OpenCV_4.2.0/opencv_contrib-4.2.0/modules/cudaoptflow/samples/nvidia_optical_flow.cpp

225 lines
7.1 KiB
C++

#include <unordered_map>
#include <iostream>
#include <fstream>
#include <iomanip>
#include "opencv2/core.hpp"
#include "opencv2/core/utility.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/cudaoptflow.hpp"
#include "opencv2/cudaarithm.hpp"
#include "opencv2/video/tracking.hpp"
using namespace std;
using namespace cv;
using namespace cv::cuda;
//this function is taken from opencv/samples/gpu/optical_flow.cpp
inline bool isFlowCorrect(Point2f u)
{
return !cvIsNaN(u.x) && !cvIsNaN(u.y) && fabs(u.x) < 1e9 && fabs(u.y) < 1e9;
}
//this function is taken from opencv/samples/gpu/optical_flow.cpp
static Vec3b computeColor(float fx, float fy)
{
static bool first = true;
// relative lengths of color transitions:
// these are chosen based on perceptual similarity
// (e.g. one can distinguish more shades between red and yellow
// than between yellow and green)
const int RY = 15;
const int YG = 6;
const int GC = 4;
const int CB = 11;
const int BM = 13;
const int MR = 6;
const int NCOLS = RY + YG + GC + CB + BM + MR;
static Vec3i colorWheel[NCOLS];
if (first)
{
int k = 0;
for (int i = 0; i < RY; ++i, ++k)
colorWheel[k] = Vec3i(255, 255 * i / RY, 0);
for (int i = 0; i < YG; ++i, ++k)
colorWheel[k] = Vec3i(255 - 255 * i / YG, 255, 0);
for (int i = 0; i < GC; ++i, ++k)
colorWheel[k] = Vec3i(0, 255, 255 * i / GC);
for (int i = 0; i < CB; ++i, ++k)
colorWheel[k] = Vec3i(0, 255 - 255 * i / CB, 255);
for (int i = 0; i < BM; ++i, ++k)
colorWheel[k] = Vec3i(255 * i / BM, 0, 255);
for (int i = 0; i < MR; ++i, ++k)
colorWheel[k] = Vec3i(255, 0, 255 - 255 * i / MR);
first = false;
}
const float rad = sqrt(fx * fx + fy * fy);
const float a = atan2(-fy, -fx) / (float)CV_PI;
const float fk = (a + 1.0f) / 2.0f * (NCOLS - 1);
const int k0 = static_cast<int>(fk);
const int k1 = (k0 + 1) % NCOLS;
const float f = fk - k0;
Vec3b pix;
for (int b = 0; b < 3; b++)
{
const float col0 = colorWheel[k0][b] / 255.0f;
const float col1 = colorWheel[k1][b] / 255.0f;
float col = (1 - f) * col0 + f * col1;
if (rad <= 1)
col = 1 - rad * (1 - col); // increase saturation with radius
else
col *= .75; // out of range
pix[2 - b] = static_cast<uchar>(255.0 * col);
}
return pix;
}
//this function is taken from opencv/samples/gpu/optical_flow.cpp
static void drawOpticalFlow(const Mat_<float>& flowx, const Mat_<float>& flowy
, Mat& dst, float maxmotion = -1)
{
dst.create(flowx.size(), CV_8UC3);
dst.setTo(Scalar::all(0));
// determine motion range:
float maxrad = maxmotion;
if (maxmotion <= 0)
{
maxrad = 1;
for (int y = 0; y < flowx.rows; ++y)
{
for (int x = 0; x < flowx.cols; ++x)
{
Point2f u(flowx(y, x), flowy(y, x));
if (!isFlowCorrect(u))
continue;
maxrad = max(maxrad, sqrt(u.x * u.x + u.y * u.y));
}
}
}
for (int y = 0; y < flowx.rows; ++y)
{
for (int x = 0; x < flowx.cols; ++x)
{
Point2f u(flowx(y, x), flowy(y, x));
if (isFlowCorrect(u))
dst.at<Vec3b>(y, x) = computeColor(u.x / maxrad, u.y / maxrad);
}
}
}
int main(int argc, char **argv)
