mirror of
https://github.com/opencv/opencv.git
synced 2024-11-27 12:40:05 +08:00
samples(gpu): cleanup samples for legacy API
This commit is contained in:
Alexander Alekhin
parent
850053f9ca
commit
fc21b15d6e
@ -21,7 +21,6 @@ set(OPENCV_CUDA_SAMPLES_REQUIRED_DEPS
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opencv_cudaoptflow
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opencv_cudabgsegm
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opencv_cudastereo
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opencv_cudalegacy
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opencv_cudaobjdetect)
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ocv_check_dependencies(${OPENCV_CUDA_SAMPLES_REQUIRED_DEPS})
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@ -4,7 +4,6 @@
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#include "opencv2/core.hpp"
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#include "opencv2/core/utility.hpp"
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#include "opencv2/cudabgsegm.hpp"
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#include "opencv2/cudalegacy.hpp"
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#include "opencv2/video.hpp"
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#include "opencv2/highgui.hpp"
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@ -16,8 +15,6 @@ enum Method
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{
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MOG,
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MOG2,
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GMG,
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FGD_STAT
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};
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int main(int argc, const char** argv)
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@ -25,7 +22,7 @@ int main(int argc, const char** argv)
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cv::CommandLineParser cmd(argc, argv,
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"{ c camera | | use camera }"
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"{ f file | ../data/vtest.avi | input video file }"
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"{ m method | mog | method (mog, mog2, gmg, fgd) }"
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"{ m method | mog | method (mog, mog2) }"
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"{ h help | | print help message }");
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if (cmd.has("help") || !cmd.check())
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@ -40,9 +37,7 @@ int main(int argc, const char** argv)
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string method = cmd.get<string>("method");
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if (method != "mog"
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&& method != "mog2"
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&& method != "gmg"
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&& method != "fgd")
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&& method != "mog2")
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{
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cerr << "Incorrect method" << endl;
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return -1;
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@ -50,8 +45,8 @@ int main(int argc, const char** argv)
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Method m = method == "mog" ? MOG :
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method == "mog2" ? MOG2 :
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method == "fgd" ? FGD_STAT :
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GMG;
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(Method)-1;
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CV_Assert(m != (Method)-1);
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VideoCapture cap;
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@ -73,8 +68,6 @@ int main(int argc, const char** argv)
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Ptr<BackgroundSubtractor> mog = cuda::createBackgroundSubtractorMOG();
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Ptr<BackgroundSubtractor> mog2 = cuda::createBackgroundSubtractorMOG2();
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Ptr<BackgroundSubtractor> gmg = cuda::createBackgroundSubtractorGMG(40);
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Ptr<BackgroundSubtractor> fgd = cuda::createBackgroundSubtractorFGD();
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GpuMat d_fgmask;
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GpuMat d_fgimg;
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@ -93,23 +86,12 @@ int main(int argc, const char** argv)
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case MOG2:
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mog2->apply(d_frame, d_fgmask);
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break;
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case GMG:
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gmg->apply(d_frame, d_fgmask);
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break;
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case FGD_STAT:
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fgd->apply(d_frame, d_fgmask);
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break;
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}
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namedWindow("image", WINDOW_NORMAL);
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namedWindow("foreground mask", WINDOW_NORMAL);
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namedWindow("foreground image", WINDOW_NORMAL);
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if (m != GMG)
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{
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namedWindow("mean background image", WINDOW_NORMAL);
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}
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namedWindow("mean background image", WINDOW_NORMAL);
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for(;;)
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{
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@ -132,15 +114,6 @@ int main(int argc, const char** argv)
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mog2->apply(d_frame, d_fgmask);
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mog2->getBackgroundImage(d_bgimg);
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break;
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case GMG:
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gmg->apply(d_frame, d_fgmask);
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break;
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case FGD_STAT:
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fgd->apply(d_frame, d_fgmask);
