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gpuimgproc module for image processing

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Vladislav Vinogradov 2013-04-17 18:14:35 +04:00
parent d569e72ad4
commit e41aea0acf
66 changed files with 889 additions and 404 deletions
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2
modules/gpu/CMakeLists.txt
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@ -4,7 +4,7 @@ endif()
set(the_description "GPU-accelerated Computer Vision")
ocv_add_module(gpu opencv_imgproc opencv_calib3d opencv_objdetect opencv_video opencv_photo opencv_legacy opencv_gpuarithm opencv_gpufilters OPTIONAL opencv_gpunvidia)
ocv_add_module(gpu opencv_imgproc opencv_calib3d opencv_objdetect opencv_video opencv_photo opencv_legacy opencv_gpuarithm opencv_gpufilters opencv_gpuimgproc OPTIONAL opencv_gpunvidia)
ocv_module_include_directories("${CMAKE_CURRENT_SOURCE_DIR}/src/cuda")

1
modules/gpu/doc/gpu.rst
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@ -8,7 +8,6 @@ gpu. GPU-accelerated Computer Vision
introduction
initalization_and_information
data_structures
image_processing
object_detection
feature_detection_and_description
camera_calibration_and_3d_reconstruction

377
modules/gpu/include/opencv2/gpu.hpp
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@ -52,6 +52,8 @@
#include "opencv2/core/gpumat.hpp"
#include "opencv2/gpuarithm.hpp"
#include "opencv2/gpufilters.hpp"
#include "opencv2/gpuimgproc.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/objdetect.hpp"
#include "opencv2/features2d.hpp"
@ -60,280 +62,7 @@ namespace cv { namespace gpu {
////////////////////////////// Image processing //////////////////////////////
enum { ALPHA_OVER, ALPHA_IN, ALPHA_OUT, ALPHA_ATOP, ALPHA_XOR, ALPHA_PLUS, ALPHA_OVER_PREMUL, ALPHA_IN_PREMUL, ALPHA_OUT_PREMUL,
ALPHA_ATOP_PREMUL, ALPHA_XOR_PREMUL, ALPHA_PLUS_PREMUL, ALPHA_PREMUL};
//! Composite two images using alpha opacity values contained in each image
//! Supports CV_8UC4, CV_16UC4, CV_32SC4 and CV_32FC4 types
CV_EXPORTS void alphaComp(const GpuMat& img1, const GpuMat& img2, GpuMat& dst, int alpha_op, Stream& stream = Stream::Null());
//! DST[x,y] = SRC[xmap[x,y],ymap[x,y]]
//! supports only CV_32FC1 map type
CV_EXPORTS void remap(const GpuMat& src, GpuMat& dst, const GpuMat& xmap, const GpuMat& ymap,
int interpolation, int borderMode = BORDER_CONSTANT, Scalar borderValue = Scalar(),
Stream& stream = Stream::Null());
//! Does mean shift filtering on GPU.
CV_EXPORTS void meanShiftFiltering(const GpuMat& src, GpuMat& dst, int sp, int sr,
TermCriteria criteria = TermCriteria(TermCriteria::MAX_ITER + TermCriteria::EPS, 5, 1),
Stream& stream = Stream::Null());
//! Does mean shift procedure on GPU.
CV_EXPORTS void meanShiftProc(const GpuMat& src, GpuMat& dstr, GpuMat& dstsp, int sp, int sr,
TermCriteria criteria = TermCriteria(TermCriteria::MAX_ITER + TermCriteria::EPS, 5, 1),
Stream& stream = Stream::Null());
//! Does mean shift segmentation with elimination of small regions.
CV_EXPORTS void meanShiftSegmentation(const GpuMat& src, Mat& dst, int sp, int sr, int minsize,
TermCriteria criteria = TermCriteria(TermCriteria::MAX_ITER + TermCriteria::EPS, 5, 1));
//! Does coloring of disparity image: [0..ndisp) -> [0..240, 1, 1] in HSV.
//! Supported types of input disparity: CV_8U, CV_16S.
//! Output disparity has CV_8UC4 type in BGRA format (alpha = 255).
CV_EXPORTS void drawColorDisp(const GpuMat& src_disp, GpuMat& dst_disp, int ndisp, Stream& stream = Stream::Null());
//! Reprojects disparity image to 3D space.
//! Supports CV_8U and CV_16S types of input disparity.
//! The output is a 3- or 4-channel floating-point matrix.
//! Each element of this matrix will contain the 3D coordinates of the point (x,y,z,1), computed from the disparity map.
//! Q is the 4x4 perspective transformation matrix that can be obtained with cvStereoRectify.
CV_EXPORTS void reprojectImageTo3D(const GpuMat& disp, GpuMat& xyzw, const Mat& Q, int dst_cn = 4, Stream& stream = Stream::Null());
//! converts image from one color space to another
CV_EXPORTS void cvtColor(const GpuMat& src, GpuMat& dst, int code, int dcn = 0, Stream& stream = Stream::Null());
enum
{
// Bayer Demosaicing (Malvar, He, and Cutler)
COLOR_BayerBG2BGR_MHT = 256,
COLOR_BayerGB2BGR_MHT = 257,
COLOR_BayerRG2BGR_MHT = 258,
COLOR_BayerGR2BGR_MHT = 259,
COLOR_BayerBG2RGB_MHT = COLOR_BayerRG2BGR_MHT,
COLOR_BayerGB2RGB_MHT = COLOR_BayerGR2BGR_MHT,
COLOR_BayerRG2RGB_MHT = COLOR_BayerBG2BGR_MHT,
COLOR_BayerGR2RGB_MHT = COLOR_BayerGB2BGR_MHT,
COLOR_BayerBG2GRAY_MHT = 260,
COLOR_BayerGB2GRAY_MHT = 261,
COLOR_BayerRG2GRAY_MHT = 262,
COLOR_BayerGR2GRAY_MHT = 263
};
CV_EXPORTS void demosaicing(const GpuMat& src, GpuMat& dst, int code, int dcn = -1, Stream& stream = Stream::Null());
//! swap channels
//! dstOrder - Integer array describing how channel values are permutated. The n-th entry
//! of the array contains the number of the channel that is stored in the n-th channel of
//! the output image. E.g. Given an RGBA image, aDstOrder = [3,2,1,0] converts this to ABGR
//! channel order.
CV_EXPORTS void swapChannels(GpuMat& image, const int dstOrder[4], Stream& stream = Stream::Null());
//! Routines for correcting image color gamma
CV_EXPORTS void gammaCorrection(const GpuMat& src, GpuMat& dst, bool forward = true, Stream& stream = Stream::Null());
//! resizes the image
//! Supports INTER_NEAREST, INTER_LINEAR, INTER_CUBIC, INTER_AREA
CV_EXPORTS void resize(const GpuMat& src, GpuMat& dst, Size dsize, double fx=0, double fy=0, int interpolation = INTER_LINEAR, Stream& stream = Stream::Null());
//! warps the image using affine transformation
//! Supports INTER_NEAREST, INTER_LINEAR, INTER_CUBIC
CV_EXPORTS void warpAffine(const GpuMat& src, GpuMat& dst, const Mat& M, Size dsize, int flags = INTER_LINEAR,
int borderMode = BORDER_CONSTANT, Scalar borderValue = Scalar(), Stream& stream = Stream::Null());
CV_EXPORTS void buildWarpAffineMaps(const Mat& M, bool inverse, Size dsize, GpuMat& xmap, GpuMat& ymap, Stream& stream = Stream::Null());
//! warps the image using perspective transformation
//! Supports INTER_NEAREST, INTER_LINEAR, INTER_CUBIC
CV_EXPORTS void warpPerspective(const GpuMat& src, GpuMat& dst, const Mat& M, Size dsize, int flags = INTER_LINEAR,
int borderMode = BORDER_CONSTANT, Scalar borderValue = Scalar(), Stream& stream = Stream::Null());
CV_EXPORTS void buildWarpPerspectiveMaps(const Mat& M, bool inverse, Size dsize, GpuMat& xmap, GpuMat& ymap, Stream& stream = Stream::Null());
//! builds plane warping maps
CV_EXPORTS void buildWarpPlaneMaps(Size src_size, Rect dst_roi, const Mat &K, const Mat& R, const Mat &T, float scale,
GpuMat& map_x, GpuMat& map_y, Stream& stream = Stream::Null());
//! builds cylindrical warping maps
CV_EXPORTS void buildWarpCylindricalMaps(Size src_size, Rect dst_roi, const Mat &K, const Mat& R, float scale,
GpuMat& map_x, GpuMat& map_y, Stream& stream = Stream::Null());
//! builds spherical warping maps
