OpenCV
3.4.14
Open Source Computer Vision
|
Modules | |
Color space processing | |
Histogram Calculation | |
Hough Transform | |
Feature Detection | |
Classes | |
class | cv::cuda::CannyEdgeDetector |
Base class for Canny Edge Detector. : More... | |
class | cv::cuda::TemplateMatching |
Base class for Template Matching. : More... | |
Functions | |
void | cv::cuda::bilateralFilter (InputArray src, OutputArray dst, int kernel_size, float sigma_color, float sigma_spatial, int borderMode=BORDER_DEFAULT, Stream &stream=Stream::Null()) |
Performs bilateral filtering of passed image. More... | |
void | cv::cuda::blendLinear (InputArray img1, InputArray img2, InputArray weights1, InputArray weights2, OutputArray result, Stream &stream=Stream::Null()) |
Performs linear blending of two images. More... | |
Ptr< CannyEdgeDetector > | cv::cuda::createCannyEdgeDetector (double low_thresh, double high_thresh, int apperture_size=3, bool L2gradient=false) |
Creates implementation for cuda::CannyEdgeDetector . More... | |
Ptr< TemplateMatching > | cv::cuda::createTemplateMatching (int srcType, int method, Size user_block_size=Size()) |
Creates implementation for cuda::TemplateMatching . More... | |
void | cv::cuda::meanShiftFiltering (InputArray src, OutputArray dst, int sp, int sr, TermCriteria criteria=TermCriteria(TermCriteria::MAX_ITER+TermCriteria::EPS, 5, 1), Stream &stream=Stream::Null()) |
Performs mean-shift filtering for each point of the source image. More... | |
void | cv::cuda::meanShiftProc (InputArray src, OutputArray dstr, OutputArray dstsp, int sp, int sr, TermCriteria criteria=TermCriteria(TermCriteria::MAX_ITER+TermCriteria::EPS, 5, 1), Stream &stream=Stream::Null()) |
Performs a mean-shift procedure and stores information about processed points (their colors and positions) in two images. More... | |
void | cv::cuda::meanShiftSegmentation (InputArray src, OutputArray dst, int sp, int sr, int minsize, TermCriteria criteria=TermCriteria(TermCriteria::MAX_ITER+TermCriteria::EPS, 5, 1), Stream &stream=Stream::Null()) |
Performs a mean-shift segmentation of the source image and eliminates small segments. More... | |
void cv::cuda::bilateralFilter | ( | InputArray | src, |
OutputArray | dst, | ||
int | kernel_size, | ||
float | sigma_color, | ||
float | sigma_spatial, | ||
int | borderMode = BORDER_DEFAULT , |
||
Stream & | stream = Stream::Null() |
||
) |
#include <opencv2/cudaimgproc.hpp>
Performs bilateral filtering of passed image.
src | Source image. Supports only (channels != 2 && depth() != CV_8S && depth() != CV_32S && depth() != CV_64F). |
dst | Destination imagwe. |
kernel_size | Kernel window size. |
sigma_color | Filter sigma in the color space. |
sigma_spatial | Filter sigma in the coordinate space. |
borderMode | Border type. See borderInterpolate for details. BORDER_REFLECT101 , BORDER_REPLICATE , BORDER_CONSTANT , BORDER_REFLECT and BORDER_WRAP are supported for now. |
stream | Stream for the asynchronous version. |
void cv::cuda::blendLinear | ( | InputArray | img1, |
InputArray | img2, | ||
InputArray | weights1, | ||
InputArray | weights2, | ||
OutputArray | result, | ||
Stream & | stream = Stream::Null() |
||
) |
#include <opencv2/cudaimgproc.hpp>
Performs linear blending of two images.
img1 | First image. Supports only CV_8U and CV_32F depth. |
img2 | Second image. Must have the same size and the same type as img1 . |
weights1 | Weights for first image. Must have tha same size as img1 . Supports only CV_32F type. |
weights2 | Weights for second image. Must have tha same size as img2 . Supports only CV_32F type. |
result | Destination image. |
stream | Stream for the asynchronous version. |
Ptr<CannyEdgeDetector> cv::cuda::createCannyEdgeDetector | ( | double | low_thresh, |
double | high_thresh, | ||
int | apperture_size = 3 , |
||
bool | L2gradient = false |
||
) |
#include <opencv2/cudaimgproc.hpp>
Creates implementation for cuda::CannyEdgeDetector .