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fgd->getBackgroundImage(d_bgimg);
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break;
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}
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double fps = cv::getTickFrequency() / (cv::getTickCount() - start);
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@ -1,388 +0,0 @@
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#if defined _MSC_VER && _MSC_VER >= 1400
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#pragma warning( disable : 4201 4408 4127 4100)
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#endif
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#include <iostream>
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#include <iomanip>
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#include <cstdio>
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#include "opencv2/core/cuda.hpp"
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#include "opencv2/cudalegacy.hpp"
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#include "opencv2/highgui.hpp"
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#include "opencv2/imgproc.hpp"
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#include "opencv2/objdetect.hpp"
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#include "opencv2/objdetect/objdetect_c.h"
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using namespace std;
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using namespace cv;
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#if !defined(HAVE_CUDA) || defined(__arm__)
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int main( int, const char** )
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{
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#if !defined(HAVE_CUDA)
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std::cout << "CUDA support is required (CMake key 'WITH_CUDA' must be true)." << std::endl;
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#endif
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#if defined(__arm__)
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std::cout << "Unsupported for ARM CUDA library." << std::endl;
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#endif
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return 0;
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}
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#else
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const Size2i preferredVideoFrameSize(640, 480);
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const cv::String wndTitle = "NVIDIA Computer Vision :: Haar Classifiers Cascade";
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static void matPrint(Mat &img, int lineOffsY, Scalar fontColor, const string &ss)
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{
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int fontFace = FONT_HERSHEY_DUPLEX;
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double fontScale = 0.8;
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int fontThickness = 2;
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Size fontSize = cv::getTextSize("T[]", fontFace, fontScale, fontThickness, 0);
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Point org;
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org.x = 1;
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org.y = 3 * fontSize.height * (lineOffsY + 1) / 2;
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putText(img, ss, org, fontFace, fontScale, Scalar(0,0,0), 5*fontThickness/2, 16);
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putText(img, ss, org, fontFace, fontScale, fontColor, fontThickness, 16);
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}
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static void displayState(Mat &canvas, bool bHelp, bool bGpu, bool bLargestFace, bool bFilter, double fps)
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{
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Scalar fontColorRed(0,0,255);
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Scalar fontColorNV(0,185,118);
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ostringstream ss;
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ss << "FPS = " << setprecision(1) << fixed << fps;
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matPrint(canvas, 0, fontColorRed, ss.str());
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ss.str("");
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ss << "[" << canvas.cols << "x" << canvas.rows << "], " <<
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(bGpu ? "GPU, " : "CPU, ") <<
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(bLargestFace ? "OneFace, " : "MultiFace, ") <<
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(bFilter ? "Filter:ON" : "Filter:OFF");
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matPrint(canvas, 1, fontColorRed, ss.str());
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if (bHelp)
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{
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matPrint(canvas, 2, fontColorNV, "Space - switch GPU / CPU");
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matPrint(canvas, 3, fontColorNV, "M - switch OneFace / MultiFace");
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matPrint(canvas, 4, fontColorNV, "F - toggle rectangles Filter");
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matPrint(canvas, 5, fontColorNV, "H - toggle hotkeys help");
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}
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else
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{
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matPrint(canvas, 2, fontColorNV, "H - toggle hotkeys help");
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}
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}
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static NCVStatus process(Mat *srcdst,
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Ncv32u width, Ncv32u height,
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NcvBool bFilterRects, NcvBool bLargestFace,
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HaarClassifierCascadeDescriptor &haar,
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NCVVector<HaarStage64> &d_haarStages, NCVVector<HaarClassifierNode128> &d_haarNodes,
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NCVVector<HaarFeature64> &d_haarFeatures, NCVVector<HaarStage64> &h_haarStages,
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INCVMemAllocator &gpuAllocator,
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INCVMemAllocator &cpuAllocator,
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cudaDeviceProp &devProp)
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{
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ncvAssertReturn(!((srcdst == NULL) ^ gpuAllocator.isCounting()), NCV_NULL_PTR);
