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gapi: buildOpticalFlowPyramid() interface, CPUkernel and CPUtests implementation

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- kernel added to a cv::gapi::video namespace
     - tests to check a kernels (based on cv::video tests for cv::buildOpticalFlowPyramid())
     - tests for a combined G-API-pipeline (buildOpticalFlowPyramid() -> calcOpticalFlowPyrLK())
     - tests for internal purposes added
     - custom function for comparison in tests implemented
This commit is contained in:
OrestChura
2020-04-14 00:53:01 +03:00
parent f19d0ae41d
commit 05d5c284f6
11 changed files with 487 additions and 41 deletions
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modules/gapi/include/opencv2/gapi/cpu/gcpukernel.hpp
+6
View File
@@ -256,6 +256,12 @@ template<typename U> struct get_out<cv::GArray<U>>
return ctx.outVecR<U>(idx);
}
};
//FIXME(dm): GArray<Mat>/GArray<GMat> conversion should be done more gracefully in the system
template<> struct get_out<cv::GArray<cv::GMat> >: public get_out<cv::GArray<cv::Mat> >
{
};
template<typename U> struct get_out<cv::GOpaque<U>>
{
static U& get(GCPUContext &ctx, int idx)
modules/gapi/include/opencv2/gapi/video.hpp
+71 -30
View File
@@ -18,42 +18,83 @@
namespace cv { namespace gapi {
namespace video
{
using GOptFlowLKOutput = std::tuple<cv::GArray<cv::Point2f>,
cv::GArray<uchar>,
cv::GArray<float>>;
using GBuildPyrOutput = std::tuple<GArray<GMat>, GScalar>;
G_TYPED_KERNEL(GCalcOptFlowLK,
<GOptFlowLKOutput(GMat,GMat,cv::GArray<cv::Point2f>,cv::GArray<cv::Point2f>,Size,
int,TermCriteria,int,double)>,
"org.opencv.video.calcOpticalFlowPyrLK")
using GOptFlowLKOutput = std::tuple<cv::GArray<cv::Point2f>,
cv::GArray<uchar>,
cv::GArray<float>>;
G_TYPED_KERNEL(GBuildOptFlowPyramid, <GBuildPyrOutput(GMat,Size,GScalar,bool,int,int,bool)>,
"org.opencv.video.buildOpticalFlowPyramid")
{
static std::tuple<GArrayDesc,GScalarDesc>
outMeta(GMatDesc,const Size&,GScalarDesc,bool,int,int,bool)
{
static std::tuple<GArrayDesc,GArrayDesc,GArrayDesc> outMeta(GMatDesc,GMatDesc,GArrayDesc,
GArrayDesc,const Size&,int,
const TermCriteria&,int,double)
{
return std::make_tuple(empty_array_desc(), empty_array_desc(), empty_array_desc());
}
return std::make_tuple(empty_array_desc(), empty_scalar_desc());
}
};
};
G_TYPED_KERNEL(GCalcOptFlowLKForPyr,
<GOptFlowLKOutput(cv::GArray<cv::GMat>,cv::GArray<cv::GMat>,
cv::GArray<cv::Point2f>,cv::GArray<cv::Point2f>,Size,int,
TermCriteria,int,double)>,
"org.opencv.video.calcOpticalFlowPyrLKForPyr")
G_TYPED_KERNEL(GCalcOptFlowLK,
<GOptFlowLKOutput(GMat,GMat,cv::GArray<cv::Point2f>,cv::GArray<cv::Point2f>,Size,
GScalar,TermCriteria,int,double)>,
"org.opencv.video.calcOpticalFlowPyrLK")
{
static std::tuple<GArrayDesc,GArrayDesc,GArrayDesc> outMeta(GMatDesc,GMatDesc,GArrayDesc,
GArrayDesc,const Size&,GScalarDesc,
const TermCriteria&,int,double)
{
static std::tuple<GArrayDesc,GArrayDesc,GArrayDesc> outMeta(GArrayDesc,GArrayDesc,
GArrayDesc,GArrayDesc,
const Size&,int,
const TermCriteria&,int,double)
{
return std::make_tuple(empty_array_desc(), empty_array_desc(), empty_array_desc());
}
};
return std::make_tuple(empty_array_desc(), empty_array_desc(), empty_array_desc());
}
};
G_TYPED_KERNEL(GCalcOptFlowLKForPyr,
<GOptFlowLKOutput(cv::GArray<cv::GMat>,cv::GArray<cv::GMat>,
cv::GArray<cv::Point2f>,cv::GArray<cv::Point2f>,Size,GScalar,
TermCriteria,int,double)>,
"org.opencv.video.calcOpticalFlowPyrLKForPyr")
{
static std::tuple<GArrayDesc,GArrayDesc,GArrayDesc> outMeta(GArrayDesc,GArrayDesc,
GArrayDesc,GArrayDesc,
const Size&,GScalarDesc,
const TermCriteria&,int,double)
{
return std::make_tuple(empty_array_desc(), empty_array_desc(), empty_array_desc());
}
};
} //namespace video
//! @addtogroup gapi_video
//! @{
/** @brief Constructs the image pyramid which can be passed to calcOpticalFlowPyrLK.
@note Function textual ID is "org.opencv.video.buildOpticalFlowPyramid"
@param img 8-bit input image.
@param winSize window size of optical flow algorithm. Must be not less than winSize
argument of calcOpticalFlowPyrLK. It is needed to calculate required
padding for pyramid levels.
@param maxLevel 0-based maximal pyramid level number.
@param withDerivatives set to precompute gradients for the every pyramid level. If pyramid is
constructed without the gradients then calcOpticalFlowPyrLK will calculate
them internally.
@param pyrBorder the border mode for pyramid layers.
@param derivBorder the border mode for gradients.
@param tryReuseInputImage put ROI of input image into the pyramid if possible. You can pass false
to force data copying.
@return output pyramid.
@return number of levels in constructed pyramid. Can be less than maxLevel.
*/
GAPI_EXPORTS std::tuple<GArray<GMat>, GScalar>
buildOpticalFlowPyramid(const GMat &img,
const Size &winSize,
const GScalar &maxLevel,
bool withDerivatives = true,
int pyrBorder = BORDER_REFLECT_101,
int derivBorder = BORDER_CONSTANT,
bool tryReuseInputImage = true);
/** @brief Calculates an optical flow for a sparse feature set using the iterative Lucas-Kanade
method with pyramids.
@@ -104,7 +145,7 @@ calcOpticalFlowPyrLK(const GMat &prevImg,
const GArray<Point2f> &prevPts,
const GArray<Point2f> &predPts,
const Size &winSize = Size(21, 21),
int maxLevel = 3,
const GScalar &maxLevel = 3,
const TermCriteria &criteria = TermCriteria(TermCriteria::COUNT |
TermCriteria::EPS,
30, 0.01),
@@ -121,7 +162,7 @@ calcOpticalFlowPyrLK(const GArray<GMat> &prevPyr,
const GArray<Point2f> &prevPts,
const GArray<Point2f> &predPts,
const Size &winSize = Size(21, 21),
int maxLevel = 3,
const GScalar &maxLevel = 3,
const TermCriteria &criteria = TermCriteria(TermCriteria::COUNT |
TermCriteria::EPS,
30, 0.01),