CV_EXPORTS void buildWarpSphericalMaps(Size src_size, Rect dst_roi, const Mat &K, const Mat& R, float scale,
GpuMat& map_x, GpuMat& map_y, Stream& stream = Stream::Null());
//! rotates an image around the origin (0,0) and then shifts it
//! supports INTER_NEAREST, INTER_LINEAR, INTER_CUBIC
//! supports 1, 3 or 4 channels images with CV_8U, CV_16U or CV_32F depth
CV_EXPORTS void rotate(const GpuMat& src, GpuMat& dst, Size dsize, double angle, double xShift = 0, double yShift = 0,
int interpolation = INTER_LINEAR, Stream& stream = Stream::Null());
//! computes Harris cornerness criteria at each image pixel
CV_EXPORTS void cornerHarris(const GpuMat& src, GpuMat& dst, int blockSize, int ksize, double k, int borderType = BORDER_REFLECT101);
CV_EXPORTS void cornerHarris(const GpuMat& src, GpuMat& dst, GpuMat& Dx, GpuMat& Dy, int blockSize, int ksize, double k, int borderType = BORDER_REFLECT101);
CV_EXPORTS void cornerHarris(const GpuMat& src, GpuMat& dst, GpuMat& Dx, GpuMat& Dy, GpuMat& buf, int blockSize, int ksize, double k,
int borderType = BORDER_REFLECT101, Stream& stream = Stream::Null());
//! computes minimum eigen value of 2x2 derivative covariation matrix at each pixel - the cornerness criteria
CV_EXPORTS void cornerMinEigenVal(const GpuMat& src, GpuMat& dst, int blockSize, int ksize, int borderType=BORDER_REFLECT101);
CV_EXPORTS void cornerMinEigenVal(const GpuMat& src, GpuMat& dst, GpuMat& Dx, GpuMat& Dy, int blockSize, int ksize, int borderType=BORDER_REFLECT101);
CV_EXPORTS void cornerMinEigenVal(const GpuMat& src, GpuMat& dst, GpuMat& Dx, GpuMat& Dy, GpuMat& buf, int blockSize, int ksize,
int borderType=BORDER_REFLECT101, Stream& stream = Stream::Null());
struct CV_EXPORTS MatchTemplateBuf
{
Size user_block_size;
GpuMat imagef, templf;
std::vector<GpuMat> images;
std::vector<GpuMat> image_sums;
std::vector<GpuMat> image_sqsums;
};
//! computes the proximity map for the raster template and the image where the template is searched for
CV_EXPORTS void matchTemplate(const GpuMat& image, const GpuMat& templ, GpuMat& result, int method, Stream &stream = Stream::Null());
//! computes the proximity map for the raster template and the image where the template is searched for
CV_EXPORTS void matchTemplate(const GpuMat& image, const GpuMat& templ, GpuMat& result, int method, MatchTemplateBuf &buf, Stream& stream = Stream::Null());
//! smoothes the source image and downsamples it
CV_EXPORTS void pyrDown(const GpuMat& src, GpuMat& dst, Stream& stream = Stream::Null());
//! upsamples the source image and then smoothes it
CV_EXPORTS void pyrUp(const GpuMat& src, GpuMat& dst, Stream& stream = Stream::Null());
//! performs linear blending of two images
//! to avoid accuracy errors sum of weigths shouldn't be very close to zero
CV_EXPORTS void blendLinear(const GpuMat& img1, const GpuMat& img2, const GpuMat& weights1, const GpuMat& weights2,
GpuMat& result, Stream& stream = Stream::Null());
//! Performa bilateral filtering of passsed image
CV_EXPORTS void bilateralFilter(const GpuMat& src, GpuMat& dst, int kernel_size, float sigma_color, float sigma_spatial,
int borderMode = BORDER_DEFAULT, Stream& stream = Stream::Null());
//! Brute force non-local means algorith (slow but universal)
CV_EXPORTS void nonLocalMeans(const GpuMat& src, GpuMat& dst, float h, int search_window = 21, int block_size = 7, int borderMode = BORDER_DEFAULT, Stream& s = Stream::Null());
//! Fast (but approximate)version of non-local means algorith similar to CPU function (running sums technique)
class CV_EXPORTS FastNonLocalMeansDenoising
{
public:
//! Simple method, recommended for grayscale images (though it supports multichannel images)
void simpleMethod(const GpuMat& src, GpuMat& dst, float h, int search_window = 21, int block_size = 7, Stream& s = Stream::Null());
//! Processes luminance and color components separatelly
void labMethod(const GpuMat& src, GpuMat& dst, float h_luminance, float h_color, int search_window = 21, int block_size = 7, Stream& s = Stream::Null());
private:
GpuMat buffer, extended_src_buffer;
GpuMat lab, l, ab;
};
struct CV_EXPORTS CannyBuf
{
void create(const Size& image_size, int apperture_size = 3);
void release();
GpuMat dx, dy;
GpuMat mag;
GpuMat map;
GpuMat st1, st2;
Ptr<FilterEngine_GPU> filterDX, filterDY;
};
CV_EXPORTS void Canny(const GpuMat& image, GpuMat& edges, double low_thresh, double high_thresh, int apperture_size = 3, bool L2gradient = false);
CV_EXPORTS void Canny(const GpuMat& image, CannyBuf& buf, GpuMat& edges, double low_thresh, double high_thresh, int apperture_size = 3, bool L2gradient = false);
CV_EXPORTS void Canny(const GpuMat& dx, const GpuMat& dy, GpuMat& edges, double low_thresh, double high_thresh, bool L2gradient = false);
CV_EXPORTS void Canny(const GpuMat& dx, const GpuMat& dy, CannyBuf& buf, GpuMat& edges, double low_thresh, double high_thresh, bool L2gradient = false);
class CV_EXPORTS ImagePyramid
{
public:
inline ImagePyramid() : nLayers_(0) {}
inline ImagePyramid(const GpuMat& img, int nLayers, Stream& stream = Stream::Null())
{
build(img, nLayers, stream);
}
void build(const GpuMat& img, int nLayers, Stream& stream = Stream::Null());
void getLayer(GpuMat& outImg, Size outRoi, Stream& stream = Stream::Null()) const;
inline void release()
{
layer0_.release();
pyramid_.clear();
nLayers_ = 0;
}
private:
GpuMat layer0_;
std::vector<GpuMat> pyramid_;
int nLayers_;
};
//! HoughLines
struct HoughLinesBuf
{
GpuMat accum;
GpuMat list;
};
CV_EXPORTS void HoughLines(const GpuMat& src, GpuMat& lines, float rho, float theta, int threshold, bool doSort = false, int maxLines = 4096);
CV_EXPORTS void HoughLines(const GpuMat& src, GpuMat& lines, HoughLinesBuf& buf, float rho, float theta, int threshold, bool doSort = false, int maxLines = 4096);
CV_EXPORTS void HoughLinesDownload(const GpuMat& d_lines, OutputArray h_lines, OutputArray h_votes = noArray());
//! HoughLinesP
//! finds line segments in the black-n-white image using probabalistic Hough transform
CV_EXPORTS void HoughLinesP(const GpuMat& image, GpuMat& lines, HoughLinesBuf& buf, float rho, float theta, int minLineLength, int maxLineGap, int maxLines = 4096);
//! HoughCircles
struct HoughCirclesBuf
{
GpuMat edges;
GpuMat accum;
GpuMat list;
CannyBuf cannyBuf;
};
CV_EXPORTS void HoughCircles(const GpuMat& src, GpuMat& circles, int method, float dp, float minDist, int cannyThreshold, int votesThreshold, int minRadius, int maxRadius, int maxCircles = 4096);
CV_EXPORTS void HoughCircles(const GpuMat& src, GpuMat& circles, HoughCirclesBuf& buf, int method, float dp, float minDist, int cannyThreshold, int votesThreshold, int minRadius, int maxRadius, int maxCircles = 4096);
CV_EXPORTS void HoughCirclesDownload(const GpuMat& d_circles, OutputArray h_circles);
//! finds arbitrary template in the grayscale image using Generalized Hough Transform
//! Ballard, D.H. (1981). Generalizing the Hough transform to detect arbitrary shapes. Pattern Recognition 13 (2): 111-122.
//! Guil, N., González-Linares, J.M. and Zapata, E.L. (1999). Bidimensional shape detection using an invariant approach. Pattern Recognition 32 (6): 1025-1038.
