Update Readme.md

Alexey

2018-02-18 1106f5325b8bd3dc4b5fe776d8abecbe3879b9d2

 src/yolo_console_dll.cpp

@@ -14,7 +14,7 @@
#endif

// To use tracking - uncomment the following line. Tracking is supported only by OpenCV 3.x
//#define TRACK_OPTFLOW
#define TRACK_OPTFLOW

#include "yolo_v2_class.hpp"  // imported functions from DLL

@@ -37,123 +37,154 @@
#pragma comment(lib, "opencv_highgui" OPENCV_VERSION ".lib")
#endif


cv::Scalar obj_id_to_color(int obj_id) {
   int const colors[6][3] = { { 1,0,1 },{ 0,0,1 },{ 0,1,1 },{ 0,1,0 },{ 1,1,0 },{ 1,0,0 } };
   int const offset = obj_id * 123457 % 6;
   int const color_scale = 150 + (obj_id * 123457) % 100;
   cv::Scalar color(colors[offset][0], colors[offset][1], colors[offset][2]);
   color *= color_scale;
   return color;
}

class preview_boxes_t {
   enum { frames_history = 30 }; // how long to keep the history saved

   struct preview_box_track_t {
      unsigned int track_id, obj_id, last_showed_frames_ago;
      cv::Mat mat_obj;
      preview_box_track_t() : track_id(0), obj_id(0), last_showed_frames_ago(frames_history) {}
   };
   std::vector<preview_box_track_t> preview_box_track_id;
   size_t const preview_box_size, const bottom_offset;
   bool const one_off_detections;
class track_kalman {
public:
   preview_boxes_t(size_t _preview_box_size = 100, size_t _bottom_offset = 100, bool _one_off_detections = false) :
      preview_box_size(_preview_box_size), bottom_offset(_bottom_offset), one_off_detections(_one_off_detections)
   {}
   cv::KalmanFilter kf;
   int state_size, meas_size, contr_size;

   void draw_preview_boxes(cv::Mat src_mat, cv::Mat draw_mat, std::vector<bbox_t> result_vec, bool draw_boxes = true)

   track_kalman(int _state_size = 10, int _meas_size = 10, int _contr_size = 0)
      : state_size(_state_size), meas_size(_meas_size), contr_size(_contr_size)
   {
      size_t const count_preview_boxes = draw_mat.cols / preview_box_size;
      if (preview_box_track_id.size() != count_preview_boxes) preview_box_track_id.resize(count_preview_boxes);
      kf.init(state_size, meas_size, contr_size, CV_32F);

      // increment frames history
      for (auto &i : preview_box_track_id)
         i.last_showed_frames_ago = std::min((unsigned)frames_history, i.last_showed_frames_ago + 1);
      cv::setIdentity(kf.measurementMatrix);
      cv::setIdentity(kf.measurementNoiseCov, cv::Scalar::all(1e-1));
      cv::setIdentity(kf.processNoiseCov, cv::Scalar::all(1e-5));
      cv::setIdentity(kf.errorCovPost, cv::Scalar::all(1e-2));
      cv::setIdentity(kf.transitionMatrix);
   }

      // occupy empty boxes
      for (auto &k : result_vec) {
         bool found = false;
         for (auto &i : preview_box_track_id) {
            if (i.track_id == k.track_id) {
               if(!one_off_detections)
                  i.last_showed_frames_ago = 0;
               found = true;
               break;
            }
         }
         if (!found) {
            for (auto &i : preview_box_track_id) {
               if (i.last_showed_frames_ago == frames_history) {
                  if (!one_off_detections && k.frames_counter == 0) break;
                  i.track_id = k.track_id;
                  i.obj_id = k.obj_id;
                  i.last_showed_frames_ago = 0;
                  break;
               }
            }
         }
   void set(std::vector<bbox_t> result_vec) {
      for (size_t i = 0; i < result_vec.size() && i < state_size*2; ++i) {
         kf.statePost.at<float>(i * 2 + 0) = result_vec[i].x;
         kf.statePost.at<float>(i * 2 + 1) = result_vec[i].y;
      }
   }

