217 lines
6.7 KiB
C++
217 lines
6.7 KiB
C++
#include "ros/ros.h"
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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 <sensor_msgs/image_encodings.h>
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#include <papillon/BoundingBox.h>
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#include <opencv/cv.h>
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#include <sstream>
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using namespace std;
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class Traite_image {
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public:
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const static int SENSITIVITY_VALUE = 20;
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const static int BLUR_SIZE = 9;
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const static int CLOSE_SIZE = 30;
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const static int ERODE_SIZE = 2;
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const static int NB_FRAME_DROP = 1;
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vector<cv::Mat> prevs;
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cv::Mat last_T;
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bool first = true;
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int resize_f = 1;
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ros::NodeHandle n;
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image_transport::ImageTransport it;
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image_transport::Subscriber sub;
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image_transport::Publisher pub_img;
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image_transport::Publisher pub_thres;
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ros::Publisher pub_cmd;
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Traite_image() : n("~"),it(n) {
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pub_img = it.advertise("/papillon/image_out", 1);
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pub_thres = it.advertise("/papillon/thres_out", 1);
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pub_cmd = n.advertise<papillon::BoundingBox>("/papillon/bbox", 1);
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sub = it.subscribe("/bebop/image_raw", 1, [this](const sensor_msgs::ImageConstPtr& img) -> void { this->on_image(img);},ros::VoidPtr(),image_transport::TransportHints("compressed"));
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}
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// Callback function executedwhen recieving an image from the camera
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// Publishes to /papillon/image_out
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void on_image(const sensor_msgs::ImageConstPtr& msg) {
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cv_bridge::CvImageConstPtr bridge_input;
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try {
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bridge_input = cv_bridge::toCvShare(msg,sensor_msgs::image_encodings::RGB8);
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}
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catch (cv::Exception& e) {
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std::ostringstream errstr;
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errstr << "cv_bridge exception caught: " << e.what();
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return;
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}
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const cv::Mat& input = bridge_input->image;
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cv::Mat next;
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resize(input, next, cv::Size(input.size().width/resize_f, input.size().height/resize_f));
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cv::Mat output;
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next.copyTo(output);
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cv::cvtColor(next, next, cv::COLOR_BGR2GRAY);
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if (first) {
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for (int i = 0; i < NB_FRAME_DROP; ++i) {
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prevs.push_back(next.clone());
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}
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first = false;
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ROS_INFO("Ready");
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}
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cv::Mat next_stab;
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stabiliseImg(prevs.back(), next, next_stab);
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int crop_ratio = 6;
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float crop_x = next_stab.size().width/crop_ratio;
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float crop_y = next_stab.size().height/crop_ratio;
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float crop_w = next_stab.size().width*(1-2.0/crop_ratio);
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float crop_h = next_stab.size().height*(1-2.0/crop_ratio);
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cv::Rect myROI(crop_x, crop_y, crop_w, crop_h);
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cv::Mat next_stab_cropped = next_stab(myROI);
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cv::Mat prev_cropped = prevs.back()(myROI);
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cv::Mat closed_thres;
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searchForMovement(prev_cropped, next_stab_cropped, output, closed_thres);
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pub_img.publish(cv_bridge::CvImage(msg->header, "rgb8", output).toImageMsg());
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pub_thres.publish(cv_bridge::CvImage(msg->header, "mono8", closed_thres).toImageMsg());
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prevs.pop_back();
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prevs.insert(prevs.begin(), next.clone());
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}
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void stabiliseImg(cv::Mat prev_grey, cv::Mat cur_grey, cv::Mat &output){
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// vector from prev to cur
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vector <cv::Point2f> prev_corner, cur_corner;
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vector <cv::Point2f> prev_corner2, cur_corner2;
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vector <uchar> status;
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vector <float> err;
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cv::goodFeaturesToTrack(prev_grey, prev_corner, 200, 0.01, 30);
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cv::calcOpticalFlowPyrLK(prev_grey, cur_grey, prev_corner, cur_corner, status, err);
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// weed out bad matches
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for(size_t i=0; i < status.size(); i++) {
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if(status[i]) {
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prev_corner2.push_back(prev_corner[i]);
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cur_corner2.push_back(cur_corner[i]);