class CV_EXPORTS GeneralizedHough_GPU : public cv::Algorithm
{
public:
static Ptr<GeneralizedHough_GPU> create(int method);
virtual ~GeneralizedHough_GPU();
//! set template to search
void setTemplate(const GpuMat& templ, int cannyThreshold = 100, Point templCenter = Point(-1, -1));
void setTemplate(const GpuMat& edges, const GpuMat& dx, const GpuMat& dy, Point templCenter = Point(-1, -1));
//! find template on image
void detect(const GpuMat& image, GpuMat& positions, int cannyThreshold = 100);
void detect(const GpuMat& edges, const GpuMat& dx, const GpuMat& dy, GpuMat& positions);
void download(const GpuMat& d_positions, OutputArray h_positions, OutputArray h_votes = noArray());
void release();
protected:
virtual void setTemplateImpl(const GpuMat& edges, const GpuMat& dx, const GpuMat& dy, Point templCenter) = 0;
virtual void detectImpl(const GpuMat& edges, const GpuMat& dx, const GpuMat& dy, GpuMat& positions) = 0;
virtual void releaseImpl() = 0;
private:
GpuMat edges_;
CannyBuf cannyBuf_;
};
///////////////////////////// Calibration 3D //////////////////////////////////
@ -351,68 +80,11 @@ CV_EXPORTS void solvePnPRansac(const Mat& object, const Mat& image, const Mat& c
//////////////////////////////// Image Labeling ////////////////////////////////
//!performs labeling via graph cuts of a 2D regular 4-connected graph.
CV_EXPORTS void graphcut(GpuMat& terminals, GpuMat& leftTransp, GpuMat& rightTransp, GpuMat& top, GpuMat& bottom, GpuMat& labels,
GpuMat& buf, Stream& stream = Stream::Null());
//!performs labeling via graph cuts of a 2D regular 8-connected graph.
CV_EXPORTS void graphcut(GpuMat& terminals, GpuMat& leftTransp, GpuMat& rightTransp, GpuMat& top, GpuMat& topLeft, GpuMat& topRight,
GpuMat& bottom, GpuMat& bottomLeft, GpuMat& bottomRight,
GpuMat& labels,
GpuMat& buf, Stream& stream = Stream::Null());
//! compute mask for Generalized Flood fill componetns labeling.
CV_EXPORTS void connectivityMask(const GpuMat& image, GpuMat& mask, const cv::Scalar& lo, const cv::Scalar& hi, Stream& stream = Stream::Null());
//! performs connected componnents labeling.
CV_EXPORTS void labelComponents(const GpuMat& mask, GpuMat& components, int flags = 0, Stream& stream = Stream::Null());
////////////////////////////////// Histograms //////////////////////////////////
//! Compute levels with even distribution. levels will have 1 row and nLevels cols and CV_32SC1 type.
CV_EXPORTS void evenLevels(GpuMat& levels, int nLevels, int lowerLevel, int upperLevel);
//! Calculates histogram with evenly distributed bins for signle channel source.
//! Supports CV_8UC1, CV_16UC1 and CV_16SC1 source types.
//! Output hist will have one row and histSize cols and CV_32SC1 type.
CV_EXPORTS void histEven(const GpuMat& src, GpuMat& hist, int histSize, int lowerLevel, int upperLevel, Stream& stream = Stream::Null());
CV_EXPORTS void histEven(const GpuMat& src, GpuMat& hist, GpuMat& buf, int histSize, int lowerLevel, int upperLevel, Stream& stream = Stream::Null());
//! Calculates histogram with evenly distributed bins for four-channel source.
//! All channels of source are processed separately.
//! Supports CV_8UC4, CV_16UC4 and CV_16SC4 source types.
//! Output hist[i] will have one row and histSize[i] cols and CV_32SC1 type.
CV_EXPORTS void histEven(const GpuMat& src, GpuMat hist[4], int histSize[4], int lowerLevel[4], int upperLevel[4], Stream& stream = Stream::Null());
CV_EXPORTS void histEven(const GpuMat& src, GpuMat hist[4], GpuMat& buf, int histSize[4], int lowerLevel[4], int upperLevel[4], Stream& stream = Stream::Null());
//! Calculates histogram with bins determined by levels array.
//! levels must have one row and CV_32SC1 type if source has integer type or CV_32FC1 otherwise.
//! Supports CV_8UC1, CV_16UC1, CV_16SC1 and CV_32FC1 source types.
//! Output hist will have one row and (levels.cols-1) cols and CV_32SC1 type.
CV_EXPORTS void histRange(const GpuMat& src, GpuMat& hist, const GpuMat& levels, Stream& stream = Stream::Null());
CV_EXPORTS void histRange(const GpuMat& src, GpuMat& hist, const GpuMat& levels, GpuMat& buf, Stream& stream = Stream::Null());
//! Calculates histogram with bins determined by levels array.
//! All levels must have one row and CV_32SC1 type if source has integer type or CV_32FC1 otherwise.
//! All channels of source are processed separately.
//! Supports CV_8UC4, CV_16UC4, CV_16SC4 and CV_32FC4 source types.
//! Output hist[i] will have one row and (levels[i].cols-1) cols and CV_32SC1 type.
CV_EXPORTS void histRange(const GpuMat& src, GpuMat hist[4], const GpuMat levels[4], Stream& stream = Stream::Null());
CV_EXPORTS void histRange(const GpuMat& src, GpuMat hist[4], const GpuMat levels[4], GpuMat& buf, Stream& stream = Stream::Null());
//! Calculates histogram for 8u one channel image
//! Output hist will have one row, 256 cols and CV32SC1 type.
CV_EXPORTS void calcHist(const GpuMat& src, GpuMat& hist, Stream& stream = Stream::Null());
CV_EXPORTS void calcHist(const GpuMat& src, GpuMat& hist, GpuMat& buf, Stream& stream = Stream::Null());
//! normalizes the grayscale image brightness and contrast by normalizing its histogram
CV_EXPORTS void equalizeHist(const GpuMat& src, GpuMat& dst, Stream& stream = Stream::Null());
CV_EXPORTS void equalizeHist(const GpuMat& src, GpuMat& dst, GpuMat& hist, Stream& stream = Stream::Null());
CV_EXPORTS void equalizeHist(const GpuMat& src, GpuMat& dst, GpuMat& hist, GpuMat& buf, Stream& stream = Stream::Null());
class CV_EXPORTS CLAHE : public cv::CLAHE
{
public:
using cv::CLAHE::apply;
virtual void apply(InputArray src, OutputArray dst, Stream& stream) = 0;
};
CV_EXPORTS Ptr<cv::gpu::CLAHE> createCLAHE(double clipLimit = 40.0, Size tileGridSize = Size(8, 8));
//////////////////////////////// StereoBM_GPU ////////////////////////////////
@ -1097,52 +769,7 @@ public:
GpuMat buf;
};
class CV_EXPORTS GoodFeaturesToTrackDetector_GPU
{
public:
explicit GoodFeaturesToTrackDetector_GPU(int maxCorners = 1000, double qualityLevel = 0.01, double minDistance = 0.0,
int blockSize = 3, bool useHarrisDetector = false, double harrisK = 0.04);
//! return 1 rows matrix with CV_32FC2 type
void operator ()(const GpuMat& image, GpuMat& corners, const GpuMat& mask = GpuMat());
int maxCorners;
double qualityLevel;
double minDistance;
int blockSize;
bool useHarrisDetector;
double harrisK;
void releaseMemory()
{
Dx_.release();
Dy_.release();
buf_.release();
eig_.release();
minMaxbuf_.release();
tmpCorners_.release();
}
private:
GpuMat Dx_;
GpuMat Dy_;
GpuMat buf_;
GpuMat eig_;
GpuMat minMaxbuf_;
GpuMat tmpCorners_;
};
inline GoodFeaturesToTrackDetector_GPU::GoodFeaturesToTrackDetector_GPU(int maxCorners_, double qualityLevel_, double minDistance_,
int blockSize_, bool useHarrisDetector_, double harrisK_)
{
maxCorners = maxCorners_;
qualityLevel = qualityLevel_;
minDistance = minDistance_;
blockSize = blockSize_;
useHarrisDetector = useHarrisDetector_;
harrisK = harrisK_;
}
class CV_EXPORTS PyrLKOpticalFlow

