Séparation des fonctions de calculs et de traitement.

This commit is contained in:
Guillaume Courrier 2019-11-26 10:56:37 +01:00
parent 5f35ec91a1
commit ea42e1722a
6 changed files with 204 additions and 15 deletions

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@ -1,5 +1,11 @@
include_directories (${CMAKE_SOURCE_DIR}/src) include_directories (${CMAKE_SOURCE_DIR}/src)
find_package(Qt5 COMPONENTS
Widgets
PrintSupport
REQUIRED
)
file( file(
GLOB GLOB
usage_examples usage_examples
@ -9,7 +15,7 @@ file(
foreach(f ${usage_examples}) foreach(f ${usage_examples})
get_filename_component(exampleName ${f} NAME_WE) get_filename_component(exampleName ${f} NAME_WE)
add_executable(${exampleName} ${f}) add_executable(${exampleName} ${f})
target_link_libraries(${exampleName} ${OpenCV_LIBS}) target_link_libraries(${exampleName} ${OpenCV_LIBS} fftw3 plotcpp qcustomplot Qt5::Widgets Qt5::PrintSupport)
install(PROGRAMS ${CMAKE_CURRENT_BINARY_DIR}/${exampleName} install(PROGRAMS ${CMAKE_CURRENT_BINARY_DIR}/${exampleName}
DESTINATION bin DESTINATION bin
RENAME ${CMAKE_PROJECT_NAME}-${exampleName}) RENAME ${CMAKE_PROJECT_NAME}-${exampleName})

51
examples/test-fft.cpp Normal file
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@ -0,0 +1,51 @@
#include <fftw3.h>
#include <cmath>
#include <libplotcpp/plotcpp.hpp>
double pi() {
return 3.1415;
}
std::vector<double> tfd2vect(fftw_complex* tfd, int N) {
std::vector<double> res;
auto it = tfd;
for (int i = 0; i != N; ++i) {
fftw_complex c = {*it[0], *it[1]};
res.push_back(sqrt(c[0]*c[0] + c[1]*c[1]));
it++;
}
return res;
}
int main(int argc, char** argv) {
QApplication app(argc, argv);
fftw_complex *in, *out;
fftw_plan p;
int N = 500;
in = (fftw_complex*) fftw_malloc(sizeof(fftw_complex) * N);
out = (fftw_complex*) fftw_malloc(sizeof(fftw_complex) * N);
p = fftw_plan_dft_1d(N, in, out, FFTW_FORWARD, FFTW_MEASURE);
std::vector<double> xx;
for (int i = 0; i != N; ++i) {
xx.push_back(i);
}
for (int i = 0; i != N; ++i) {
in[i][0] = sin(2*pi()*50*i/N);
}
fftw_execute(p); /* repeat as needed */
std::vector<double> res = tfd2vect(out, N);
PlotCpp g;
g.plot(xx, res);
g.draw();
fftw_destroy_plan(p);
fftw_free(in); fftw_free(out);
return app.exec();
}

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@ -1,8 +1,11 @@
# file(GLOB headers *.hpp) # file(GLOB headers *.hpp)
# file(GLOB lib_files *.cpp) # file(GLOB lib_files *.cpp)
add_executable(traitement traitement.cpp) # add_executable(traitement traitement.cpp)
target_link_libraries(traitement ${OpenCV_LIBS}) # target_link_libraries(traitement ${OpenCV_LIBS} fftw3)
add_executable(test-fft test-fft.cpp)
target_link_libraries(test-fft)
# target_include_directories(blk PUBLIC ${CMAKE_CURRENT_SOURCE_DIR}) # target_include_directories(blk PUBLIC ${CMAKE_CURRENT_SOURCE_DIR})
# target_compile_options (blk PUBLIC -std=c++11 ) # target_compile_options (blk PUBLIC -std=c++11 )

