Open Source Computer Vision Library https://opencv.org/
You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
 
 
 
 
 
 

351 lines
9.8 KiB

#include <iostream>
#include <iomanip>
#include <string>
#include "cvconfig.h"
#include "opencv2/core/core.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/gpu/gpu.hpp"
#ifdef HAVE_CUDA
#include "NPP_staging/NPP_staging.hpp"
#endif
using namespace std;
using namespace cv;
using namespace cv::gpu;
#if !defined(HAVE_CUDA)
int main(int argc, const char* argv[])
{
cout << "Please compile the library with CUDA support" << endl;
return -1;
}
#else
#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"
bool help_showed = false;
void printHelp()
{
cout << "Usage help:\n";
cout << setiosflags(ios::left);
cout << "\t" << setw(15) << PARAM_ALPHA << " - set alpha\n";
cout << "\t" << setw(15) << PARAM_GAMMA << " - set gamma\n";
cout << "\t" << setw(15) << PARAM_INNER << " - set number of inner iterations\n";
cout << "\t" << setw(15) << PARAM_LEFT << " - specify left image\n";
cout << "\t" << setw(15) << PARAM_RIGHT << " - specify right image\n";
cout << "\t" << setw(15) << PARAM_OUTER << " - set number of outer iterations\n";
cout << "\t" << setw(15) << PARAM_SCALE << " - set pyramid scale factor\n";
cout << "\t" << setw(15) << PARAM_SOLVER << " - set number of basic solver iterations\n";
cout << "\t" << setw(15) << PARAM_TIME_STEP << " - set frame interpolation time step\n";
cout << "\t" << setw(15) << PARAM_HELP << " - display this help message\n";
help_showed = true;
}
int processCommandLine(int argc, const char* argv[], float& timeStep, string& frame0Name, string& frame1Name, BroxOpticalFlow& flow)
{
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)
flow.scale_factor = static_cast<float>(atof(argv[++iarg]));
else
return -1;
}
else if(strcmp(argv[iarg], PARAM_ALPHA) == 0)
{
if (iarg + 1 < argc)
flow.alpha = static_cast<float>(atof(argv[++iarg]));
else
return -1;
}
else if(strcmp(argv[iarg], PARAM_GAMMA) == 0)
{
if (iarg + 1 < argc)
flow.gamma = static_cast<float>(atof(argv[++iarg]));
else
return -1;
}
else if(strcmp(argv[iarg], PARAM_INNER) == 0)
{
if (iarg + 1 < argc)
flow.inner_iterations = atoi(argv[++iarg]);
else
return -1;
}
else if(strcmp(argv[iarg], PARAM_OUTER) == 0)
{
if (iarg + 1 < argc)
flow.outer_iterations = atoi(argv[++iarg]);
else
return -1;
}
else if(strcmp(argv[iarg], PARAM_SOLVER) == 0)
{
if (iarg + 1 < argc)
flow.solver_iterations = atoi(argv[++iarg]);
else
return -1;
}
else if(strcmp(argv[iarg], PARAM_TIME_STEP) == 0)
{
if (iarg + 1 < argc)
timeStep = static_cast<float>(atof(argv[++iarg]));
else
return -1;
}
else if(strcmp(argv[iarg], PARAM_HELP) == 0)
{
printHelp();
return 0;
}
}
return 0;
}
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);
}
void getFlowField(const Mat& u, const Mat& v, Mat& flowField)
{
float maxDisplacement = 1.0f;
for (int i = 0; i < u.rows; ++i)
{
const float* ptr_u = u.ptr<float>(i);
const float* ptr_v = v.ptr<float>(i);
for (int j = 0; j < u.cols; ++j)
{
float d = max(fabsf(ptr_u[j]), fabsf(ptr_v[j]));
if (d > maxDisplacement)
maxDisplacement = d;
}
}
flowField.create(u.size(), CV_8UC4);
for (int i = 0; i < flowField.rows; ++i)
{
const float* ptr_u = u.ptr<float>(i);
const float* ptr_v = v.ptr<float>(i);
Vec4b* row = flowField.ptr<Vec4b>(i);
for (int j = 0; j < flowField.cols; ++j)
{
row[j][0] = 0;
row[j][1] = static_cast<unsigned char> (mapValue (-ptr_v[j], -maxDisplacement, maxDisplacement, 0.0f, 255.0f));
row[j][2] = static_cast<unsigned char> (mapValue ( ptr_u[j], -maxDisplacement, maxDisplacement, 0.0f, 255.0f));
row[j][3] = 255;