0
modules/gpu/src/bilateral_filter.cpp → modules/gpu/src/disparity_bilateral_filter.cpp
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2
modules/gpu/test/test_precomp.hpp
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@ -74,8 +74,6 @@
#include "opencv2/ts/gpu_test.hpp"
#include "opencv2/gpu.hpp"
#include "interpolation.hpp"
#include "opencv2/core/gpu_private.hpp"
#endif

0
modules/gpu/test/test_threshold.cpp → modules/gpuarithm/test/test_threshold.cpp
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9
modules/gpuimgproc/CMakeLists.txt Normal file
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@ -0,0 +1,9 @@
if(ANDROID OR IOS)
ocv_module_disable(gpuimgproc)
endif()
set(the_description "GPU-accelerated Image Processing")
ocv_warnings_disable(CMAKE_CXX_FLAGS -Wundef -Wmissing-declarations -Wshadow -Wunused-parameter)
ocv_define_module(gpuimgproc opencv_imgproc opencv_gpuarithm opencv_gpufilters OPTIONAL opencv_photo)

8
modules/gpuimgproc/doc/gpuimgproc.rst Normal file
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@ -0,0 +1,8 @@
*************************************
gpu. GPU-accelerated Image Processing
*************************************
.. toctree::
:maxdepth: 1
image_processing