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NCVStatus ncvStat;
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NCV_SET_SKIP_COND(gpuAllocator.isCounting());
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NCVMatrixAlloc<Ncv8u> d_src(gpuAllocator, width, height);
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ncvAssertReturn(d_src.isMemAllocated(), NCV_ALLOCATOR_BAD_ALLOC);
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NCVMatrixAlloc<Ncv8u> h_src(cpuAllocator, width, height);
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ncvAssertReturn(h_src.isMemAllocated(), NCV_ALLOCATOR_BAD_ALLOC);
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NCVVectorAlloc<NcvRect32u> d_rects(gpuAllocator, 100);
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ncvAssertReturn(d_rects.isMemAllocated(), NCV_ALLOCATOR_BAD_ALLOC);
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NCV_SKIP_COND_BEGIN
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for (Ncv32u i=0; i<(Ncv32u)srcdst->rows; i++)
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{
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memcpy(h_src.ptr() + i * h_src.stride(), srcdst->ptr(i), srcdst->cols);
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}
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ncvStat = h_src.copySolid(d_src, 0);
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ncvAssertReturnNcvStat(ncvStat);
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ncvAssertCUDAReturn(cudaStreamSynchronize(0), NCV_CUDA_ERROR);
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NCV_SKIP_COND_END
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NcvSize32u roi;
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roi.width = d_src.width();
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roi.height = d_src.height();
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Ncv32u numDetections;
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ncvStat = ncvDetectObjectsMultiScale_device(
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d_src, roi, d_rects, numDetections, haar, h_haarStages,
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d_haarStages, d_haarNodes, d_haarFeatures,
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haar.ClassifierSize,
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(bFilterRects || bLargestFace) ? 4 : 0,
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1.2f, 1,
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(bLargestFace ? NCVPipeObjDet_FindLargestObject : 0)
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| NCVPipeObjDet_VisualizeInPlace,
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gpuAllocator, cpuAllocator, devProp, 0);
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ncvAssertReturnNcvStat(ncvStat);
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ncvAssertCUDAReturn(cudaStreamSynchronize(0), NCV_CUDA_ERROR);
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NCV_SKIP_COND_BEGIN
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ncvStat = d_src.copySolid(h_src, 0);
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ncvAssertReturnNcvStat(ncvStat);
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ncvAssertCUDAReturn(cudaStreamSynchronize(0), NCV_CUDA_ERROR);
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for (Ncv32u i=0; i<(Ncv32u)srcdst->rows; i++)
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{
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memcpy(srcdst->ptr(i), h_src.ptr() + i * h_src.stride(), srcdst->cols);
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}
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NCV_SKIP_COND_END
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return NCV_SUCCESS;
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}
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int main(int argc, const char** argv)
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{
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cout << "OpenCV / NVIDIA Computer Vision" << endl;
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cout << "Face Detection in video and live feed" << endl;
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cout << "Syntax: exename <cascade_file> <image_or_video_or_cameraid>" << endl;
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cout << "=========================================" << endl;
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ncvAssertPrintReturn(cv::cuda::getCudaEnabledDeviceCount() != 0, "No GPU found or the library is compiled without CUDA support", -1);
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ncvAssertPrintReturn(argc == 3, "Invalid number of arguments", -1);
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cv::cuda::printShortCudaDeviceInfo(cv::cuda::getDevice());
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string cascadeName = argv[1];
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string inputName = argv[2];
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NCVStatus ncvStat;
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NcvBool bQuit = false;
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VideoCapture capture;
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Size2i frameSize;
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//open content source
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Mat image = imread(inputName);
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Mat frame;
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if (!image.empty())
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{
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frameSize.width = image.cols;
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frameSize.height = image.rows;
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}
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else
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{
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if (!capture.open(inputName))
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{
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int camid = -1;
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istringstream ss(inputName);
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int x = 0;
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ss >> x;
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ncvAssertPrintReturn(capture.open(camid) != 0, "Can't open source", -1);
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}
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capture >> frame;
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ncvAssertPrintReturn(!frame.empty(), "Empty video source", -1);
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frameSize.width = frame.cols;
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frameSize.height = frame.rows;
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}
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NcvBool bUseGPU = true;