low_thresh | First threshold for the hysteresis procedure. |
high_thresh | Second threshold for the hysteresis procedure. |
apperture_size | Aperture size for the Sobel operator. |
L2gradient | Flag indicating whether a more accurate \(L_2\) norm \(=\sqrt{(dI/dx)^2 + (dI/dy)^2}\) should be used to compute the image gradient magnitude ( L2gradient=true ), or a faster default \(L_1\) norm \(=|dI/dx|+|dI/dy|\) is enough ( L2gradient=false ). |
Ptr<TemplateMatching> cv::cuda::createTemplateMatching | ( | int | srcType, |
int | method, | ||
Size | user_block_size = Size() |
||
) |
#include <opencv2/cudaimgproc.hpp>
Creates implementation for cuda::TemplateMatching .
srcType | Input source type. CV_32F and CV_8U depth images (1..4 channels) are supported for now. |
method | Specifies the way to compare the template with the image. |
user_block_size | You can use field user_block_size to set specific block size. If you leave its default value Size(0,0) then automatic estimation of block size will be used (which is optimized for speed). By varying user_block_size you can reduce memory requirements at the cost of speed. |
The following methods are supported for the CV_8U depth images for now:
The following methods are supported for the CV_32F images for now:
void cv::cuda::meanShiftFiltering | ( | InputArray | src, |
OutputArray | dst, | ||
int | sp, | ||
int | sr, | ||
TermCriteria | criteria = TermCriteria(TermCriteria::MAX_ITER+TermCriteria::EPS, 5, 1) , |
||
Stream & | stream = Stream::Null() |
||
) |
#include <opencv2/cudaimgproc.hpp>
Performs mean-shift filtering for each point of the source image.
src | Source image. Only CV_8UC4 images are supported for now. |
dst | Destination image containing the color of mapped points. It has the same size and type as src . |
sp | Spatial window radius. |
sr | Color window radius. |
criteria | Termination criteria. See TermCriteria. |
stream | Stream for the asynchronous version. |
It maps each point of the source image into another point. As a result, you have a new color and new position of each point.
void cv::cuda::meanShiftProc | ( | InputArray | src, |
OutputArray | dstr, | ||
OutputArray | dstsp, | ||
int | sp, | ||
int | sr, | ||
TermCriteria | criteria = TermCriteria(TermCriteria::MAX_ITER+TermCriteria::EPS, 5, 1) , |
||
Stream & | stream = Stream::Null() |
||
) |
#include <opencv2/cudaimgproc.hpp>
Performs a mean-shift procedure and stores information about processed points (their colors and positions) in two images.
src | Source image. Only CV_8UC4 images are supported for now. |
dstr | Destination image containing the color of mapped points. The size and type is the same as src . |
dstsp | Destination image containing the position of mapped points. The size is the same as src size. The type is CV_16SC2 . |
sp | Spatial window radius. |
sr | Color window radius. |
criteria | Termination criteria. See TermCriteria. |
stream | Stream for the asynchronous version. |
void cv::cuda::meanShiftSegmentation | ( | InputArray | src, |
OutputArray | dst, | ||
int | sp, | ||
int | sr, | ||
int | minsize, | ||
TermCriteria | criteria = TermCriteria(TermCriteria::MAX_ITER+TermCriteria::EPS, 5, 1) , |
||
Stream & | stream = Stream::Null() |
||
) |
#include <opencv2/cudaimgproc.hpp>
Performs a mean-shift segmentation of the source image and eliminates small segments.
src | Source image. Only CV_8UC4 images are supported for now. |
dst | Segmented image with the same size and type as src (host memory). |
sp | Spatial window radius. |
sr | Color window radius. |
minsize | Minimum segment size. Smaller segments are merged. |
criteria | Termination criteria. See TermCriteria. |
stream | Stream for the asynchronous version. |