0
modules/gpu/doc/image_processing.rst → modules/gpuimgproc/doc/image_processing.rst
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441
modules/gpuimgproc/include/opencv2/gpuimgproc.hpp Normal file
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@ -0,0 +1,441 @@
/*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*/
#ifndef __OPENCV_GPUIMGPROC_HPP__
#define __OPENCV_GPUIMGPROC_HPP__
#ifndef __cplusplus
# error gpuimgproc.hpp header must be compiled as C++
#endif
#include "opencv2/core/gpumat.hpp"
#include "opencv2/gpufilters.hpp"
#include "opencv2/imgproc.hpp"
namespace cv { namespace gpu {
enum { ALPHA_OVER, ALPHA_IN, ALPHA_OUT, ALPHA_ATOP, ALPHA_XOR, ALPHA_PLUS, ALPHA_OVER_PREMUL, ALPHA_IN_PREMUL, ALPHA_OUT_PREMUL,
ALPHA_ATOP_PREMUL, ALPHA_XOR_PREMUL, ALPHA_PLUS_PREMUL, ALPHA_PREMUL};
//! Composite two images using alpha opacity values contained in each image
//! Supports CV_8UC4, CV_16UC4, CV_32SC4 and CV_32FC4 types
CV_EXPORTS void alphaComp(const GpuMat& img1, const GpuMat& img2, GpuMat& dst, int alpha_op, Stream& stream = Stream::Null());
//! DST[x,y] = SRC[xmap[x,y],ymap[x,y]]
//! supports only CV_32FC1 map type
CV_EXPORTS void remap(const GpuMat& src, GpuMat& dst, const GpuMat& xmap, const GpuMat& ymap,
int interpolation, int borderMode = BORDER_CONSTANT, Scalar borderValue = Scalar(),
Stream& stream = Stream::Null());
//! Does mean shift filtering on GPU.
CV_EXPORTS void meanShiftFiltering(const GpuMat& src, GpuMat& dst, int sp, int sr,
TermCriteria criteria = TermCriteria(TermCriteria::MAX_ITER + TermCriteria::EPS, 5, 1),
Stream& stream = Stream::Null());
//! Does mean shift procedure on GPU.
CV_EXPORTS void meanShiftProc(const GpuMat& src, GpuMat& dstr, GpuMat& dstsp, int sp, int sr,
TermCriteria criteria = TermCriteria(TermCriteria::MAX_ITER + TermCriteria::EPS, 5, 1),
Stream& stream = Stream::Null());
//! Does mean shift segmentation with elimination of small regions.
CV_EXPORTS void meanShiftSegmentation(const GpuMat& src, Mat& dst, int sp, int sr, int minsize,
TermCriteria criteria = TermCriteria(TermCriteria::MAX_ITER + TermCriteria::EPS, 5, 1));
//! Does coloring of disparity image: [0..ndisp) -> [0..240, 1, 1] in HSV.
//! Supported types of input disparity: CV_8U, CV_16S.
//! Output disparity has CV_8UC4 type in BGRA format (alpha = 255).
CV_EXPORTS void drawColorDisp(const GpuMat& src_disp, GpuMat& dst_disp, int ndisp, Stream& stream = Stream::Null());
//! Reprojects disparity image to 3D space.
//! Supports CV_8U and CV_16S types of input disparity.
//! The output is a 3- or 4-channel floating-point matrix.
//! Each element of this matrix will contain the 3D coordinates of the point (x,y,z,1), computed from the disparity map.
//! Q is the 4x4 perspective transformation matrix that can be obtained with cvStereoRectify.
CV_EXPORTS void reprojectImageTo3D(const GpuMat& disp, GpuMat& xyzw, const Mat& Q, int dst_cn = 4, Stream& stream = Stream::Null());
//! converts image from one color space to another
CV_EXPORTS void cvtColor(const GpuMat& src, GpuMat& dst, int code, int dcn = 0, Stream& stream = Stream::Null());
enum
{
// Bayer Demosaicing (Malvar, He, and Cutler)
COLOR_BayerBG2BGR_MHT = 256,
COLOR_BayerGB2BGR_MHT = 257,
COLOR_BayerRG2BGR_MHT = 258,
COLOR_BayerGR2BGR_MHT = 259,
COLOR_BayerBG2RGB_MHT = COLOR_BayerRG2BGR_MHT,
COLOR_BayerGB2RGB_MHT = COLOR_BayerGR2BGR_MHT,
COLOR_BayerRG2RGB_MHT = COLOR_BayerBG2BGR_MHT,
COLOR_BayerGR2RGB_MHT = COLOR_BayerGB2BGR_MHT,
COLOR_BayerBG2GRAY_MHT = 260,
COLOR_BayerGB2GRAY_MHT = 261,
COLOR_BayerRG2GRAY_MHT = 262,
COLOR_BayerGR2GRAY_MHT = 263
};
CV_EXPORTS void demosaicing(const GpuMat& src, GpuMat& dst, int code, int dcn = -1, Stream& stream = Stream::Null());
//! swap channels
//! dstOrder - Integer array describing how channel values are permutated. The n-th entry
//! of the array contains the number of the channel that is stored in the n-th channel of
//! the output image. E.g. Given an RGBA image, aDstOrder = [3,2,1,0] converts this to ABGR
//! channel order.
CV_EXPORTS void swapChannels(GpuMat& image, const int dstOrder[4], Stream& stream = Stream::Null());
//! Routines for correcting image color gamma
CV_EXPORTS void gammaCorrection(const GpuMat& src, GpuMat& dst, bool forward = true, Stream& stream = Stream::Null());
//! resizes the image
//! Supports INTER_NEAREST, INTER_LINEAR, INTER_CUBIC, INTER_AREA
CV_EXPORTS void resize(const GpuMat& src, GpuMat& dst, Size dsize, double fx=0, double fy=0, int interpolation = INTER_LINEAR, Stream& stream = Stream::Null());
//! warps the image using affine transformation
//! Supports INTER_NEAREST, INTER_LINEAR, INTER_CUBIC
CV_EXPORTS void warpAffine(const GpuMat& src, GpuMat& dst, const Mat& M, Size dsize, int flags = INTER_LINEAR,
int borderMode = BORDER_CONSTANT, Scalar borderValue = Scalar(), Stream& stream = Stream::Null());
CV_EXPORTS void buildWarpAffineMaps(const Mat& M, bool inverse, Size dsize, GpuMat& xmap, GpuMat& ymap, Stream& stream = Stream::Null());
//! warps the image using perspective transformation
//! Supports INTER_NEAREST, INTER_LINEAR, INTER_CUBIC
CV_EXPORTS void warpPerspective(const GpuMat& src, GpuMat& dst, const Mat& M, Size dsize, int flags = INTER_LINEAR,
int borderMode = BORDER_CONSTANT, Scalar borderValue = Scalar(), Stream& stream = Stream::Null());
CV_EXPORTS void buildWarpPerspectiveMaps(const Mat& M, bool inverse, Size dsize, GpuMat& xmap, GpuMat& ymap, Stream& stream = Stream::Null());
//! builds plane warping maps
CV_EXPORTS void buildWarpPlaneMaps(Size src_size, Rect dst_roi, const Mat &K, const Mat& R, const Mat &T, float scale,
GpuMat& map_x, GpuMat& map_y, Stream& stream = Stream::Null());
//! builds cylindrical warping maps
CV_EXPORTS void buildWarpCylindricalMaps(Size src_size, Rect dst_roi, const Mat &K, const Mat& R, float scale,
GpuMat& map_x, GpuMat& map_y, Stream& stream = Stream::Null());
//! builds spherical warping maps
CV_EXPORTS void buildWarpSphericalMaps(Size src_size, Rect dst_roi, const Mat &K, const Mat& R, float scale,
GpuMat& map_x, GpuMat& map_y, Stream& stream = Stream::Null());
//! rotates an image around the origin (0,0) and then shifts it
//! supports INTER_NEAREST, INTER_LINEAR, INTER_CUBIC
//! supports 1, 3 or 4 channels images with CV_8U, CV_16U or CV_32F depth
CV_EXPORTS void rotate(const GpuMat& src, GpuMat& dst, Size dsize, double angle, double xShift = 0, double yShift = 0,
int interpolation = INTER_LINEAR, Stream& stream = Stream::Null());
//! computes Harris cornerness criteria at each image pixel
CV_EXPORTS void cornerHarris(const GpuMat& src, GpuMat& dst, int blockSize, int ksize, double k, int borderType = BORDER_REFLECT101);
CV_EXPORTS void cornerHarris(const GpuMat& src, GpuMat& dst, GpuMat& Dx, GpuMat& Dy, int blockSize, int ksize, double k, int borderType = BORDER_REFLECT101);
CV_EXPORTS void cornerHarris(const GpuMat& src, GpuMat& dst, GpuMat& Dx, GpuMat& Dy, GpuMat& buf, int blockSize, int ksize, double k,
int borderType = BORDER_REFLECT101, Stream& stream = Stream::Null());
//! computes minimum eigen value of 2x2 derivative covariation matrix at each pixel - the cornerness criteria
CV_EXPORTS void cornerMinEigenVal(const GpuMat& src, GpuMat& dst, int blockSize, int ksize, int borderType=BORDER_REFLECT101);
CV_EXPORTS void cornerMinEigenVal(const GpuMat& src, GpuMat& dst, GpuMat& Dx, GpuMat& Dy, int blockSize, int ksize, int borderType=BORDER_REFLECT101);
CV_EXPORTS void cornerMinEigenVal(const GpuMat& src, GpuMat& dst, GpuMat& Dx, GpuMat& Dy, GpuMat& buf, int blockSize, int ksize,
int borderType=BORDER_REFLECT101, Stream& stream = Stream::Null());
struct CV_EXPORTS MatchTemplateBuf
{
Size user_block_size;
GpuMat imagef, templf;
std::vector<GpuMat> images;
std::vector<GpuMat> image_sums;
std::vector<GpuMat> image_sqsums;
};
//! computes the proximity map for the raster template and the image where the template is searched for
CV_EXPORTS void matchTemplate(const GpuMat& image, const GpuMat& templ, GpuMat& result, int method, Stream &stream = Stream::Null());
//! computes the proximity map for the raster template and the image where the template is searched for
CV_EXPORTS void matchTemplate(const GpuMat& image, const GpuMat& templ, GpuMat& result, int method, MatchTemplateBuf &buf, Stream& stream = Stream::Null());
//! smoothes the source image and downsamples it
CV_EXPORTS void pyrDown(const GpuMat& src, GpuMat& dst, Stream& stream = Stream::Null());
//! upsamples the source image and then smoothes it
CV_EXPORTS void pyrUp(const GpuMat& src, GpuMat& dst, Stream& stream = Stream::Null());
//! performs linear blending of two images
//! to avoid accuracy errors sum of weigths shouldn't be very close to zero
CV_EXPORTS void blendLinear(const GpuMat& img1, const GpuMat& img2, const GpuMat& weights1, const GpuMat& weights2,
GpuMat& result, Stream& stream = Stream::Null());
//! Performa bilateral filtering of passsed image
CV_EXPORTS void bilateralFilter(const GpuMat& src, GpuMat& dst, int kernel_size, float sigma_color, float sigma_spatial,
int borderMode = BORDER_DEFAULT, Stream& stream = Stream::Null());
//! Brute force non-local means algorith (slow but universal)
CV_EXPORTS void nonLocalMeans(const GpuMat& src, GpuMat& dst, float h, int search_window = 21, int block_size = 7, int borderMode = BORDER_DEFAULT, Stream& s = Stream::Null());
//! Fast (but approximate)version of non-local means algorith similar to CPU function (running sums technique)
class CV_EXPORTS FastNonLocalMeansDenoising
{
public:
//! Simple method, recommended for grayscale images (though it supports multichannel images)
void simpleMethod(const GpuMat& src, GpuMat& dst, float h, int search_window = 21, int block_size = 7, Stream& s = Stream::Null());
//! Processes luminance and color components separatelly