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NcvBool bLargestObject = false;
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NcvBool bFilterRects = true;
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NcvBool bHelpScreen = false;
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CascadeClassifier classifierOpenCV;
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ncvAssertPrintReturn(classifierOpenCV.load(cascadeName) != 0, "Error (in OpenCV) opening classifier", -1);
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int devId;
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ncvAssertCUDAReturn(cudaGetDevice(&devId), -1);
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cudaDeviceProp devProp;
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ncvAssertCUDAReturn(cudaGetDeviceProperties(&devProp, devId), -1);
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cout << "Using GPU: " << devId << "(" << devProp.name <<
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"), arch=" << devProp.major << "." << devProp.minor << endl;
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//==============================================================================
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//
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// Load the classifier from file (assuming its size is about 1 mb)
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// using a simple allocator
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//
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//==============================================================================
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NCVMemNativeAllocator gpuCascadeAllocator(NCVMemoryTypeDevice, static_cast<Ncv32u>(devProp.textureAlignment));
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ncvAssertPrintReturn(gpuCascadeAllocator.isInitialized(), "Error creating cascade GPU allocator", -1);
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NCVMemNativeAllocator cpuCascadeAllocator(NCVMemoryTypeHostPinned, static_cast<Ncv32u>(devProp.textureAlignment));
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ncvAssertPrintReturn(cpuCascadeAllocator.isInitialized(), "Error creating cascade CPU allocator", -1);
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Ncv32u haarNumStages, haarNumNodes, haarNumFeatures;
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ncvStat = ncvHaarGetClassifierSize(cascadeName, haarNumStages, haarNumNodes, haarNumFeatures);
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ncvAssertPrintReturn(ncvStat == NCV_SUCCESS, "Error reading classifier size (check the file)", -1);
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NCVVectorAlloc<HaarStage64> h_haarStages(cpuCascadeAllocator, haarNumStages);
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ncvAssertPrintReturn(h_haarStages.isMemAllocated(), "Error in cascade CPU allocator", -1);
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NCVVectorAlloc<HaarClassifierNode128> h_haarNodes(cpuCascadeAllocator, haarNumNodes);
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ncvAssertPrintReturn(h_haarNodes.isMemAllocated(), "Error in cascade CPU allocator", -1);
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NCVVectorAlloc<HaarFeature64> h_haarFeatures(cpuCascadeAllocator, haarNumFeatures);
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ncvAssertPrintReturn(h_haarFeatures.isMemAllocated(), "Error in cascade CPU allocator", -1);
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HaarClassifierCascadeDescriptor haar;
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ncvStat = ncvHaarLoadFromFile_host(cascadeName, haar, h_haarStages, h_haarNodes, h_haarFeatures);
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ncvAssertPrintReturn(ncvStat == NCV_SUCCESS, "Error loading classifier", -1);
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NCVVectorAlloc<HaarStage64> d_haarStages(gpuCascadeAllocator, haarNumStages);
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ncvAssertPrintReturn(d_haarStages.isMemAllocated(), "Error in cascade GPU allocator", -1);
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NCVVectorAlloc<HaarClassifierNode128> d_haarNodes(gpuCascadeAllocator, haarNumNodes);
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ncvAssertPrintReturn(d_haarNodes.isMemAllocated(), "Error in cascade GPU allocator", -1);
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NCVVectorAlloc<HaarFeature64> d_haarFeatures(gpuCascadeAllocator, haarNumFeatures);
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ncvAssertPrintReturn(d_haarFeatures.isMemAllocated(), "Error in cascade GPU allocator", -1);
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ncvStat = h_haarStages.copySolid(d_haarStages, 0);
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ncvAssertPrintReturn(ncvStat == NCV_SUCCESS, "Error copying cascade to GPU", -1);
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ncvStat = h_haarNodes.copySolid(d_haarNodes, 0);
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ncvAssertPrintReturn(ncvStat == NCV_SUCCESS, "Error copying cascade to GPU", -1);
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ncvStat = h_haarFeatures.copySolid(d_haarFeatures, 0);
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ncvAssertPrintReturn(ncvStat == NCV_SUCCESS, "Error copying cascade to GPU", -1);
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//==============================================================================
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//
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// Calculate memory requirements and create real allocators
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//
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//==============================================================================
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NCVMemStackAllocator gpuCounter(static_cast<Ncv32u>(devProp.textureAlignment));
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ncvAssertPrintReturn(gpuCounter.isInitialized(), "Error creating GPU memory counter", -1);
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NCVMemStackAllocator cpuCounter(static_cast<Ncv32u>(devProp.textureAlignment));
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ncvAssertPrintReturn(cpuCounter.isInitialized(), "Error creating CPU memory counter", -1);
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ncvStat = process(NULL, frameSize.width, frameSize.height,
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false, false, haar,
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d_haarStages, d_haarNodes,
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d_haarFeatures, h_haarStages,
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gpuCounter, cpuCounter, devProp);
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ncvAssertPrintReturn(ncvStat == NCV_SUCCESS, "Error in memory counting pass", -1);
