implémentation des descripteur dans le package ROS + ajout de dynamic_reconfigure pour changer les paramètres
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c132000776
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14ad23ddc3
5 changed files with 82 additions and 17 deletions
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@ -9,6 +9,11 @@ find_package(catkin REQUIRED COMPONENTS
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std_msgs
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cv_bridge
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image_transport
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dynamic_reconfigure
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)
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generate_dynamic_reconfigure_options(
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cfg/Descriptor.cfg
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)
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catkin_package()
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@ -22,3 +27,4 @@ target_link_libraries(controller ${catkin_LIBRARIES})
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add_executable(descripteur src/descripteur.cpp)
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target_link_libraries(descripteur ${catkin_LIBRARIES})
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#add_dependencies(descripteur ${PROJECT_NAME}_gencfg)
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11
ROS/gesture_based_control/cfg/Descriptor.cfg
Executable file
11
ROS/gesture_based_control/cfg/Descriptor.cfg
Executable file
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@ -0,0 +1,11 @@
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#!/usr/bin/env python
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PACKAGE = "gesture_based_control"
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from dynamic_reconfigure.parameter_generator_catkin import *
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gen = ParameterGenerator()
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gen.add("cmax", int_t, 0, "cmax", 50, 0, 100)
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gen.add("threshold", int_t, 0, "threshold", 50, 0, 255)
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exit(gen.generate(PACKAGE, "gesture_based_control", "Descriptors"))
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@ -10,4 +10,5 @@
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<node name="descripteur" pkg="gesture_based_control" type="descripteur" output="screen">
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<remap from="/image_raw" to="/usb_cam/image_raw"/>
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</node>
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<node name="rqt_reconfigure" pkg="rqt_reconfigure" type="rqt_reconfigure"/>
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</launch>
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@ -2,10 +2,20 @@
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#include <opencv2/opencv.hpp>
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#include <image_transport/image_transport.h>
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#include <cv_bridge/cv_bridge.h>
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//#include <math.hpp>
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#include <std_msgs/String.h>
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#include <dynamic_reconfigure/server.h>
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void callback(const sensor_msgs::ImageConstPtr& msg) {
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#include <gesture_based_control/DescriptorsConfig.h>
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#include "math.hpp"
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void callback(gesture_based_control::DescriptorsConfig &config, uint32_t level, int& cmax, int& threshold) {
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cmax = config.cmax;
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threshold = config.threshold;
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}
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void callback(const sensor_msgs::ImageConstPtr& msg, int& threshold, int& cmax, ros::Publisher& order_pub, image_transport::Publisher& image_pub) {
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cv_bridge::CvImagePtr cv_ptr;
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std_msgs::String s;
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try {
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cv_ptr = cv_bridge::toCvCopy(msg, sensor_msgs::image_encodings::RGB8);
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@ -14,17 +24,62 @@ void callback(const sensor_msgs::ImageConstPtr& msg) {
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return;
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}
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const cv::Mat& input = cv_ptr->image;
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cv::Mat& input = cv_ptr->image;
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cv::Mat binaire(input.rows, input.cols, CV_8UC1);
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math::filter(input, binaire, threshold);
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cv::GaussianBlur(input, input, cv::Size(7,7), 1.5, 1.5);
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std::vector<math::contour> contours;
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std::vector<cv::Vec4i> hierarchy;
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cv::findContours(binaire, contours, hierarchy, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE);
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if (contours.size() != 0) {
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int index = math::max_cont(contours);
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math::csignal desc = math::descriptors(contours[index], cmax);
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//TODO: implémenter algo ml
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//TODO: publier résultat
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int r = 0;
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switch (r) {
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case 0:
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s.data = "left";
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break;
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case 1:
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s.data = "right";
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break;
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case 2:
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s.data = "stop";
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break;
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case 3:
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s.data = "forward";
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break;
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default:
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s.data = "None";
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break;
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}
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order_pub.publish(s);
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cv::drawContours(input, contours, index, 255);
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}
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image_pub.publish(cv_bridge::CvImage(msg->header, "rgb8", input).toImageMsg());
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}
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int main(int argc, char** argv) {
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ros::init(argc, argv, "descripteur");
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int threshold = 25;
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int cmax = 10;
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ros::NodeHandle n;
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image_transport::ImageTransport it(n);
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image_transport::Subscriber sub = it.subscribe("/image_raw", 1, callback);
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ros::Publisher order_pub = n.advertise<std_msgs::String>("/order", 100);
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image_transport::Publisher image_pub = it.advertise("/image_out", 1);
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image_transport::Subscriber sub = it.subscribe("/image_raw", 1, boost::bind(callback, _1, boost::ref(threshold), boost::ref(cmax), boost::ref(order_pub), boost::ref(image_pub)));
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dynamic_reconfigure::Server<gesture_based_control::DescriptorsConfig> server;
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dynamic_reconfigure::Server<gesture_based_control::DescriptorsConfig>::CallbackType f;
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f = boost::bind(&callback, _1, _2, boost::ref(cmax), boost::ref(threshold));
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server.setCallback(f);
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ros::spin();
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}
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@ -14,7 +14,7 @@ namespace math {
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using contour = std::vector<cv::Point>;
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constexpr double pi() {return std::atan(1)*4;}
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void displayi_abs(const csignal& s) {
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void display_abs(const csignal& s) {
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int count=0;
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for (auto d: s) {
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std::cout << count++ << ' ' << std::abs(d) << std::endl;
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@ -65,16 +65,13 @@ namespace math {
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if ((R>G) && (R>B)) {
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if (((R-B)>=seuil) || ((R-G)>=seuil)) {
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detect = true;
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}
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}
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if (detect==1) {
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output.data[indexNB]=255;
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} else {
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output.data[indexNB]=0;
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}
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}
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}
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}
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csignal cont2sig(const contour& cont) {
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csignal sig;
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@ -109,15 +106,13 @@ namespace math {
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for (int n=0; n<size; ++n) {
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t += (input[n] * std::exp(complex(0, -2*pi()*n*k/size)));
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}
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std::cout << t << std::endl;
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res->push_back(t);
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}
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return *res;
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}
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csignal fft_rec(const csignal& input) {
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csignal fft_rec(const csignal& input) { //TODO: implémenter la fft !!!
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int size = input.size();
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std::cout << "Size: " << size << std::endl;
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if (size <= 1) {
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return input;
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@ -175,7 +170,6 @@ namespace math {
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opt_size = 1 << (int)std::ceil(std::log(N)/std::log(2));
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}
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opt_size = input.size();
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std::cout << opt_size << std::endl;
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csignal sig(input);
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for (int i=0; i<opt_size-input.size(); ++i) {
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sig.push_back(complex(0, 0));
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@ -212,7 +206,6 @@ namespace math {
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int kmin = tfd.size()/2 + cmin;
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int kmax = tfd.size()/2 + cmax;
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//display(tfd);
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auto tfd_it = tfd.end() + cmin;
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for (int k=0; k<-cmin; ++k) {
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res.push_back(*(tfd_it++));
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@ -221,7 +214,6 @@ namespace math {
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for (int k=0; k<cmax+1; ++k) {
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res.push_back(*(tfd_it++));
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}
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//display(res);
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return res;
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}
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