void labMethod(const GpuMat& src, GpuMat& dst, float h_luminance, float h_color, int search_window = 21, int block_size = 7, Stream& s = Stream::Null());
private:
GpuMat buffer, extended_src_buffer;
GpuMat lab, l, ab;
};
struct CV_EXPORTS CannyBuf
{
void create(const Size& image_size, int apperture_size = 3);
void release();
GpuMat dx, dy;
GpuMat mag;
GpuMat map;
GpuMat st1, st2;
Ptr<FilterEngine_GPU> filterDX, filterDY;
};
CV_EXPORTS void Canny(const GpuMat& image, GpuMat& edges, double low_thresh, double high_thresh, int apperture_size = 3, bool L2gradient = false);
CV_EXPORTS void Canny(const GpuMat& image, CannyBuf& buf, GpuMat& edges, double low_thresh, double high_thresh, int apperture_size = 3, bool L2gradient = false);
CV_EXPORTS void Canny(const GpuMat& dx, const GpuMat& dy, GpuMat& edges, double low_thresh, double high_thresh, bool L2gradient = false);
CV_EXPORTS void Canny(const GpuMat& dx, const GpuMat& dy, CannyBuf& buf, GpuMat& edges, double low_thresh, double high_thresh, bool L2gradient = false);
class CV_EXPORTS ImagePyramid
{
public:
inline ImagePyramid() : nLayers_(0) {}
inline ImagePyramid(const GpuMat& img, int nLayers, Stream& stream = Stream::Null())
{
build(img, nLayers, stream);
}
void build(const GpuMat& img, int nLayers, Stream& stream = Stream::Null());
void getLayer(GpuMat& outImg, Size outRoi, Stream& stream = Stream::Null()) const;
inline void release()
{
layer0_.release();
pyramid_.clear();
nLayers_ = 0;
}
private:
GpuMat layer0_;
std::vector<GpuMat> pyramid_;
int nLayers_;
};
//! HoughLines
struct HoughLinesBuf
{
GpuMat accum;
GpuMat list;
};
CV_EXPORTS void HoughLines(const GpuMat& src, GpuMat& lines, float rho, float theta, int threshold, bool doSort = false, int maxLines = 4096);
CV_EXPORTS void HoughLines(const GpuMat& src, GpuMat& lines, HoughLinesBuf& buf, float rho, float theta, int threshold, bool doSort = false, int maxLines = 4096);
CV_EXPORTS void HoughLinesDownload(const GpuMat& d_lines, OutputArray h_lines, OutputArray h_votes = noArray());
//! HoughLinesP
//! finds line segments in the black-n-white image using probabalistic Hough transform
CV_EXPORTS void HoughLinesP(const GpuMat& image, GpuMat& lines, HoughLinesBuf& buf, float rho, float theta, int minLineLength, int maxLineGap, int maxLines = 4096);
//! HoughCircles
struct HoughCirclesBuf
{
GpuMat edges;
GpuMat accum;
GpuMat list;
CannyBuf cannyBuf;
};
CV_EXPORTS void HoughCircles(const GpuMat& src, GpuMat& circles, int method, float dp, float minDist, int cannyThreshold, int votesThreshold, int minRadius, int maxRadius, int maxCircles = 4096);
CV_EXPORTS void HoughCircles(const GpuMat& src, GpuMat& circles, HoughCirclesBuf& buf, int method, float dp, float minDist, int cannyThreshold, int votesThreshold, int minRadius, int maxRadius, int maxCircles = 4096);
CV_EXPORTS void HoughCirclesDownload(const GpuMat& d_circles, OutputArray h_circles);
//! finds arbitrary template in the grayscale image using Generalized Hough Transform
//! Ballard, D.H. (1981). Generalizing the Hough transform to detect arbitrary shapes. Pattern Recognition 13 (2): 111-122.
//! Guil, N., González-Linares, J.M. and Zapata, E.L. (1999). Bidimensional shape detection using an invariant approach. Pattern Recognition 32 (6): 1025-1038.
class CV_EXPORTS GeneralizedHough_GPU : public cv::Algorithm
{
public:
static Ptr<GeneralizedHough_GPU> create(int method);
virtual ~GeneralizedHough_GPU();
//! set template to search
void setTemplate(const GpuMat& templ, int cannyThreshold = 100, Point templCenter = Point(-1, -1));
void setTemplate(const GpuMat& edges, const GpuMat& dx, const GpuMat& dy, Point templCenter = Point(-1, -1));
//! find template on image
void detect(const GpuMat& image, GpuMat& positions, int cannyThreshold = 100);
void detect(const GpuMat& edges, const GpuMat& dx, const GpuMat& dy, GpuMat& positions);
void download(const GpuMat& d_positions, OutputArray h_positions, OutputArray h_votes = noArray());
void release();
protected:
virtual void setTemplateImpl(const GpuMat& edges, const GpuMat& dx, const GpuMat& dy, Point templCenter) = 0;
virtual void detectImpl(const GpuMat& edges, const GpuMat& dx, const GpuMat& dy, GpuMat& positions) = 0;
virtual void releaseImpl() = 0;
private:
GpuMat edges_;
CannyBuf cannyBuf_;
};
//!performs labeling via graph cuts of a 2D regular 4-connected graph.
CV_EXPORTS void graphcut(GpuMat& terminals, GpuMat& leftTransp, GpuMat& rightTransp, GpuMat& top, GpuMat& bottom, GpuMat& labels,
GpuMat& buf, Stream& stream = Stream::Null());
//!performs labeling via graph cuts of a 2D regular 8-connected graph.
CV_EXPORTS void graphcut(GpuMat& terminals, GpuMat& leftTransp, GpuMat& rightTransp, GpuMat& top, GpuMat& topLeft, GpuMat& topRight,
GpuMat& bottom, GpuMat& bottomLeft, GpuMat& bottomRight,
GpuMat& labels,
GpuMat& buf, Stream& stream = Stream::Null());
//! compute mask for Generalized Flood fill componetns labeling.
CV_EXPORTS void connectivityMask(const GpuMat& image, GpuMat& mask, const cv::Scalar& lo, const cv::Scalar& hi, Stream& stream = Stream::Null());
//! performs connected componnents labeling.
CV_EXPORTS void labelComponents(const GpuMat& mask, GpuMat& components, int flags = 0, Stream& stream = Stream::Null());
//! Compute levels with even distribution. levels will have 1 row and nLevels cols and CV_32SC1 type.
CV_EXPORTS void evenLevels(GpuMat& levels, int nLevels, int lowerLevel, int upperLevel);
//! Calculates histogram with evenly distributed bins for signle channel source.
//! Supports CV_8UC1, CV_16UC1 and CV_16SC1 source types.
//! Output hist will have one row and histSize cols and CV_32SC1 type.
CV_EXPORTS void histEven(const GpuMat& src, GpuMat& hist, int histSize, int lowerLevel, int upperLevel, Stream& stream = Stream::Null());
CV_EXPORTS void histEven(const GpuMat& src, GpuMat& hist, GpuMat& buf, int histSize, int lowerLevel, int upperLevel, Stream& stream = Stream::Null());
//! Calculates histogram with evenly distributed bins for four-channel source.
//! All channels of source are processed separately.
//! Supports CV_8UC4, CV_16UC4 and CV_16SC4 source types.
//! Output hist[i] will have one row and histSize[i] cols and CV_32SC1 type.
CV_EXPORTS void histEven(const GpuMat& src, GpuMat hist[4], int histSize[4], int lowerLevel[4], int upperLevel[4], Stream& stream = Stream::Null());
CV_EXPORTS void histEven(const GpuMat& src, GpuMat hist[4], GpuMat& buf, int histSize[4], int lowerLevel[4], int upperLevel[4], Stream& stream = Stream::Null());
//! Calculates histogram with bins determined by levels array.
//! levels must have one row and CV_32SC1 type if source has integer type or CV_32FC1 otherwise.
//! Supports CV_8UC1, CV_16UC1, CV_16SC1 and CV_32FC1 source types.
//! Output hist will have one row and (levels.cols-1) cols and CV_32SC1 type.
CV_EXPORTS void histRange(const GpuMat& src, GpuMat& hist, const GpuMat& levels, Stream& stream = Stream::Null());
CV_EXPORTS void histRange(const GpuMat& src, GpuMat& hist, const GpuMat& levels, GpuMat& buf, Stream& stream = Stream::Null());
//! Calculates histogram with bins determined by levels array.
//! All levels must have one row and CV_32SC1 type if source has integer type or CV_32FC1 otherwise.
//! All channels of source are processed separately.
//! Supports CV_8UC4, CV_16UC4, CV_16SC4 and CV_32FC4 source types.
//! Output hist[i] will have one row and (levels[i].cols-1) cols and CV_32SC1 type.
CV_EXPORTS void histRange(const GpuMat& src, GpuMat hist[4], const GpuMat levels[4], Stream& stream = Stream::Null());
CV_EXPORTS void histRange(const GpuMat& src, GpuMat hist[4], const GpuMat levels[4], GpuMat& buf, Stream& stream = Stream::Null());
//! Calculates histogram for 8u one channel image
//! Output hist will have one row, 256 cols and CV32SC1 type.
CV_EXPORTS void calcHist(const GpuMat& src, GpuMat& hist, Stream& stream = Stream::Null());
CV_EXPORTS void calcHist(const GpuMat& src, GpuMat& hist, GpuMat& buf, Stream& stream = Stream::Null());
//! normalizes the grayscale image brightness and contrast by normalizing its histogram
CV_EXPORTS void equalizeHist(const GpuMat& src, GpuMat& dst, Stream& stream = Stream::Null());
CV_EXPORTS void equalizeHist(const GpuMat& src, GpuMat& dst, GpuMat& hist, Stream& stream = Stream::Null());
CV_EXPORTS void equalizeHist(const GpuMat& src, GpuMat& dst, GpuMat& hist, GpuMat& buf, Stream& stream = Stream::Null());
class CV_EXPORTS CLAHE : public cv::CLAHE
{
public:
using cv::CLAHE::apply;
virtual void apply(InputArray src, OutputArray dst, Stream& stream) = 0;
};
CV_EXPORTS Ptr<cv::gpu::CLAHE> createCLAHE(double clipLimit = 40.0, Size tileGridSize = Size(8, 8));
class CV_EXPORTS GoodFeaturesToTrackDetector_GPU
{
public:
explicit GoodFeaturesToTrackDetector_GPU(int maxCorners = 1000, double qualityLevel = 0.01, double minDistance = 0.0,
int blockSize = 3, bool useHarrisDetector = false, double harrisK = 0.04);
//! return 1 rows matrix with CV_32FC2 type
void operator ()(const GpuMat& image, GpuMat& corners, const GpuMat& mask = GpuMat());
int maxCorners;
double qualityLevel;
double minDistance;
int blockSize;
bool useHarrisDetector;
double harrisK;
void releaseMemory()
{
Dx_.release();
Dy_.release();
buf_.release();
eig_.release();
minMaxbuf_.release();
tmpCorners_.release();
}
private:
GpuMat Dx_;
GpuMat Dy_;
GpuMat buf_;
GpuMat eig_;
GpuMat minMaxbuf_;
GpuMat tmpCorners_;
};
inline GoodFeaturesToTrackDetector_GPU::GoodFeaturesToTrackDetector_GPU(int maxCorners_, double qualityLevel_, double minDistance_,
int blockSize_, bool useHarrisDetector_, double harrisK_)
{
maxCorners = maxCorners_;
qualityLevel = qualityLevel_;
minDistance = minDistance_;
blockSize = blockSize_;
useHarrisDetector = useHarrisDetector_;
harrisK = harrisK_;
}
}} // namespace cv { namespace gpu {
#endif /* __OPENCV_GPUIMGPROC_HPP__ */