{
std::unordered_map<std::string, NvidiaOpticalFlow_1_0::NVIDIA_OF_PERF_LEVEL> presetMap = {
{ "slow", NvidiaOpticalFlow_1_0::NVIDIA_OF_PERF_LEVEL::NV_OF_PERF_LEVEL_SLOW },
{ "medium", NvidiaOpticalFlow_1_0::NVIDIA_OF_PERF_LEVEL::NV_OF_PERF_LEVEL_MEDIUM },
{ "fast", NvidiaOpticalFlow_1_0::NVIDIA_OF_PERF_LEVEL::NV_OF_PERF_LEVEL_FAST } };
try
{
CommandLineParser cmd(argc, argv,
"{ l left | ../data/basketball1.png | specify left image }"
"{ r right | ../data/basketball2.png | specify right image }"
"{ g gpuid | 0 | cuda device index}"
"{ p preset | slow | perf preset for OF algo [ options : slow, medium, fast ]}"
"{ o output | OpenCVNvOF.flo | output flow vector file in middlebury format}"
"{ th enableTemporalHints | false | Enable temporal hints}"
"{ eh enableExternalHints | false | Enable external hints}"
"{ cb enableCostBuffer | false | Enable output cost buffer}"
"{ h help | | print help message }");
cmd.about("Nvidia's optical flow sample.");
if (cmd.has("help") || !cmd.check())
{
cmd.printMessage();
cmd.printErrors();
return 0;
}
string pathL = cmd.get<string>("left");
string pathR = cmd.get<string>("right");
string preset = cmd.get<string>("preset");
string output = cmd.get<string>("output");
bool enableExternalHints = cmd.get<bool>("enableExternalHints");
bool enableTemporalHints = cmd.get<bool>("enableTemporalHints");
bool enableCostBuffer = cmd.get<bool>("enableCostBuffer");
int gpuId = cmd.get<int>("gpuid");
if (pathL.empty()) cout << "Specify left image path\n";
if (pathR.empty()) cout << "Specify right image path\n";
if (preset.empty()) cout << "Specify perf preset for OpticalFlow algo\n";
if (pathL.empty() || pathR.empty()) return 0;
auto search = presetMap.find(preset);
if (search == presetMap.end())
{
std::cout << "Invalid preset level : " << preset << std::endl;
return 0;
}
NvidiaOpticalFlow_1_0::NVIDIA_OF_PERF_LEVEL perfPreset = search->second;
Mat frameL = imread(pathL, IMREAD_GRAYSCALE);
Mat frameR = imread(pathR, IMREAD_GRAYSCALE);
if (frameL.empty()) cout << "Can't open '" << pathL << "'\n";
if (frameR.empty()) cout << "Can't open '" << pathR << "'\n";
if (frameL.empty() || frameR.empty()) return -1;
Ptr<NvidiaOpticalFlow_1_0> nvof = NvidiaOpticalFlow_1_0::create(
frameL.size().width, frameL.size().height, perfPreset,
enableTemporalHints, enableExternalHints, enableCostBuffer, gpuId);
Mat flowx, flowy, flowxy, upsampledFlowXY, image;
nvof->calc(frameL, frameR, flowxy);
nvof->upSampler(flowxy, frameL.size().width, frameL.size().height,
nvof->getGridSize(), upsampledFlowXY);
if (output.size() != 0)
{
if (!writeOpticalFlow(output, upsampledFlowXY))
cout << "Failed to save Flow Vector" << endl;
else
cout << "Flow vector saved as '" << output << "'\n";
}
Mat planes[] = { flowx, flowy };
split(upsampledFlowXY, planes);
flowx = planes[0]; flowy = planes[1];
drawOpticalFlow(flowx, flowy, image, 10);
imshow("Colorize image",image);
waitKey(0);
nvof->collectGarbage();
}
catch (const std::exception &ex)
{
std::cout << ex.what() << std::endl;
return 1;
}
return 0;
}