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}
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}
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cv::Mat T = estimateRigidTransform(prev_corner2, cur_corner2, true); // false = rigid transform, no scaling/shearing
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if(T.data == NULL) {
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last_T.copyTo(T);
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}
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T.copyTo(last_T);
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cv::warpAffine(cur_grey, output, T, cur_grey.size(),cv::INTER_CUBIC|cv::WARP_INVERSE_MAP);
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}
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void searchForMovement(cv::Mat prev_grey, cv::Mat cur_grey, cv::Mat &output, cv::Mat &out2){
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cv::GaussianBlur(prev_grey, prev_grey, cv::Size(BLUR_SIZE,BLUR_SIZE), 3.0);
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cv::GaussianBlur(cur_grey, cur_grey, cv::Size(BLUR_SIZE,BLUR_SIZE), 3.0);
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// Subtract the 2 last frames and threshold them
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cv::Mat thres;
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cv::absdiff(prev_grey,cur_grey,thres);
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cv::Mat element = getStructuringElement( cv::MORPH_ELLIPSE,
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cv::Size( 2*ERODE_SIZE + 1, 2*ERODE_SIZE+1 ),
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cv::Point( ERODE_SIZE, ERODE_SIZE ) );
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// Apply the erode operation
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cv::erode(thres, thres, element );
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cv::threshold(thres, thres, SENSITIVITY_VALUE, 255, cv::THRESH_BINARY);
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// Intermediate output
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thres.copyTo(out2);
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cv::Mat closed_thres;
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cv::Mat structuringElement = getStructuringElement(cv::MORPH_ELLIPSE, cv::Size(CLOSE_SIZE, CLOSE_SIZE));
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cv::morphologyEx( thres, closed_thres, cv::MORPH_CLOSE, structuringElement );
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bool objectDetected = false;
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cv::Mat temp;
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closed_thres.copyTo(temp);
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vector< vector<cv::Point> > contours;
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//find contours of filtered image using openCV findContours function
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cv::findContours(temp,contours,CV_RETR_EXTERNAL,CV_CHAIN_APPROX_SIMPLE );// retrieves external contours
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//if contours vector is not empty, we have found some objects
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if(contours.size()>0){
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vector<cv::Rect> nc_rects; // Non connected rectangles
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for(size_t i=0; i<contours.size();i++)
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{
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nc_rects.push_back(cv::boundingRect(contours[i]));
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}
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vector<cv::Rect> c_rects; // Connected rectangles
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cleanBBoxes(nc_rects, cur_grey.size(), c_rects);
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if (c_rects.size() > 0) {
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for (const auto& rect : c_rects)
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cv::rectangle(output, rect, cv::Scalar(0, 255, 0), 2);
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cv::Rect objBRect = c_rects.front();
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papillon::BoundingBox bbox = papillon::BoundingBox();
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bbox.x = objBRect.x / (float)cur_grey.size().width;
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bbox.y = objBRect.y / (float)cur_grey.size().height;
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bbox.width = objBRect.width / (float)cur_grey.size().width;
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bbox.height = objBRect.height / (float)cur_grey.size().height;
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pub_cmd.publish(bbox);
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}
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}
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}
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void cleanBBoxes(vector<cv::Rect> nc_rects, cv::Size img, vector<cv::Rect> &c_rects) {
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int max = 0;
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for (auto r : nc_rects) {
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cv::Point center = rectCenter(r);
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if (r.width > img.width / 2 || r.height > img.height / 8)
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continue;
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if (center.y > img.height * 2 / 3 || center.y < img.height / 3)
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continue;
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int r_area = r.area();
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if (max < r_area) {
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max = r_area;
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c_rects.insert(c_rects.begin(), r);
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} else {
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c_rects.push_back(r);
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}
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}
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}
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cv::Point rectCenter(cv::Rect r) {
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return cv::Point(r.x + r.width/2, r.y + r.height / 2);
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}
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inline bool isFlowCorrect(cv::Point2f u)
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{
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return !cvIsNaN(u.x) && !cvIsNaN(u.y) && fabs(u.x) < 1e9 && fabs(u.y) < 1e9;
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}
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};
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int main(int argc, char **argv)
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{
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ros::init(argc, argv, "test_opencv");
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Traite_image dataset=Traite_image();
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ros::spin();
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return 0;
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}
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