0
modules/gpu/perf/perf_denoising.cpp → modules/gpuimgproc/perf/perf_denoising.cpp
View File

46
modules/gpu/perf/perf_imgproc.cpp → modules/gpuimgproc/perf/perf_imgproc.cpp
View File

@ -366,7 +366,7 @@ PERF_TEST_P(Sz_Depth_Op, ImgProc_Threshold,
//////////////////////////////////////////////////////////////////////
// HistEvenC1
PERF_TEST_P(Sz_Depth, ImgProc_HistEvenC1,
PERF_TEST_P(Sz_Depth, HistEvenC1,
Combine(GPU_TYPICAL_MAT_SIZES,
Values(CV_8U, CV_16U, CV_16S)))
{
@ -405,7 +405,7 @@ PERF_TEST_P(Sz_Depth, ImgProc_HistEvenC1,
//////////////////////////////////////////////////////////////////////
// HistEvenC4
PERF_TEST_P(Sz_Depth, ImgProc_HistEvenC4,
PERF_TEST_P(Sz_Depth, HistEvenC4,
Combine(GPU_TYPICAL_MAT_SIZES,
Values(CV_8U, CV_16U, CV_16S)))
{
@ -446,7 +446,7 @@ PERF_TEST_P(Sz_Depth, ImgProc_HistEvenC4,
//////////////////////////////////////////////////////////////////////
// CalcHist
PERF_TEST_P(Sz, ImgProc_CalcHist,
PERF_TEST_P(Sz, CalcHist,
GPU_TYPICAL_MAT_SIZES)
{
const cv::Size size = GetParam();
@ -472,7 +472,7 @@ PERF_TEST_P(Sz, ImgProc_CalcHist,
//////////////////////////////////////////////////////////////////////
// EqualizeHist
PERF_TEST_P(Sz, ImgProc_EqualizeHist,
PERF_TEST_P(Sz, EqualizeHist,
GPU_TYPICAL_MAT_SIZES)
{
const cv::Size size = GetParam();
@ -503,7 +503,7 @@ PERF_TEST_P(Sz, ImgProc_EqualizeHist,
DEF_PARAM_TEST(Sz_ClipLimit, cv::Size, double);
PERF_TEST_P(Sz_ClipLimit, ImgProc_CLAHE,
PERF_TEST_P(Sz_ClipLimit, CLAHE,
Combine(GPU_TYPICAL_MAT_SIZES,
Values(0.0, 40.0)))
{
@ -539,7 +539,7 @@ PERF_TEST_P(Sz_ClipLimit, ImgProc_CLAHE,
DEF_PARAM_TEST(Image_AppertureSz_L2gradient, string, int, bool);
PERF_TEST_P(Image_AppertureSz_L2gradient, ImgProc_Canny,
PERF_TEST_P(Image_AppertureSz_L2gradient, Canny,
Combine(Values("perf/800x600.png", "perf/1280x1024.png", "perf/1680x1050.png"),
Values(3, 5),
Bool()))
@ -579,7 +579,7 @@ PERF_TEST_P(Image_AppertureSz_L2gradient, ImgProc_Canny,
DEF_PARAM_TEST_1(Image, string);
PERF_TEST_P(Image, ImgProc_MeanShiftFiltering,
PERF_TEST_P(Image, MeanShiftFiltering,
Values<string>("gpu/meanshift/cones.png"))
{
declare.time(300.0);
@ -615,7 +615,7 @@ PERF_TEST_P(Image, ImgProc_MeanShiftFiltering,
//////////////////////////////////////////////////////////////////////
// MeanShiftProc
PERF_TEST_P(Image, ImgProc_MeanShiftProc,
PERF_TEST_P(Image, MeanShiftProc,
Values<string>("gpu/meanshift/cones.png"))
{
declare.time(300.0);
@ -649,7 +649,7 @@ PERF_TEST_P(Image, ImgProc_MeanShiftProc,
//////////////////////////////////////////////////////////////////////
// MeanShiftSegmentation
PERF_TEST_P(Image, ImgProc_MeanShiftSegmentation,
PERF_TEST_P(Image, MeanShiftSegmentation,
Values<string>("gpu/meanshift/cones.png"))
{
declare.time(300.0);
@ -682,7 +682,7 @@ PERF_TEST_P(Image, ImgProc_MeanShiftSegmentation,
//////////////////////////////////////////////////////////////////////
// BlendLinear
PERF_TEST_P(Sz_Depth_Cn, ImgProc_BlendLinear,
PERF_TEST_P(Sz_Depth_Cn, BlendLinear,
Combine(GPU_TYPICAL_MAT_SIZES,
Values(CV_8U, CV_32F),
GPU_CHANNELS_1_3_4))
@ -725,7 +725,7 @@ CV_ENUM(TemplateMethod, TM_SQDIFF, TM_SQDIFF_NORMED, TM_CCORR, TM_CCORR_NORMED,
DEF_PARAM_TEST(Sz_TemplateSz_Cn_Method, cv::Size, cv::Size, MatCn, TemplateMethod);
PERF_TEST_P(Sz_TemplateSz_Cn_Method, ImgProc_MatchTemplate8U,
PERF_TEST_P(Sz_TemplateSz_Cn_Method, MatchTemplate8U,
Combine(GPU_TYPICAL_MAT_SIZES,
Values(cv::Size(5, 5), cv::Size(16, 16), cv::Size(30, 30)),
GPU_CHANNELS_1_3_4,
@ -765,7 +765,7 @@ PERF_TEST_P(Sz_TemplateSz_Cn_Method, ImgProc_MatchTemplate8U,
////////////////////////////////////////////////////////////////////////////////
// MatchTemplate32F
PERF_TEST_P(Sz_TemplateSz_Cn_Method, ImgProc_MatchTemplate32F,
PERF_TEST_P(Sz_TemplateSz_Cn_Method, MatchTemplate32F,
Combine(GPU_TYPICAL_MAT_SIZES,
Values(cv::Size(5, 5), cv::Size(16, 16), cv::Size(30, 30)),
GPU_CHANNELS_1_3_4,
@ -807,7 +807,7 @@ PERF_TEST_P(Sz_TemplateSz_Cn_Method, ImgProc_MatchTemplate32F,
DEF_PARAM_TEST(Image_Type_Border_BlockSz_ApertureSz, string, MatType, BorderMode, int, int);
PERF_TEST_P(Image_Type_Border_BlockSz_ApertureSz, ImgProc_CornerHarris,
PERF_TEST_P(Image_Type_Border_BlockSz_ApertureSz, CornerHarris,
Combine(Values<string>("gpu/stereobm/aloe-L.png"),
Values(CV_8UC1, CV_32FC1),
Values(BorderMode(cv::BORDER_REFLECT101), BorderMode(cv::BORDER_REPLICATE), BorderMode(cv::BORDER_REFLECT)),
@ -852,7 +852,7 @@ PERF_TEST_P(Image_Type_Border_BlockSz_ApertureSz, ImgProc_CornerHarris,
//////////////////////////////////////////////////////////////////////
// CornerMinEigenVal
PERF_TEST_P(Image_Type_Border_BlockSz_ApertureSz, ImgProc_CornerMinEigenVal,
PERF_TEST_P(Image_Type_Border_BlockSz_ApertureSz, CornerMinEigenVal,
Combine(Values<string>("gpu/stereobm/aloe-L.png"),
Values(CV_8UC1, CV_32FC1),
Values(BorderMode(cv::BORDER_REFLECT101), BorderMode(cv::BORDER_REPLICATE), BorderMode(cv::BORDER_REFLECT)),
@ -1087,7 +1087,7 @@ PERF_TEST_P(Sz_Depth_Cn, ImgProc_PyrUp,
DEF_PARAM_TEST(Sz_Depth_Code, cv::Size, MatDepth, CvtColorInfo);
PERF_TEST_P(Sz_Depth_Code, ImgProc_CvtColor,
PERF_TEST_P(Sz_Depth_Code, CvtColor,
Combine(GPU_TYPICAL_MAT_SIZES,
Values(CV_8U, CV_32F),
Values(CvtColorInfo(4, 4, cv::COLOR_RGBA2BGRA),
@ -1138,7 +1138,7 @@ PERF_TEST_P(Sz_Depth_Code, ImgProc_CvtColor,
}
}
PERF_TEST_P(Sz_Depth_Code, ImgProc_CvtColorBayer,
PERF_TEST_P(Sz_Depth_Code, CvtColorBayer,
Combine(GPU_TYPICAL_MAT_SIZES,
Values(CV_8U, CV_16U),
Values(CvtColorInfo(1, 3, cv::COLOR_BayerBG2BGR),
@ -1185,7 +1185,7 @@ CV_ENUM(DemosaicingCode,
DEF_PARAM_TEST(Sz_Code, cv::Size, DemosaicingCode);
PERF_TEST_P(Sz_Code, ImgProc_Demosaicing,
PERF_TEST_P(Sz_Code, Demosaicing,
Combine(GPU_TYPICAL_MAT_SIZES,
DemosaicingCode::all()))
{
@ -1224,7 +1224,7 @@ PERF_TEST_P(Sz_Code, ImgProc_Demosaicing,
//////////////////////////////////////////////////////////////////////
// SwapChannels
PERF_TEST_P(Sz, ImgProc_SwapChannels,
PERF_TEST_P(Sz, SwapChannels,
GPU_TYPICAL_MAT_SIZES)
{
const cv::Size size = GetParam();
@ -1255,7 +1255,7 @@ CV_ENUM(AlphaOp, ALPHA_OVER, ALPHA_IN, ALPHA_OUT, ALPHA_ATOP, ALPHA_XOR, ALPHA_P
DEF_PARAM_TEST(Sz_Type_Op, cv::Size, MatType, AlphaOp);
PERF_TEST_P(Sz_Type_Op, ImgProc_AlphaComp,
PERF_TEST_P(Sz_Type_Op, AlphaComp,
Combine(GPU_TYPICAL_MAT_SIZES,
Values(CV_8UC4, CV_16UC4, CV_32SC4, CV_32FC4),
AlphaOp::all()))
@ -1394,7 +1394,7 @@ namespace
};
}
PERF_TEST_P(Sz, ImgProc_HoughLines,
PERF_TEST_P(Sz, HoughLines,
GPU_TYPICAL_MAT_SIZES)
{
declare.time(30.0);
@ -1442,7 +1442,7 @@ PERF_TEST_P(Sz, ImgProc_HoughLines,
DEF_PARAM_TEST_1(Image, std::string);
PERF_TEST_P(Image, ImgProc_HoughLinesP,
PERF_TEST_P(Image, HoughLinesP,
testing::Values("cv/shared/pic5.png", "stitching/a1.png"))
{
declare.time(30.0);
@ -1490,7 +1490,7 @@ PERF_TEST_P(Image, ImgProc_HoughLinesP,
DEF_PARAM_TEST(Sz_Dp_MinDist, cv::Size, float, float);
PERF_TEST_P(Sz_Dp_MinDist, ImgProc_HoughCircles,
PERF_TEST_P(Sz_Dp_MinDist, HoughCircles,
Combine(GPU_TYPICAL_MAT_SIZES,
Values(1.0f, 2.0f, 4.0f),
Values(1.0f)))
@ -1547,7 +1547,7 @@ CV_FLAGS(GHMethod, GHT_POSITION, GHT_SCALE, GHT_ROTATION);
DEF_PARAM_TEST(Method_Sz, GHMethod, cv::Size);
PERF_TEST_P(Method_Sz, ImgProc_GeneralizedHough,
PERF_TEST_P(Method_Sz, GeneralizedHough,
Combine(Values(GHMethod(GHT_POSITION), GHMethod(GHT_POSITION | GHT_SCALE), GHMethod(GHT_POSITION | GHT_ROTATION), GHMethod(GHT_POSITION | GHT_SCALE | GHT_ROTATION)),
GPU_TYPICAL_MAT_SIZES))
{

0
modules/gpu/perf/perf_labeling.cpp → modules/gpuimgproc/perf/perf_labeling.cpp
View File

47
modules/gpuimgproc/perf/perf_main.cpp Normal file
View File

@ -0,0 +1,47 @@
/*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 "perf_precomp.hpp"
using namespace perf;
CV_PERF_TEST_MAIN(gpuimgproc, printCudaInfo())

43
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@ -0,0 +1,43 @@
/*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 "perf_precomp.hpp"