111
src/math.hpp Normal file
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@ -0,0 +1,111 @@
#pragma once
#include <vector>
#include <complex>
#include <opencv2/opencv.hpp>
#include <iterator>
#include <cmath>
namespace math {
using complex = std::complex<float>;
using signal = std::vector<double>;
using csignal = std::vector<complex>;
using contour = std::vector<cv::Point>;
constexpr double pi() {return std::atan(1)*4;}
//TODO implémenter la fft
csignal fft(const signal& input) {
//TODO: s'assurer que le signal est bien formé (i.e. bonne taille)
return fft_rec(input);
};
csignal fft_rec(const signal& input) {
int size = input.size();
if (size == 1) {
return input;
} else {
signal odd;
signal even;
std::back_insert_iterator<signal> odd_back_it(odd);
std::back_insert_iterator<signal> even_back_it(even);
bool insert_in_even = false;
for (auto it = input.begin(); it != input.end(); ++it) {
if (insert_in_even) {
*even_back_it++ = *it;
insert_in_even = false;
} else {
*odd_back_it++ = *it;
insert_in_even = true;
}
}
signal odd_fft = fft_rec(odd);
signal even_fft = fft_rec(even);
signal res;
res.reserve(size);
for (int k = 0; k<size/2; ++k) {
complex t = std::exp(complex(0, -2*pi()*k/size))*odd[k];
res[k] = even[k] + t;
res[size/2+k] = even[k] - t;
}
return res;
}
}
complex mean(const signal& sig) {
complex res = 0;
for (auto x: sig) {
res += x;
}
return complex(res.real()/sig.size(), res.imag()/sig.size());
};
signal cont2sig(const contour& cont) {
signal sig;
auto sig_it = sig.begin();
auto cont_it = cont.begin();
for (auto cont_it = cont.begin(); cont_it != cont.end(); ++cont_it) {
*sig_it = complex((*cont_it).x, (*cont_it).y);
sig_it++;
}
return sig;
};
contour coef2cont(const signal& tfd, complex mean, int size, int cmax) {
contour cont;
auto tf_it = tfd.begin();
auto cont_it = cont.begin();
for (auto tf_it = tfd.begin(); tf_it != tfd.end(); ++tf_it) {
//TODO retrouver la formule
//*cont_it = mean;
}
return cont;
};
int max_cont(const std::vector<contour>& contours) {
int max = 0;
int id = 0;
for (int i=0; i<contours.size(); ++i) {
if (contours[i].size() > max) {
max = contours[i].size();
id = i;
}
}
return id;
};
contour simplify_contour(const contour& cont, int cmax) {
contour res;
signal z = cont2sig(cont);
complex zm = mean(z);
signal tfd = fft(z);
res = coef2cont(tfd, zm, 0, cmax);
return res;
};
}

13
src/test-fft.cpp Normal file
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@ -0,0 +1,13 @@
#include <math.hpp>
#include <cmath>
int main(int argc, char** argv) {
math::signal s;
for (int i=0; i<100; ++i) {
s.push_back(std::sin(2*math::pi()*50*i/100));
}
math::fft(s);
return 0;
}

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@ -1,4 +1,7 @@
#include "opencv2/opencv.hpp" #include "opencv2/opencv.hpp"
#include <math.h>
#include <algorithm>
#include "math.hpp"
int filter(const cv::Mat& img, cv::Mat output, int seuil) { int filter(const cv::Mat& img, cv::Mat output, int seuil) {
bool detect = false; bool detect = false;
@ -25,12 +28,15 @@ int filter(const cv::Mat& img, cv::Mat output, int seuil) {
} }
int main(int argc, char** argv) { int main(int argc, char** argv) {
int seuil=80; int seuil=0;
if (argc > 1) { if (argc > 1) {
seuil = atol(argv[1]); seuil = atol(argv[1]);
} }
int cmax = 10;
int N = 5000;
char detect; char detect;
cv::VideoCapture cap(0); cv::VideoCapture cap(0);
if(!cap.isOpened()) if(!cap.isOpened())
@ -60,15 +66,14 @@ int main(int argc, char** argv) {
cv::imshow("Detection", binaire); cv::imshow("Detection", binaire);
cv::findContours(binaire, contours, hierarchy, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE); cv::findContours(binaire, contours, hierarchy, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE);
cv::Mat Dessin = cv::Mat::zeros(X,Y, CV_8UC1); cv::Mat Dessin = cv::Mat::zeros(X,Y, CV_8UC1);
unsigned int max = 0;
int id = 0; int id = math::max_cont(contours);
for(numc = 0; numc<contours.size(); numc++) { std::cout << contours[id].size() << std::endl;
if (contours[numc].size() > max) {
max = contours[numc].size(); std::vector<cv::Point> new_cont = math::simplify_contour(contours[id], cmax);
id = numc;
}
}
cv::drawContours(Dessin, contours, id, 255); cv::drawContours(Dessin, contours, id, 255);
cv::drawContours(Dessin, new_cont, id, 255);
cv::imshow("Contours", Dessin); cv::imshow("Contours", Dessin);
if(cv::waitKey(30) == 27) { if(cv::waitKey(30) == 27) {
break; break;