_W void inpaint( InputArray src, InputArray inpaintMask,
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OutputArray dst, double inpaintRadius, int flags );
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@ -189,7 +189,7 @@ CV_EXPORTS_W void fastNlMeansDenoisingColored( InputArray src, OutputArray dst,
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float h = 3, float hColor = 3,
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int templateWindowSize = 7, int searchWindowSize = 21);
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/** @brief Modification of fastNlMeansDenoising function for images sequence where consequtive images have been
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/** @brief Modification of fastNlMeansDenoising function for images sequence where consecutive images have been
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captured in small period of time. For example video. This version of the function is for grayscale
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images or for manual manipulation with colorspaces. For more details see
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<http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.131.6394>
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@ -216,7 +216,7 @@ CV_EXPORTS_W void fastNlMeansDenoisingMulti( InputArrayOfArrays srcImgs, OutputA
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int imgToDenoiseIndex, int temporalWindowSize,
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float h = 3, int templateWindowSize = 7, int searchWindowSize = 21);
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/** @brief Modification of fastNlMeansDenoising function for images sequence where consequtive images have been
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/** @brief Modification of fastNlMeansDenoising function for images sequence where consecutive images have been
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captured in small period of time. For example video. This version of the function is for grayscale
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images or for manual manipulation with colorspaces. For more details see
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<http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.131.6394>
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@ -376,43 +376,6 @@ results, default value is 0.85.
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*/
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CV_EXPORTS_W Ptr<TonemapDrago> createTonemapDrago(float gamma = 1.0f, float saturation = 1.0f, float bias = 0.85f);
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/** @brief This algorithm decomposes image into two layers: base layer and detail layer using bilateral filter
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and compresses contrast of the base layer thus preserving all the details.
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This implementation uses regular bilateral filter from opencv.
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Saturation enhancement is possible as in ocvTonemapDrago.
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For more information see @cite DD02 .
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*/
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class CV_EXPORTS_W TonemapDurand : public Tonemap
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{
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public:
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CV_WRAP virtual float getSaturation() const = 0;
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CV_WRAP virtual void setSaturation(float saturation) = 0;
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CV_WRAP virtual float getContrast() const = 0;
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CV_WRAP virtual void setContrast(float contrast) = 0;
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CV_WRAP virtual float getSigmaSpace() const = 0;
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CV_WRAP virtual void setSigmaSpace(float sigma_space) = 0;
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CV_WRAP virtual float getSigmaColor() const = 0;
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CV_WRAP virtual void setSigmaColor(float sigma_color) = 0;
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};
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/** @brief Creates TonemapDurand object
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@param gamma gamma value for gamma correction. See createTonemap
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@param contrast resulting contrast on logarithmic scale, i. e. log(max / min), where max and min
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are maximum and minimum luminance values of the resulting image.
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@param saturation saturation enhancement value. See createTonemapDrago
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@param sigma_space bilateral filter sigma in color space
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@param sigma_color bilateral filter sigma in coordinate space
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*/
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CV_EXPORTS_W Ptr<TonemapDurand>
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createTonemapDurand(float gamma = 1.0f, float contrast = 4.0f, float saturation = 1.0f, float sigma_space = 2.0f, float sigma_color = 2.0f);
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/** @brief This is a global tonemapping operator that models human visual system.
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@ -502,7 +465,7 @@ class CV_EXPORTS_W AlignMTB : public AlignExposures
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{
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public:
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CV_WRAP virtual void process(InputArrayOfArrays src, std::vector<Mat>& dst,
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InputArray times, InputArray response) = 0;
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InputArray times, InputArray response) CV_OVERRIDE = 0;
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/** @brief Short version of process, that doesn't take extra arguments.
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@ -591,7 +554,7 @@ public:
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@param samples number of pixel locations to use
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@param lambda smoothness term weight. Greater values produce smoother results, but can alter the
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response.
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@param random if true sample pixel locations are chosen at random, otherwise the form a
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@param random if true sample pixel locations are chosen at random, otherwise they form a
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rectangular grid.
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*/
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CV_EXPORTS_W Ptr<CalibrateDebevec> createCalibrateDebevec(int samples = 70, float lambda = 10.0f, bool random = false);
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@ -646,7 +609,7 @@ class CV_EXPORTS_W MergeDebevec : public MergeExposures
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{
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public:
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CV_WRAP virtual void process(InputArrayOfArrays src, OutputArray dst,
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InputArray times, InputArray response) = 0;
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InputArray times, InputArray response) CV_OVERRIDE = 0;
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CV_WRAP virtual void process(InputArrayOfArrays src, OutputArray dst, InputArray times) = 0;
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};
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@ -669,7 +632,7 @@ class CV_EXPORTS_W MergeMertens : public MergeExposures
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{
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public:
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CV_WRAP virtual void process(InputArrayOfArrays src, OutputArray dst,
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InputArray times, InputArray response) = 0;
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InputArray times, InputArray response) CV_OVERRIDE = 0;
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/** @brief Short version of process, that doesn't take extra arguments.
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@param src vector of input images
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@ -705,7 +668,7 @@ class CV_EXPORTS_W MergeRobertson : public MergeExposures
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{
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public:
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CV_WRAP virtual void process(InputArrayOfArrays src, OutputArray dst,
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InputArray times, InputArray response) = 0;
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InputArray times, InputArray response) CV_OVERRIDE = 0;
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CV_WRAP virtual void process(InputArrayOfArrays src, OutputArray dst, InputArray times) = 0;
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};
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@ -730,6 +693,9 @@ CV_EXPORTS_W void decolor( InputArray src, OutputArray grayscale, OutputArray co
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//! @addtogroup photo_clone
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//! @{
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/** @example samples/cpp/tutorial_code/photo/seamless_cloning/cloning_demo.cpp
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An example using seamlessClone function
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*/
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/** @brief Image editing tasks concern either global changes (color/intensity corrections, filters,
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deformations) or local changes concerned to a selection. Here we are interested in achieving local
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changes, ones that are restricted to a region manually selected (ROI), in a seamless and effortless
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@ -748,7 +714,7 @@ complex outlines into a new background
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consuming and often leaves an undesirable halo. Seamless cloning, even averaged with the
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original image, is not effective. Mixed seamless cloning based on a loose selection proves
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effective.
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- **FEATURE_EXCHANGE** Feature exchange allows the user to easily replace certain features of
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- **MONOCHROME_TRANSFER** Monochrome transfer allows the user to easily replace certain features of
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one object by alternative features.
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*/
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CV_EXPORTS_W void seamlessClone( InputArray src, InputArray dst, InputArray mask, Point p,
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@ -833,6 +799,9 @@ CV_EXPORTS_W void edgePreservingFilter(InputArray src, OutputArray dst, int flag
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CV_EXPORTS_W void detailEnhance(InputArray src, OutputArray dst, float sigma_s = 10,
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float sigma_r = 0.15f);
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/** @example samples/cpp/tutorial_code/photo/non_photorealistic_rendering/npr_demo.cpp
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An example using non-photorealistic line drawing functions
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*/
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/** @brief Pencil-like non-photorealistic line drawing
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@param src Input 8-bit 3-channel image.
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