66
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@ -0,0 +1,66 @@
/*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*/
#ifdef __GNUC__
# pragma GCC diagnostic ignored "-Wmissing-declarations"
# if defined __clang__ || defined __APPLE__
# pragma GCC diagnostic ignored "-Wmissing-prototypes"
# pragma GCC diagnostic ignored "-Wextra"
# endif
#endif
#ifndef __OPENCV_PERF_PRECOMP_HPP__
#define __OPENCV_PERF_PRECOMP_HPP__
#include "opencv2/ts.hpp"
#include "opencv2/ts/gpu_perf.hpp"
#include "opencv2/gpuimgproc.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/photo.hpp"
#ifdef GTEST_CREATE_SHARED_LIBRARY
#error no modules except ts should have GTEST_CREATE_SHARED_LIBRARY defined
#endif
#endif

0
modules/gpu/src/blend.cpp → modules/gpuimgproc/src/blend.cpp
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0
modules/gpu/src/color.cpp → modules/gpuimgproc/src/color.cpp
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0
modules/gpu/src/cuda/bilateral_filter.cu → modules/gpuimgproc/src/cuda/bilateral_filter.cu
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0
modules/gpu/src/cuda/blend.cu → modules/gpuimgproc/src/cuda/blend.cu
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0
modules/gpu/src/cuda/canny.cu → modules/gpuimgproc/src/cuda/canny.cu
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0
modules/gpu/src/cuda/ccomponetns.cu → modules/gpuimgproc/src/cuda/ccomponetns.cu
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0
modules/gpu/src/cuda/clahe.cu → modules/gpuimgproc/src/cuda/clahe.cu
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0
modules/gpu/src/cuda/color.cu → modules/gpuimgproc/src/cuda/color.cu
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0
modules/gpu/src/cuda/debayer.cu → modules/gpuimgproc/src/cuda/debayer.cu
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0
modules/gpu/src/cuda/gftt.cu → modules/gpuimgproc/src/cuda/gftt.cu
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0
modules/gpu/src/cuda/hist.cu → modules/gpuimgproc/src/cuda/hist.cu
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0
modules/gpu/src/cuda/hough.cu → modules/gpuimgproc/src/cuda/hough.cu
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1
modules/gpu/src/cuda/imgproc.cu → modules/gpuimgproc/src/cuda/imgproc.cu
View File

@ -47,7 +47,6 @@
#include "opencv2/core/cuda/vec_math.hpp"
#include "opencv2/core/cuda/saturate_cast.hpp"
#include "opencv2/core/cuda/border_interpolate.hpp"
#include "internal_shared.hpp"
namespace cv { namespace gpu { namespace cudev
{

0
modules/gpu/src/cuda/match_template.cu → modules/gpuimgproc/src/cuda/match_template.cu
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0
modules/gpu/src/cuda/nlm.cu → modules/gpuimgproc/src/cuda/nlm.cu
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0
modules/gpu/src/cuda/pyr_down.cu → modules/gpuimgproc/src/cuda/pyr_down.cu
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0
modules/gpu/src/cuda/pyr_up.cu → modules/gpuimgproc/src/cuda/pyr_up.cu
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0
modules/gpu/src/cuda/remap.cu → modules/gpuimgproc/src/cuda/remap.cu
View File

0
modules/gpu/src/cuda/resize.cu → modules/gpuimgproc/src/cuda/resize.cu
View File

0
modules/gpu/src/cuda/warp.cu → modules/gpuimgproc/src/cuda/warp.cu
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0
modules/gpu/src/cvt_color_internal.h → modules/gpuimgproc/src/cvt_color_internal.h
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0
modules/gpu/src/denoising.cpp → modules/gpuimgproc/src/denoising.cpp
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0
modules/gpu/src/gftt.cpp → modules/gpuimgproc/src/gftt.cpp
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0
modules/gpu/src/graphcuts.cpp → modules/gpuimgproc/src/graphcuts.cpp
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0
modules/gpu/src/hough.cpp → modules/gpuimgproc/src/hough.cpp
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0
modules/gpu/src/imgproc.cpp → modules/gpuimgproc/src/imgproc.cpp
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0
modules/gpu/src/match_template.cpp → modules/gpuimgproc/src/match_template.cpp
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0
modules/gpu/src/mssegmentation.cpp → modules/gpuimgproc/src/mssegmentation.cpp
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43
modules/gpuimgproc/src/precomp.cpp Normal file
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@ -0,0 +1,43 @@
/*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 "precomp.hpp"

53
modules/gpuimgproc/src/precomp.hpp Normal file
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@ -0,0 +1,53 @@
/*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*/
#ifndef __OPENCV_PRECOMP_H__
#define __OPENCV_PRECOMP_H__
#include "opencv2/gpufilters.hpp"
#include "opencv2/gpuarithm.hpp"
#include "opencv2/gpuimgproc.hpp"
#include "opencv2/core/private.hpp"
#include "opencv2/core/gpu_private.hpp"
#endif /* __OPENCV_PRECOMP_H__ */

0
modules/gpu/src/pyramids.cpp → modules/gpuimgproc/src/pyramids.cpp
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0
modules/gpu/src/remap.cpp → modules/gpuimgproc/src/remap.cpp
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0
modules/gpu/src/resize.cpp → modules/gpuimgproc/src/resize.cpp
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0
modules/gpu/src/warp.cpp → modules/gpuimgproc/src/warp.cpp
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0
modules/gpu/test/interpolation.hpp → modules/gpuimgproc/test/interpolation.hpp
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0
modules/gpu/test/test_color.cpp → modules/gpuimgproc/test/test_color.cpp
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0
modules/gpu/test/test_denoising.cpp → modules/gpuimgproc/test/test_denoising.cpp
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0
modules/gpu/test/test_hough.cpp → modules/gpuimgproc/test/test_hough.cpp
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0
modules/gpu/test/test_imgproc.cpp → modules/gpuimgproc/test/test_imgproc.cpp
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0
modules/gpu/test/test_labeling.cpp → modules/gpuimgproc/test/test_labeling.cpp
View File

45
modules/gpuimgproc/test/test_main.cpp Normal file
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@ -0,0 +1,45 @@
/*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"
CV_GPU_TEST_MAIN("gpu")

43
modules/gpuimgproc/test/test_precomp.cpp Normal file
View File

@ -0,0 +1,43 @@
/*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"

63
modules/gpuimgproc/test/test_precomp.hpp Normal file
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@ -0,0 +1,63 @@
/*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*/
#ifdef __GNUC__
# pragma GCC diagnostic ignored "-Wmissing-declarations"
# if defined __clang__ || defined __APPLE__
# pragma GCC diagnostic ignored "-Wmissing-prototypes"
# pragma GCC diagnostic ignored "-Wextra"
# endif
#endif
#ifndef __OPENCV_TEST_PRECOMP_HPP__
#define __OPENCV_TEST_PRECOMP_HPP__
#include "opencv2/ts.hpp"
#include "opencv2/ts/gpu_test.hpp"
#include "opencv2/gpuimgproc.hpp"
#include "opencv2/gpuarithm.hpp"
#include "opencv2/imgproc.hpp"
#include "interpolation.hpp"
#endif

0
modules/gpu/test/test_pyramids.cpp → modules/gpuimgproc/test/test_pyramids.cpp
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0
modules/gpu/test/test_remap.cpp → modules/gpuimgproc/test/test_remap.cpp
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0
modules/gpu/test/test_resize.cpp → modules/gpuimgproc/test/test_resize.cpp
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0
modules/gpu/test/test_warp_affine.cpp → modules/gpuimgproc/test/test_warp_affine.cpp
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0
modules/gpu/test/test_warp_perspective.cpp → modules/gpuimgproc/test/test_warp_perspective.cpp
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1
samples/cpp/CMakeLists.txt
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@ -19,6 +19,7 @@ if(BUILD_EXAMPLES AND OCV_DEPENDENCIES_FOUND)
if(HAVE_opencv_gpu)
ocv_include_directories("${OpenCV_SOURCE_DIR}/modules/gpuarithm/include")
ocv_include_directories("${OpenCV_SOURCE_DIR}/modules/gpufilters/include")
ocv_include_directories("${OpenCV_SOURCE_DIR}/modules/gpuimgproc/include")
ocv_include_directories("${OpenCV_SOURCE_DIR}/modules/gpu/include")
endif()

2
samples/gpu/CMakeLists.txt
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@ -2,7 +2,7 @@ SET(OPENCV_GPU_SAMPLES_REQUIRED_DEPS opencv_core opencv_flann opencv_imgproc ope
opencv_ml opencv_video opencv_objdetect opencv_features2d
opencv_calib3d opencv_legacy opencv_contrib opencv_gpu
opencv_nonfree opencv_softcascade opencv_superres
opencv_gpucodec opencv_gpuarithm opencv_gpufilters opencv_gpunvidia)
opencv_gpucodec opencv_gpuarithm opencv_gpufilters opencv_gpunvidia opencv_gpuimgproc)
ocv_check_dependencies(${OPENCV_GPU_SAMPLES_REQUIRED_DEPS})