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NCVMemStackAllocator gpuAllocator(NCVMemoryTypeDevice, gpuCounter.maxSize(), static_cast<Ncv32u>(devProp.textureAlignment));
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ncvAssertPrintReturn(gpuAllocator.isInitialized(), "Error creating GPU memory allocator", -1);
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NCVMemStackAllocator cpuAllocator(NCVMemoryTypeHostPinned, cpuCounter.maxSize(), static_cast<Ncv32u>(devProp.textureAlignment));
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ncvAssertPrintReturn(cpuAllocator.isInitialized(), "Error creating CPU memory allocator", -1);
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printf("Initialized for frame size [%dx%d]\n", frameSize.width, frameSize.height);
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//==============================================================================
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//
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// Main processing loop
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//
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//==============================================================================
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namedWindow(wndTitle, 1);
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Mat frameDisp;
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do
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{
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Mat gray;
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cvtColor((image.empty() ? frame : image), gray, cv::COLOR_BGR2GRAY);
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//
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// process
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//
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NcvSize32u minSize = haar.ClassifierSize;
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if (bLargestObject)
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{
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Ncv32u ratioX = preferredVideoFrameSize.width / minSize.width;
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Ncv32u ratioY = preferredVideoFrameSize.height / minSize.height;
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Ncv32u ratioSmallest = min(ratioX, ratioY);
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ratioSmallest = max((Ncv32u)(ratioSmallest / 2.5f), (Ncv32u)1);
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minSize.width *= ratioSmallest;
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minSize.height *= ratioSmallest;
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}
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Ncv32f avgTime;
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NcvTimer timer = ncvStartTimer();
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if (bUseGPU)
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{
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ncvStat = process(&gray, frameSize.width, frameSize.height,
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bFilterRects, bLargestObject, haar,
|
||||
d_haarStages, d_haarNodes,
|
||||
d_haarFeatures, h_haarStages,
|
||||
gpuAllocator, cpuAllocator, devProp);
|
||||
ncvAssertPrintReturn(ncvStat == NCV_SUCCESS, "Error in memory counting pass", -1);
|
||||
}
|
||||
else
|
||||
{
|
||||
vector<Rect> rectsOpenCV;
|
||||
|
||||
classifierOpenCV.detectMultiScale(
|
||||
gray,
|
||||
rectsOpenCV,
|
||||
1.2f,
|
||||
bFilterRects ? 4 : 0,
|
||||
(bLargestObject ? CV_HAAR_FIND_BIGGEST_OBJECT : 0)
|
||||
| CV_HAAR_SCALE_IMAGE,
|
||||
Size(minSize.width, minSize.height));
|
||||
|
||||
for (size_t rt = 0; rt < rectsOpenCV.size(); ++rt)
|
||||
rectangle(gray, rectsOpenCV[rt], Scalar(255));
|
||||
}
|
||||
|
||||
avgTime = (Ncv32f)ncvEndQueryTimerMs(timer);
|
||||
|
||||
cvtColor(gray, frameDisp, cv::COLOR_GRAY2BGR);
|
||||
displayState(frameDisp, bHelpScreen, bUseGPU, bLargestObject, bFilterRects, 1000.0f / avgTime);
|
||||
imshow(wndTitle, frameDisp);
|
||||
|
||||
//handle input
|
||||
switch (cv::waitKey(3))
|
||||
{
|
||||
case ' ':
|
||||
bUseGPU = !bUseGPU;
|
||||
break;
|
||||
case 'm':
|
||||
case 'M':
|
||||
bLargestObject = !bLargestObject;
|
||||
break;
|
||||
case 'f':
|
||||
case 'F':
|
||||
bFilterRects = !bFilterRects;
|
||||
break;
|
||||
case 'h':
|
||||
case 'H':
|
||||
bHelpScreen = !bHelpScreen;
|
||||
break;
|
||||
case 27:
|
||||
bQuit = true;
|
||||
break;
|
||||
}
|
||||
|
||||
// For camera and video file, capture the next image
|
||||
if (capture.isOpened())
|
||||
{
|
||||
capture >> frame;
|
||||
if (frame.empty())
|
||||
{
|
||||
break;
|
||||
}
|
||||
}
|
||||
} while (!bQuit);
|
||||
|
||||
cv::destroyWindow(wndTitle);
|
||||
|
||||
return 0;
|
||||
}
|
||||
|
||||
#endif //!defined(HAVE_CUDA)
|
||||
@ -1,651 +0,0 @@
|
||||
#if defined _MSC_VER && _MSC_VER >= 1400
|
||||
#pragma warning( disable : 4201 4408 4127 4100)
|
||||
#endif
|
||||
|
||||
#include <iostream>
|
||||
#include <iomanip>
|
||||
#include <memory>
|
||||
#include <exception>
|
||||
#include <ctime>
|
||||
#include <ctype.h>
|
||||
|
||||
#include <iostream>
|
||||
#include <iomanip>
|
||||
#include "opencv2/core/cuda.hpp"
|
||||
#include "opencv2/cudalegacy.hpp"
|
||||
#include "opencv2/highgui.hpp"
|
||||
|
||||
#include "opencv2/core/core_c.h" // FIXIT legacy API
|
||||
#include "opencv2/highgui/highgui_c.h" // FIXIT legacy API
|
||||
|
||||
#if !defined(HAVE_CUDA)
|
||||
int main( int, const char** )
|
||||
{
|
||||
std::cout << "Please compile the library with CUDA support" << std::endl;
|
||||
return -1;
|
||||
}
|
||||
#else
|
||||
|
||||
//using std::shared_ptr;
|
||||
using cv::Ptr;
|
||||
|
||||
#define PARAM_LEFT "--left"
|
||||
#define PARAM_RIGHT "--right"
|
||||
#define PARAM_SCALE "--scale"
|
||||
#define PARAM_ALPHA "--alpha"
|
||||
#define PARAM_GAMMA "--gamma"
|
||||
#define PARAM_INNER "--inner"
|
||||
#define PARAM_OUTER "--outer"
|
||||
#define PARAM_SOLVER "--solver"
|
||||
#define PARAM_TIME_STEP "--time-step"
|
||||
#define PARAM_HELP "--help"
|
||||
|
||||
Ptr<INCVMemAllocator> g_pGPUMemAllocator;
|
||||
Ptr<INCVMemAllocator> g_pHostMemAllocator;
|
||||
|
||||
class RgbToMonochrome
|
||||
{
|
||||
public:
|
||||
float operator ()(unsigned char b, unsigned char g, unsigned char r)
|
||||
{
|
||||
float _r = static_cast<float>(r)/255.0f;
|
||||
float _g = static_cast<float>(g)/255.0f;
|
||||
float _b = static_cast<float>(b)/255.0f;
|
||||
return (_r + _g + _b)/3.0f;
|
||||
}
|
||||
};
|
||||
|
||||
class RgbToR
|
||||
{
|
||||
public:
|
||||
float operator ()(unsigned char /*b*/, unsigned char /*g*/, unsigned char r)
|
||||
{
|
||||
return static_cast<float>(r)/255.0f;
|
||||
}
|
||||
};
|
||||
|
||||
|
||||
class RgbToG
|
||||
{
|
||||
public:
|
||||
float operator ()(unsigned char /*b*/, unsigned char g, unsigned char /*r*/)
|
||||
{
|
||||
return static_cast<float>(g)/255.0f;