}
}
}
int main(int argc, const char* argv[])
{
string frame0Name, frame1Name;
float timeStep = 0.01f;
BroxOpticalFlow d_flow(0.197f /*alpha*/, 50.0f /*gamma*/, 0.8f /*scale_factor*/,
10 /*inner_iterations*/, 77 /*outer_iterations*/, 10 /*solver_iterations*/);
int result = processCommandLine(argc, argv, timeStep, frame0Name, frame1Name, d_flow);
if (help_showed)
return -1;
if (argc == 1 || result)
{
printHelp();
return result;
}
if (frame0Name.empty() || frame1Name.empty())
{
cout << "Missing input file names\n";
return -1;
}
Mat frame0Color = imread(frame0Name);
Mat frame1Color = imread(frame1Name);
if (frame0Color.empty() || frame1Color.empty())
{
cout << "Can't load input images\n";
return -1;
}
cout << "OpenCV / NVIDIA Computer Vision\n";
cout << "Optical Flow Demo: Frame Interpolation\n";
cout << "=========================================\n";
cout << "Press:\n ESC to quit\n 'a' to move to the previous frame\n 's' to move to the next frame\n";
frame0Color.convertTo(frame0Color, CV_32F, 1.0 / 255.0);
frame1Color.convertTo(frame1Color, CV_32F, 1.0 / 255.0);
Mat frame0Gray, frame1Gray;
cvtColor(frame0Color, frame0Gray, COLOR_BGR2GRAY);
cvtColor(frame1Color, frame1Gray, COLOR_BGR2GRAY);
GpuMat d_frame0(frame0Gray);
GpuMat d_frame1(frame1Gray);
Mat fu, fv;
Mat bu, bv;
GpuMat d_fu, d_fv;
GpuMat d_bu, d_bv;
cout << "Estimating optical flow\nForward...\n";
d_flow(d_frame0, d_frame1, d_fu, d_fv);
d_flow(d_frame1, d_frame0, d_bu, d_bv);
d_fu.download(fu);
d_fv.download(fv);
d_bu.download(bu);
d_bv.download(bv);
// first frame color components (GPU memory)
GpuMat d_b, d_g, d_r;
// second frame color components (GPU memory)
GpuMat d_bt, d_gt, d_rt;
// prepare color components on host and copy them to device memory
Mat channels[3];
cv::split(frame0Color, channels);
d_b.upload(channels[0]);
d_g.upload(channels[1]);
d_r.upload(channels[2]);
cv::split(frame1Color, channels);
d_bt.upload(channels[0]);
d_gt.upload(channels[1]);
d_rt.upload(channels[2]);
cout << "Interpolating...\n";
cout.precision (4);
// temporary buffer
GpuMat d_buf;
// intermediate frame color components (GPU memory)
GpuMat d_rNew, d_gNew, d_bNew;
GpuMat d_newFrame;
vector<Mat> frames;
frames.reserve(1.0f / timeStep + 2);
frames.push_back(frame0Color);
// compute interpolated frames
for (float timePos = timeStep; timePos < 1.0f; timePos += timeStep)
{
// interpolate blue channel
interpolateFrames(d_b, d_bt, d_fu, d_fv, d_bu, d_bv, timePos, d_bNew, d_buf);
// interpolate green channel
interpolateFrames(d_g, d_gt, d_fu, d_fv, d_bu, d_bv, timePos, d_gNew, d_buf);
// interpolate red channel
interpolateFrames(d_r, d_rt, d_fu, d_fv, d_bu, d_bv, timePos, d_rNew, d_buf);
GpuMat channels[] = {d_bNew, d_gNew, d_rNew};
merge(channels, 3, d_newFrame);
Mat newFrame;
d_newFrame.download(newFrame);
frames.push_back(newFrame);
cout << timePos * 100.0f << "%\r";
}
cout << setw (5) << "100%\n";
frames.push_back(frame1Color);
int currentFrame;
currentFrame = 0;
Mat flowFieldForward;
Mat flowFieldBackward;
getFlowField(fu, fv, flowFieldForward);
getFlowField(bu, bv, flowFieldBackward);
imshow("Forward flow", flowFieldForward);
imshow("Backward flow", flowFieldBackward);
imshow("Interpolated frame", frames[currentFrame]);
bool qPressed = false;
while (!qPressed)
{
int key = toupper(waitKey(10));
switch (key)
{
case 27:
qPressed = true;
break;
case 'A':
if (currentFrame > 0)
--currentFrame;
imshow("Interpolated frame", frames[currentFrame]);
break;
case 'S':
if (currentFrame < frames.size() - 1)
++currentFrame;
imshow("Interpolated frame", frames[currentFrame]);
break;
}
}
return 0;
}
#endif