图像处理 CUDA 加速的计算机视觉


模块

  色彩空间处理
 
  直方图计算
 
  霍夫变换
 
  特征检测
 

class   cv::cuda::CannyEdgeDetector
  Base class for Canny Edge Detector . : 更多...
 
class   cv::cuda::TemplateMatching
  Base class for Template Matching. : 更多...
 

函数

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. 更多...
 
void  cv::cuda::blendLinear ( InputArray img1, InputArray img2, InputArray weights1, InputArray weights2, OutputArray result, Stream &stream= Stream::Null ())
  对 2 图像履行线性融合。 更多...
 
Ptr < CannyEdgeDetector cv::cuda::createCannyEdgeDetector (double low_thresh, double high_thresh, int apperture_size=3, bool L2gradient=false)
  创建实现,为 cuda::CannyEdgeDetector . 更多...
 
Ptr < TemplateMatching cv::cuda::createTemplateMatching (int srcType, int method, Size user_block_size= Size ())
  创建实现,为 cuda::TemplateMatching . 更多...
 
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. 更多...
 
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. 更多...
 
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. 更多...
 

详细描述

函数文档编制

◆  bilateralFilter()

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.

Parameters
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.
另请参阅
bilateralFilter

◆  blendLinear()

void cv::cuda::blendLinear ( InputArray   img1 ,
InputArray   img2 ,
InputArray   weights1 ,
InputArray   weights2 ,
OutputArray   result ,
Stream stream = Stream::Null ()  
)

#include < opencv2/cudaimgproc.hpp >

对 2 图像履行线性融合。

Parameters
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.

◆  createCannyEdgeDetector()

Ptr < CannyEdgeDetector > cv::cuda::createCannyEdgeDetector ( double  low_thresh ,
double  high_thresh ,
int  apperture_size = 3 ,
bool  L2gradient = false  
)

#include < opencv2/cudaimgproc.hpp >

创建实现,为 cuda::CannyEdgeDetector .

Parameters
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 ).

◆  createTemplateMatching()

Ptr < TemplateMatching > cv::cuda::createTemplateMatching ( int  srcType ,
int  method ,
Size   user_block_size = Size ()  
)

#include < opencv2/cudaimgproc.hpp >

创建实现,为 cuda::TemplateMatching .

Parameters
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:

  • CV_TM_SQDIFF
  • CV_TM_SQDIFF_NORMED
  • CV_TM_CCORR
  • CV_TM_CCORR_NORMED
  • CV_TM_CCOEFF
  • CV_TM_CCOEFF_NORMED

The following methods are supported for the CV_32F images for now:

  • CV_TM_SQDIFF
  • CV_TM_CCORR
另请参阅
matchTemplate

◆  meanShiftFiltering()

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.

Parameters
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.

◆  meanShiftProc()

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.

Parameters
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.
另请参阅
cuda::meanShiftFiltering

◆  meanShiftSegmentation()

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.

Parameters
src Source image. Only CV_8UC4 images are supported for now.
dst Segmented image with the same size and type as src (host or gpu 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.