|
||||
}
|
||||
};
|
||||
|
||||
class RgbToB
|
||||
{
|
||||
public:
|
||||
float operator ()(unsigned char b, unsigned char /*g*/, unsigned char /*r*/)
|
||||
{
|
||||
return static_cast<float>(b)/255.0f;
|
||||
}
|
||||
};
|
||||
|
||||
template<class T>
|
||||
NCVStatus CopyData(IplImage *image, Ptr<NCVMatrixAlloc<Ncv32f> >& dst)
|
||||
{
|
||||
dst = Ptr<NCVMatrixAlloc<Ncv32f> > (new NCVMatrixAlloc<Ncv32f> (*g_pHostMemAllocator, image->width, image->height));
|
||||
ncvAssertReturn (dst->isMemAllocated (), NCV_ALLOCATOR_BAD_ALLOC);
|
||||
|
||||
unsigned char *row = reinterpret_cast<unsigned char*> (image->imageData);
|
||||
T convert;
|
||||
for (int i = 0; i < image->height; ++i)
|
||||
{
|
||||
for (int j = 0; j < image->width; ++j)
|
||||
{
|
||||
if (image->nChannels < 3)
|
||||
{
|
||||
dst->ptr ()[j + i*dst->stride ()] = static_cast<float> (*(row + j*image->nChannels))/255.0f;
|
||||
}
|
||||
else
|
||||
{
|
||||
unsigned char *color = row + j * image->nChannels;
|
||||
dst->ptr ()[j +i*dst->stride ()] = convert (color[0], color[1], color[2]);
|
||||
}
|
||||
}
|
||||
row += image->widthStep;
|
||||
}
|
||||
return NCV_SUCCESS;
|
||||
}
|
||||
|
||||
template<class T>
|
||||
NCVStatus CopyData(const IplImage *image, const NCVMatrixAlloc<Ncv32f> &dst)
|
||||
{
|
||||
unsigned char *row = reinterpret_cast<unsigned char*> (image->imageData);
|
||||
T convert;
|
||||
for (int i = 0; i < image->height; ++i)
|
||||
{
|
||||
for (int j = 0; j < image->width; ++j)
|
||||
{
|
||||
if (image->nChannels < 3)
|
||||
{
|
||||
dst.ptr ()[j + i*dst.stride ()] = static_cast<float>(*(row + j*image->nChannels))/255.0f;
|
||||
}
|
||||
else
|
||||
{
|
||||
unsigned char *color = row + j * image->nChannels;
|
||||
dst.ptr ()[j +i*dst.stride()] = convert (color[0], color[1], color[2]);
|
||||
}
|
||||
}
|
||||
row += image->widthStep;
|
||||
}
|
||||
return NCV_SUCCESS;
|
||||
}
|
||||
|
||||
static NCVStatus LoadImages (const char *frame0Name,
|
||||
const char *frame1Name,
|
||||
int &width,
|
||||
int &height,
|
||||
Ptr<NCVMatrixAlloc<Ncv32f> > &src,
|
||||
Ptr<NCVMatrixAlloc<Ncv32f> > &dst,
|
||||
IplImage *&firstFrame,
|
||||
IplImage *&lastFrame)
|
||||
{
|
||||
IplImage *image;
|
||||
image = cvLoadImage (frame0Name);
|
||||
if (image == 0)
|
||||
{
|
||||
std::cout << "Could not open '" << frame0Name << "'\n";
|
||||
return NCV_FILE_ERROR;
|
||||
}
|
||||
|
||||
firstFrame = image;
|
||||
// copy data to src
|
||||
ncvAssertReturnNcvStat (CopyData<RgbToMonochrome> (image, src));
|
||||
|
||||
IplImage *image2;
|
||||
image2 = cvLoadImage (frame1Name);
|
||||
if (image2 == 0)
|
||||
{
|
||||
std::cout << "Could not open '" << frame1Name << "'\n";
|
||||
return NCV_FILE_ERROR;
|
||||
}
|
||||
lastFrame = image2;
|
||||
|
||||
ncvAssertReturnNcvStat (CopyData<RgbToMonochrome> (image2, dst));
|
||||
|
||||
width = image->width;
|
||||
height = image->height;
|
||||
|
||||
return NCV_SUCCESS;
|
||||
}
|
||||
|
||||
template<typename T>
|
||||
inline T Clamp (T x, T a, T b)
|
||||
{
|
||||
return ((x) > (a) ? ((x) < (b) ? (x) : (b)) : (a));
|
||||
}
|
||||
|
||||
template<typename T>
|
||||
inline T MapValue (T x, T a, T b, T c, T d)
|
||||
{
|
||||
x = Clamp (x, a, b);
|
||||
return c + (d - c) * (x - a) / (b - a);
|
||||
}
|
||||
|
||||
static NCVStatus ShowFlow (NCVMatrixAlloc<Ncv32f> &u, NCVMatrixAlloc<Ncv32f> &v, const char *name)
|
||||
{
|
||||
IplImage *flowField;
|
||||
|
||||
NCVMatrixAlloc<Ncv32f> host_u(*g_pHostMemAllocator, u.width(), u.height());
|
||||
ncvAssertReturn(host_u.isMemAllocated(), NCV_ALLOCATOR_BAD_ALLOC);
|
||||
|
||||
NCVMatrixAlloc<Ncv32f> host_v (*g_pHostMemAllocator, u.width (), u.height ());
|
||||
ncvAssertReturn (host_v.isMemAllocated (), NCV_ALLOCATOR_BAD_ALLOC);
|
||||
|
||||
ncvAssertReturnNcvStat (u.copySolid (host_u, 0));
|
||||
ncvAssertReturnNcvStat (v.copySolid (host_v, 0));
|
||||
|
||||
float *ptr_u = host_u.ptr ();
|
||||
float *ptr_v = host_v.ptr ();
|
||||
|
||||
float maxDisplacement = 1.0f;
|
||||
|
||||
for (Ncv32u i = 0; i < u.height (); ++i)
|
||||
{
|
||||
for (Ncv32u j = 0; j < u.width (); ++j)
|
||||
{
|
||||
float d = std::max ( fabsf(*ptr_u), fabsf(*ptr_v) );
|
||||
if (d > maxDisplacement) maxDisplacement = d;
|
||||
++ptr_u;
|
||||
++ptr_v;
|
||||
}
|
||||
ptr_u += u.stride () - u.width ();
|
||||
ptr_v += v.stride () - v.width ();
|
||||
}
|
||||
|
||||
CvSize image_size = cvSize (u.width (), u.height ());
|
||||
flowField = cvCreateImage (image_size, IPL_DEPTH_8U, 4);
|
||||
if (flowField == 0) return NCV_NULL_PTR;
|
||||
|
||||
unsigned char *row = reinterpret_cast<unsigned char *> (flowField->imageData);
|
||||
|
||||
ptr_u = host_u.ptr();
|
||||
ptr_v = host_v.ptr();
|
||||
for (int i = 0; i < flowField->height; ++i)
|
||||
{
|
||||
for (int j = 0; j < flowField->width; ++j)
|
||||
{
|
||||
(row + j * flowField->nChannels)[0] = 0;
|
||||
(row + j * flowField->nChannels)[1] = static_cast<unsigned char> (MapValue (-(*ptr_v), -maxDisplacement, maxDisplacement, 0.0f, 255.0f));
|
||||
(row + j * flowField->nChannels)[2] = static_cast<unsigned char> (MapValue (*ptr_u , -maxDisplacement, maxDisplacement, 0.0f, 255.0f));
|
||||
(row + j * flowField->nChannels)[3] = 255;
|
||||
++ptr_u;
|
||||
++ptr_v;
|
||||
}
|
||||
row += flowField->widthStep;
|
||||
ptr_u += u.stride () - u.width ();
|
||||
ptr_v += v.stride () - v.width ();
|
||||
}
|
||||
|
||||
cvShowImage (name, flowField);
|
||||
|
||||
return NCV_SUCCESS;
|
||||
}
|
||||
|
||||
static IplImage *CreateImage (NCVMatrixAlloc<Ncv32f> &h_r, NCVMatrixAlloc<Ncv32f> &h_g, NCVMatrixAlloc<Ncv32f> &h_b)
|
||||
{
|
||||
CvSize imageSize = cvSize (h_r.width (), h_r.height ());
|
||||
IplImage *image = cvCreateImage (imageSize, IPL_DEPTH_8U, 4);
|
||||
if (image == 0) return 0;
|
||||
|
||||
unsigned char *row = reinterpret_cast<unsigned char*> (image->imageData);
|
||||
|
||||
for (int i = 0; i < image->height; ++i)
|
||||
{
|
||||
for (int j = 0; j < image->width; ++j)
|
||||
{
|
||||
int offset = j * image->nChannels;
|
||||
int pos = i * h_r.stride () + j;
|
||||
row[offset + 0] = static_cast<unsigned char> (h_b.ptr ()[pos] * 255.0f);
|
||||
row[offset + 1] = static_cast<unsigned char> (h_g.ptr ()[pos] * 255.0f);
|
||||
row[offset + 2] = static_cast<unsigned char> (h_r.ptr ()[pos] * 255.0f);
|
||||
row[offset + 3] = 255;
|
||||
}
|
||||
row += image->widthStep;
|
||||
}
|
||||
return image;
|
||||
}
|
||||
|
||||
static void PrintHelp ()
|
||||
{
|
||||
std::cout << "Usage help:\n";
|
||||
std::cout << std::setiosflags(std::ios::left);
|
||||
std::cout << "\t" << std::setw(15) << PARAM_ALPHA << " - set alpha\n";
|
||||
std::cout << "\t" << std::setw(15) << PARAM_GAMMA << " - set gamma\n";
|
||||
std::cout << "\t" << std::setw(15) << PARAM_INNER << " - set number of inner iterations\n";
|
||||
std::cout << "\t" << std::setw(15) << PARAM_LEFT << " - specify left image\n";
|
||||
std::cout << "\t" << std::setw(15) << PARAM_RIGHT << " - specify right image\n";
|
||||
std::cout << "\t" << std::setw(15) << PARAM_OUTER << " - set number of outer iterations\n";
