android流光字体实现,【流光算法代码实现】Demo
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简介
本篇讲解使用opencv提供的流光法算法接口，实现物体跟踪。范例代码为参考修改tvl1_optical_flow.cpp实现。
具体实现
实现代码
#include
#include
#include "opencv2/video/tracking.hpp"
#include "opencv2/highgui/highgui.hpp"
using namespace cv;
using namespace std;
inline bool isFlowCorrect(Point2f u)
{
return !cvIsNaN(u.x) && !cvIsNaN(u.y) && fabs(u.y) < 1e9;
}
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(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.f;
const float col1 = colorWheel[k1][b] / 255.f;
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(255.f * col);
}
return pix;
}
static void drawOpticalFlow(const Mat_& flow, Mat& dst, float maxmotion = -1)
{
dst.create(flow.size(), CV_8UC3);
dst.setTo(Scalar::all(0));
// determine motion range:
float maxrad = maxmotion;
if (maxmotion <= 0)
{
maxrad = 1;
for (int y = 0; y < flow.rows; ++y)
{
for (int x = 0; x < flow.cols; ++x)
{
Point2f u = flow(y, x);
if (!isFlowCorrect(u))
continue;
maxrad = max(maxrad, sqrt(u.x * u.x + u.y * u.y));
}
}
}
for (int y = 0; y < flow.rows; ++y)
{
for (int x = 0; x < flow.cols; ++x)
{
Point2f u = flow(y, x);
if (isFlowCorrect(u))
dst.at(y, x) = computeColor(u.x / maxrad, u.y / maxrad);
}
}
}
int main(int argc, const char* argv[])
{
Mat frame0;
Mat frame1;
Mat_ flow;
Ptr tvl1 = createOptFlow_DualTVL1();
Mat out;
if (argc < 2){
cerr << "Usage : " << argv[0] << "" << endl;
return -1;
}
VideoCapture cap;
cap.open(argv[1]);
while(1){
cap >> frame0;
if(frame0.empty()){
cerr<< "video is over!!" << endl;
break;
}
cvtColor(frame0, frame0, CV_BGR2GRAY);
if(!frame1.empty()){
const double start = (double)getTickCount();
tvl1->calc(frame0, frame1, flow);
const double timeSec = (getTickCount() - start) / getTickFrequency();
cout << "calcOpticalFlowDual_TVL1 : " << timeSec << " sec" << endl;
drawOpticalFlow(flow, out);
imshow("out", out);
imshow("src", frame0);
waitKey(10);
}
frame0.copyTo(frame1);
}
waitKey();
return 0;
}
代码讲解
1、创建了一个DenseOpticalFlow实例，同时获得打开了需要跟踪处理的video视频到cap中。
Ptr tvl1 = createOptFlow_DualTVL1();
Mat out;
if (argc < 2){
cerr << "Usage : " << argv[0] << "" << endl;
return -1;
}
VideoCapture cap;
cap.open(argv[1]);
2、在循环中，不断的读取video的帧数据到frame0中，接着cvtColor将frame0中的数据，灰阶化。判断到存储前一帧数据为空，也就是表示
刚刚读取到第一帧数据时候，不进入处理函数中，直接跳过。最后将frame0中的帧数据，保存到frame1中。frame0进入下一次循环，获得新一帧
数据。
while(1){
cap >> frame0;
if(frame0.empty()){
cerr<< "video is over!!" << endl;
break;
}
cvtColor(frame0, frame0, CV_BGR2GRAY);
if(!frame1.empty()){
...........
...........
}
frame0.copyTo(frame1);
}
3、当检测到frame1保存了前一帧数据之后，进入到流光法计算中。首先获得当前时钟getTickCount。使用tvl1->calc分别传入当前
帧(frame0)和前一帧(frame1)，将获得的位置偏移保存到flow中。接着计算出calc函数处理花费的时间，之后使用函数
drawOpticalFlow，利用flow中的位置偏移，根据偏移位置的方向和速度，从而在out图像，对应位置赋予不同的颜色和饱和度。最后将
当前帧图像和处理之后的out图像分别显示出来。
const double start = (double)getTickCount();
tvl1->calc(frame0, frame1, flow);
const double timeSec = (getTickCount() - start) / getTickFrequency();
cout << "calcOpticalFlowDual_TVL1 : " << timeSec << " sec" << endl;
drawOpticalFlow(flow, out);
imshow("out", out);
imshow("src", frame0);
waitKey(10);