|
||||
std::cout << "\t" << std::setw(15) << PARAM_SCALE << " - set pyramid scale factor\n";
|
||||
std::cout << "\t" << std::setw(15) << PARAM_SOLVER << " - set number of basic solver iterations\n";
|
||||
std::cout << "\t" << std::setw(15) << PARAM_TIME_STEP << " - set frame interpolation time step\n";
|
||||
std::cout << "\t" << std::setw(15) << PARAM_HELP << " - display this help message\n";
|
||||
}
|
||||
|
||||
static int ProcessCommandLine(int argc, char **argv,
|
||||
Ncv32f &timeStep,
|
||||
char *&frame0Name,
|
||||
char *&frame1Name,
|
||||
NCVBroxOpticalFlowDescriptor &desc)
|
||||
{
|
||||
timeStep = 0.25f;
|
||||
for (int iarg = 1; iarg < argc; ++iarg)
|
||||
{
|
||||
if (strcmp(argv[iarg], PARAM_LEFT) == 0)
|
||||
{
|
||||
if (iarg + 1 < argc)
|
||||
{
|
||||
frame0Name = argv[++iarg];
|
||||
}
|
||||
else
|
||||
return -1;
|
||||
}
|
||||
if (strcmp(argv[iarg], PARAM_RIGHT) == 0)
|
||||
{
|
||||
if (iarg + 1 < argc)
|
||||
{
|
||||
frame1Name = argv[++iarg];
|
||||
}
|
||||
else
|
||||
return -1;
|
||||
}
|
||||
else if(strcmp(argv[iarg], PARAM_SCALE) == 0)
|
||||
{
|
||||
if (iarg + 1 < argc)
|
||||
desc.scale_factor = static_cast<Ncv32f>(atof(argv[++iarg]));
|
||||
else
|
||||
return -1;
|
||||
}
|
||||
else if(strcmp(argv[iarg], PARAM_ALPHA) == 0)
|
||||
{
|
||||
if (iarg + 1 < argc)
|
||||
desc.alpha = static_cast<Ncv32f>(atof(argv[++iarg]));
|
||||
else
|
||||
return -1;
|
||||
}
|
||||
else if(strcmp(argv[iarg], PARAM_GAMMA) == 0)
|
||||
{
|
||||
if (iarg + 1 < argc)
|
||||
desc.gamma = static_cast<Ncv32f>(atof(argv[++iarg]));
|
||||
else
|
||||
return -1;
|
||||
}
|
||||
else if(strcmp(argv[iarg], PARAM_INNER) == 0)
|
||||
{
|
||||
if (iarg + 1 < argc)
|
||||
desc.number_of_inner_iterations = static_cast<Ncv32u>(atoi(argv[++iarg]));
|
||||
else
|
||||
return -1;
|
||||
}
|
||||
else if(strcmp(argv[iarg], PARAM_OUTER) == 0)
|
||||
{
|
||||
if (iarg + 1 < argc)
|
||||
desc.number_of_outer_iterations = static_cast<Ncv32u>(atoi(argv[++iarg]));
|
||||
else
|
||||
return -1;
|
||||
}
|
||||
else if(strcmp(argv[iarg], PARAM_SOLVER) == 0)
|
||||
{
|
||||
if (iarg + 1 < argc)
|
||||
desc.number_of_solver_iterations = static_cast<Ncv32u>(atoi(argv[++iarg]));
|
||||
else
|
||||
return -1;
|
||||
}
|
||||
else if(strcmp(argv[iarg], PARAM_TIME_STEP) == 0)
|
||||
{
|
||||
if (iarg + 1 < argc)
|
||||
timeStep = static_cast<Ncv32f>(atof(argv[++iarg]));
|
||||
else
|
||||
return -1;
|
||||
}
|
||||
else if(strcmp(argv[iarg], PARAM_HELP) == 0)
|
||||
{
|
||||
PrintHelp ();
|
||||
return 0;
|
||||
}
|
||||
}
|
||||
return 0;
|
||||
}
|
||||
|
||||
|
||||
int main(int argc, char **argv)
|
||||
{
|
||||
char *frame0Name = 0, *frame1Name = 0;
|
||||
Ncv32f timeStep = 0.01f;
|
||||
|
||||
NCVBroxOpticalFlowDescriptor desc;
|
||||
|
||||
desc.alpha = 0.197f;
|
||||
desc.gamma = 50.0f;
|
||||
desc.number_of_inner_iterations = 10;
|
||||
desc.number_of_outer_iterations = 77;
|
||||
desc.number_of_solver_iterations = 10;
|
||||
desc.scale_factor = 0.8f;
|
||||
|
||||
int result = ProcessCommandLine (argc, argv, timeStep, frame0Name, frame1Name, desc);
|
||||
if (argc == 1 || result)
|
||||
{
|
||||
PrintHelp();
|
||||
return result;
|
||||
}
|
||||
|
||||
cv::cuda::printShortCudaDeviceInfo(cv::cuda::getDevice());
|
||||
|
||||
std::cout << "OpenCV / NVIDIA Computer Vision\n";
|
||||
std::cout << "Optical Flow Demo: Frame Interpolation\n";
|
||||
std::cout << "=========================================\n";
|
||||
std::cout << "Press:\n ESC to quit\n 'a' to move to the previous frame\n 's' to move to the next frame\n";
|
||||
|
||||
int devId;
|
||||
ncvAssertCUDAReturn(cudaGetDevice(&devId), -1);
|
||||
cudaDeviceProp devProp;
|
||||
ncvAssertCUDAReturn(cudaGetDeviceProperties(&devProp, devId), -1);
|
||||
std::cout << "Using GPU: " << devId << "(" << devProp.name <<
|
||||
"), arch=" << devProp.major << "." << devProp.minor << std::endl;
|
||||
|
||||
g_pGPUMemAllocator = Ptr<INCVMemAllocator> (new NCVMemNativeAllocator (NCVMemoryTypeDevice, static_cast<Ncv32u>(devProp.textureAlignment)));
|
||||
ncvAssertPrintReturn (g_pGPUMemAllocator->isInitialized (), "Device memory allocator isn't initialized", -1);
|
||||
|
||||
g_pHostMemAllocator = Ptr<INCVMemAllocator> (new NCVMemNativeAllocator (NCVMemoryTypeHostPageable, static_cast<Ncv32u>(devProp.textureAlignment)));
|
||||
ncvAssertPrintReturn (g_pHostMemAllocator->isInitialized (), "Host memory allocator isn't initialized", -1);
|
||||
|
||||
int width, height;
|
||||
|
||||
Ptr<NCVMatrixAlloc<Ncv32f> > src_host;
|
||||
Ptr<NCVMatrixAlloc<Ncv32f> > dst_host;
|
||||
|
||||
IplImage *firstFrame, *lastFrame;
|
||||
if (frame0Name != 0 && frame1Name != 0)
|
||||
{
|
||||
ncvAssertReturnNcvStat (LoadImages (frame0Name, frame1Name, width, height, src_host, dst_host, firstFrame, lastFrame));
|
||||
}
|
||||
else
|
||||
{
|
||||
ncvAssertReturnNcvStat (LoadImages ("frame10.bmp", "frame11.bmp", width, height, src_host, dst_host, firstFrame, lastFrame));
|
||||
}
|
||||
|
||||
Ptr<NCVMatrixAlloc<Ncv32f> > src (new NCVMatrixAlloc<Ncv32f> (*g_pGPUMemAllocator, src_host->width (), src_host->height ()));
|
||||
ncvAssertReturn(src->isMemAllocated(), -1);
|
||||
|
||||
Ptr<NCVMatrixAlloc<Ncv32f> > dst (new NCVMatrixAlloc<Ncv32f> (*g_pGPUMemAllocator, src_host->width (), src_host->height ()));
|
||||
ncvAssertReturn (dst->isMemAllocated (), -1);
|
||||
|
||||
ncvAssertReturnNcvStat (src_host->copySolid ( *src, 0 ));
|
||||
ncvAssertReturnNcvStat (dst_host->copySolid ( *dst, 0 ));
|
||||
|
||||
#if defined SAFE_MAT_DECL
|
||||
#undef SAFE_MAT_DECL
|
||||
#endif
|
||||
#define SAFE_MAT_DECL(name, allocator, sx, sy) \
|
||||
NCVMatrixAlloc<Ncv32f> name(*allocator, sx, sy);\
|
||||
ncvAssertReturn(name.isMemAllocated(), -1);
|
||||
|
||||
SAFE_MAT_DECL (u, g_pGPUMemAllocator, width, height);
|
||||
SAFE_MAT_DECL (v, g_pGPUMemAllocator, width, height);
|
||||
|
||||
SAFE_MAT_DECL (uBck, g_pGPUMemAllocator, width, height);
|
||||
SAFE_MAT_DECL (vBck, g_pGPUMemAllocator, width, height);
|
||||
|
||||
SAFE_MAT_DECL (h_r, g_pHostMemAllocator, width, height);
|
||||
SAFE_MAT_DECL (h_g, g_pHostMemAllocator, width, height);
|
||||
SAFE_MAT_DECL (h_b, g_pHostMemAllocator, width, height);
|
||||
|
||||
std::cout << "Estimating optical flow\nForward...\n";
|
||||
|
||||
if (NCV_SUCCESS != NCVBroxOpticalFlow (desc, *g_pGPUMemAllocator, *src, *dst, u, v, 0))
|
||||
{
|
||||
std::cout << "Failed\n";
|
||||
return -1;
|
||||
}
|
||||
|
||||
std::cout << "Backward...\n";
|
||||
if (NCV_SUCCESS != NCVBroxOpticalFlow (desc, *g_pGPUMemAllocator, *dst, *src, uBck, vBck, 0))
|
||||
{
|
||||
std::cout << "Failed\n";
|
||||
return -1;
|
||||
}
|
||||
|
||||
// matrix for temporary data
|
||||
SAFE_MAT_DECL (d_temp, g_pGPUMemAllocator, width, height);
|
||||
|
||||
// first frame color components (GPU memory)
|
||||
SAFE_MAT_DECL (d_r, g_pGPUMemAllocator, width, height);
|
||||
SAFE_MAT_DECL (d_g, g_pGPUMemAllocator, width, height);
|
||||
SAFE_MAT_DECL (d_b, g_pGPUMemAllocator, width, height);
|
||||
|
||||
// second frame color components (GPU memory)
|
||||
SAFE_MAT_DECL (d_rt, g_pGPUMemAllocator, width, height);
|
||||
SAFE_MAT_DECL (d_gt, g_pGPUMemAllocator, width, height);
|
||||
SAFE_MAT_DECL (d_bt, g_pGPUMemAllocator, width, height);
|
||||
|
||||
// intermediate frame color components (GPU memory)
|
||||
SAFE_MAT_DECL (d_rNew, g_pGPUMemAllocator, width, height);
|
||||
SAFE_MAT_DECL (d_gNew, g_pGPUMemAllocator, width, height);
|
||||
SAFE_MAT_DECL (d_bNew, g_pGPUMemAllocator, width, height);
|
||||
|
||||
// interpolated forward flow
|
||||
SAFE_MAT_DECL (ui, g_pGPUMemAllocator, width, height);
|
||||
SAFE_MAT_DECL (vi, g_pGPUMemAllocator, width, height);
|
||||
|
||||
// interpolated backward flow
|
||||
SAFE_MAT_DECL (ubi, g_pGPUMemAllocator, width, height);
|
||||
SAFE_MAT_DECL (vbi, g_pGPUMemAllocator, width, height);
|
||||
|
||||
// occlusion masks
|
||||
SAFE_MAT_DECL (occ0, g_pGPUMemAllocator, width, height);
|
||||
SAFE_MAT_DECL (occ1, g_pGPUMemAllocator, width, height);
|
||||
|
||||
// prepare color components on host and copy them to device memory
|
||||
ncvAssertReturnNcvStat (CopyData<RgbToR> (firstFrame, h_r));
|
||||
ncvAssertReturnNcvStat (CopyData<RgbToG> (firstFrame, h_g));
|
||||
ncvAssertReturnNcvStat (CopyData<RgbToB> (firstFrame, h_b));
|
||||
|
||||
ncvAssertReturnNcvStat (h_r.copySolid ( d_r, 0 ));
|
||||
ncvAssertReturnNcvStat (h_g.copySolid ( d_g, 0 ));
|
||||
ncvAssertReturnNcvStat (h_b.copySolid ( d_b, 0 ));
|
||||
|
||||
ncvAssertReturnNcvStat (CopyData<RgbToR> (lastFrame, h_r));
|
||||
ncvAssertReturnNcvStat (CopyData<RgbToG> (lastFrame, h_g));
|
||||
ncvAssertReturnNcvStat (CopyData<RgbToB> (lastFrame, h_b));
|
||||
|
||||
ncvAssertReturnNcvStat (h_r.copySolid ( d_rt, 0 ));
|
||||
ncvAssertReturnNcvStat (h_g.copySolid ( d_gt, 0 ));
|
||||
ncvAssertReturnNcvStat (h_b.copySolid ( d_bt, 0 ));
|
||||
|
||||
std::cout << "Interpolating...\n";
|
||||
std::cout.precision (4);
|
||||
|
||||
std::vector<IplImage*> frames;
|
||||
frames.push_back (firstFrame);
|
||||
|
||||
// compute interpolated frames
|
||||
for (Ncv32f timePos = timeStep; timePos < 1.0f; timePos += timeStep)
|
||||
{
|
||||
ncvAssertCUDAReturn (cudaMemset (ui.ptr (), 0, ui.pitch () * ui.height ()), NCV_CUDA_ERROR);
|
||||
ncvAssertCUDAReturn (cudaMemset (vi.ptr (), 0, vi.pitch () * vi.height ()), NCV_CUDA_ERROR);
|
||||
|
||||
ncvAssertCUDAReturn (cudaMemset (ubi.ptr (), 0, ubi.pitch () * ubi.height ()), NCV_CUDA_ERROR);
|
||||
ncvAssertCUDAReturn (cudaMemset (vbi.ptr (), 0, vbi.pitch () * vbi.height ()), NCV_CUDA_ERROR);
|
||||
|
||||
ncvAssertCUDAReturn (cudaMemset (occ0.ptr (), 0, occ0.pitch () * occ0.height ()), NCV_CUDA_ERROR);
|
||||
ncvAssertCUDAReturn (cudaMemset (occ1.ptr (), 0, occ1.pitch () * occ1.height ()), NCV_CUDA_ERROR);
|
||||
|
||||
NppStInterpolationState state;
|
||||
// interpolation state should be filled once except pSrcFrame0, pSrcFrame1, and pNewFrame
|
||||
// we will only need to reset buffers content to 0 since interpolator doesn't do this itself
|
||||
state.size = NcvSize32u (width, height);
|
||||
state.nStep = d_r.pitch ();
|
||||
state.pSrcFrame0 = d_r.ptr ();
|
||||
state.pSrcFrame1 = d_rt.ptr ();
|
||||
state.pFU = u.ptr ();
|
||||
state.pFV = v.ptr ();
|
||||
state.pBU = uBck.ptr ();
|
||||
state.pBV = vBck.ptr ();
|
||||
state.pos = timePos;
|
||||
state.pNewFrame = d_rNew.ptr ();
|
||||
state.ppBuffers[0] = occ0.ptr ();
|
||||
state.ppBuffers[1] = occ1.ptr ();
|
||||
state.ppBuffers[2] = ui.ptr ();
|
||||
state.ppBuffers[3] = vi.ptr ();
|
||||
state.ppBuffers[4] = ubi.ptr ();
|
||||
state.ppBuffers[5] = vbi.ptr ();
|
||||
|
||||
// interpolate red channel
|
||||
nppiStInterpolateFrames (&state);
|
||||
|
||||
// reset buffers
|
||||
ncvAssertCUDAReturn (cudaMemset (ui.ptr (), 0, ui.pitch () * ui.height ()), NCV_CUDA_ERROR);
|
||||
ncvAssertCUDAReturn (cudaMemset (vi.ptr (), 0, vi.pitch () * vi.height ()), NCV_CUDA_ERROR);
|
||||
|
||||
ncvAssertCUDAReturn (cudaMemset (ubi.ptr (), 0, ubi.pitch () * ubi.height ()), NCV_CUDA_ERROR);
|
||||
ncvAssertCUDAReturn (cudaMemset (vbi.ptr (), 0, vbi.pitch () * vbi.height ()), NCV_CUDA_ERROR);
|
||||
|
||||
ncvAssertCUDAReturn (cudaMemset (occ0.ptr (), 0, occ0.pitch () * occ0.height ()), NCV_CUDA_ERROR);
|
||||
ncvAssertCUDAReturn (cudaMemset (occ1.ptr (), 0, occ1.pitch () * occ1.height ()), NCV_CUDA_ERROR);
|
||||
|
||||
// interpolate green channel
|
||||
state.pSrcFrame0 = d_g.ptr ();
|
||||
state.pSrcFrame1 = d_gt.ptr ();
|
||||
state.pNewFrame = d_gNew.ptr ();
|
||||
|
||||
nppiStInterpolateFrames (&state);
|
||||
|
||||
// reset buffers
|
||||
ncvAssertCUDAReturn (cudaMemset (ui.ptr (), 0, ui.pitch () * ui.height ()), NCV_CUDA_ERROR);
|
||||
ncvAssertCUDAReturn (cudaMemset (vi.ptr (), 0, vi.pitch () * vi.height ()), NCV_CUDA_ERROR);
|
||||
|
||||
ncvAssertCUDAReturn (cudaMemset (ubi.ptr (), 0, ubi.pitch () * ubi.height ()), NCV_CUDA_ERROR);
|
||||
ncvAssertCUDAReturn (cudaMemset (vbi.ptr (), 0, vbi.pitch () * vbi.height ()), NCV_CUDA_ERROR);
|
||||
|
||||
ncvAssertCUDAReturn (cudaMemset (occ0.ptr (), 0, occ0.pitch () * occ0.height ()), NCV_CUDA_ERROR);
|
||||
ncvAssertCUDAReturn (cudaMemset (occ1.ptr (), 0, occ1.pitch () * occ1.height ()), NCV_CUDA_ERROR);
|
||||
|
||||
// interpolate blue channel
|
||||
state.pSrcFrame0 = d_b.ptr ();
|
||||
state.pSrcFrame1 = d_bt.ptr ();
|
||||
state.pNewFrame = d_bNew.ptr ();
|
||||
|
||||
nppiStInterpolateFrames (&state);
|
||||
|
||||
// copy to host memory
|
||||
ncvAssertReturnNcvStat (d_rNew.copySolid (h_r, 0));
|
||||
ncvAssertReturnNcvStat (d_gNew.copySolid (h_g, 0));
|
||||
ncvAssertReturnNcvStat (d_bNew.copySolid (h_b, 0));
|
||||
|
||||
// convert to IplImage
|
||||
IplImage *newFrame = CreateImage (h_r, h_g, h_b);
|
||||
if (newFrame == 0)
|
||||
{
|
||||
std::cout << "Could not create new frame in host memory\n";
|
||||
break;
|
||||
}
|
||||
frames.push_back (newFrame);
|
||||
std::cout << timePos * 100.0f << "%\r";
|
||||
}
|
||||
std::cout << std::setw (5) << "100%\n";
|
||||
|
||||
frames.push_back (lastFrame);
|
||||
|
||||
Ncv32u currentFrame;
|
||||
currentFrame = 0;
|
||||
|
||||
ShowFlow (u, v, "Forward flow");
|
||||
ShowFlow (uBck, vBck, "Backward flow");
|
||||
|
||||
cvShowImage ("Interpolated frame", frames[currentFrame]);
|
||||
|
||||
bool qPressed = false;
|
||||
while ( !qPressed )
|
||||
{
|
||||
int key = toupper (cvWaitKey (10));
|
||||
switch (key)
|
||||
{
|
||||
case 27:
|
||||
qPressed = true;
|
||||
break;
|
||||
case 'A':
|
||||
if (currentFrame > 0) --currentFrame;
|
||||
cvShowImage ("Interpolated frame", frames[currentFrame]);
|
||||
break;
|
||||
case 'S':
|
||||
if (currentFrame < frames.size()-1) ++currentFrame;
|
||||
cvShowImage ("Interpolated frame", frames[currentFrame]);
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
cvDestroyAllWindows ();
|
||||
|
||||
std::vector<IplImage*>::iterator iter;
|
||||
for (iter = frames.begin (); iter != frames.end (); ++iter)
|
||||
{
|
||||
cvReleaseImage (&(*iter));
|
||||
}
|
||||
|
||||
return 0;
|
||||
}
|
||||
|
||||
#endif
|
||||
Loading…
Reference in New Issue
Block a user