      // draw preview box (from old or current frame)
      for (size_t i = 0; i < preview_box_track_id.size(); ++i)
      {
         // get object image
         cv::Mat dst = preview_box_track_id[i].mat_obj;
         bool current_detection = false;
   // Kalman.correct() calculates: statePost = statePre + gain * (z(k)-measurementMatrix*statePre);
   // corrected state (x(k)): x(k)=x'(k)+K(k)*(z(k)-H*x'(k))
   std::vector<bbox_t> correct(std::vector<bbox_t> result_vec) {
      cv::Mat measurement(meas_size, 1, CV_32F);
      for (size_t i = 0; i < result_vec.size() && i < meas_size * 2; ++i) {
         measurement.at<float>(i * 2 + 0) = result_vec[i].x;
         measurement.at<float>(i * 2 + 1) = result_vec[i].y;
      }
      cv::Mat estimated = kf.correct(measurement);
      for (size_t i = 0; i < result_vec.size() && i < meas_size * 2; ++i) {
         result_vec[i].x = estimated.at<float>(i * 2 + 0);
         result_vec[i].y = estimated.at<float>(i * 2 + 1);
      }
      return result_vec;
   }

         for (auto &k : result_vec) {
            if (preview_box_track_id[i].track_id == k.track_id) {
               if (one_off_detections && preview_box_track_id[i].last_showed_frames_ago > 0) break;
               bbox_t b = k;
               cv::Rect r(b.x, b.y, b.w, b.h);
               cv::Rect img_rect(cv::Point2i(0, 0), src_mat.size());
               cv::Rect rect_roi = r & img_rect;
               if (rect_roi.width > 1 || rect_roi.height > 1) {
                  cv::Mat roi = src_mat(rect_roi);
                  cv::resize(roi, dst, cv::Size(preview_box_size, preview_box_size));
                  preview_box_track_id[i].mat_obj = dst.clone();
                  current_detection = true;
   // Kalman.predict() calculates: statePre = TransitionMatrix * statePost;
   // predicted state (x'(k)): x(k)=A*x(k-1)+B*u(k)
   std::vector<bbox_t> predict() {
      std::vector<bbox_t> result_vec;
      cv::Mat control;
      cv::Mat prediction = kf.predict(control);
      for (size_t i = 0; i < prediction.rows && i < state_size * 2; ++i) {
         result_vec[i].x = prediction.at<float>(i * 2 + 0);
         result_vec[i].y = prediction.at<float>(i * 2 + 1);
      }
      return result_vec;
   }

};




class extrapolate_coords_t {
public:
   std::vector<bbox_t> old_result_vec;
   std::vector<float> dx_vec, dy_vec, time_vec;
   std::vector<float> old_dx_vec, old_dy_vec;

   void new_result(std::vector<bbox_t> new_result_vec, float new_time) {
      old_dx_vec = dx_vec;
      old_dy_vec = dy_vec;
      if (old_dx_vec.size() != old_result_vec.size()) std::cout << "old_dx != old_res \n";
      dx_vec = std::vector<float>(new_result_vec.size(), 0);
      dy_vec = std::vector<float>(new_result_vec.size(), 0);
      update_result(new_result_vec, new_time, false);
      old_result_vec = new_result_vec;
      time_vec = std::vector<float>(new_result_vec.size(), new_time);
   }

   void update_result(std::vector<bbox_t> new_result_vec, float new_time, bool update = true) {
      for (size_t i = 0; i < new_result_vec.size(); ++i) {
         for (size_t k = 0; k < old_result_vec.size(); ++k) {
            if (old_result_vec[k].track_id == new_result_vec[i].track_id && old_result_vec[k].obj_id == new_result_vec[i].obj_id) {
               float const delta_time = new_time - time_vec[k];
               if (abs(delta_time) < 1) break;
               size_t index = (update) ? k : i;
               float dx = ((float)new_result_vec[i].x - (float)old_result_vec[k].x) / delta_time;
               float dy = ((float)new_result_vec[i].y - (float)old_result_vec[k].y) / delta_time;
               float old_dx = dx, old_dy = dy;

               // if it's shaking
               if (update) {
                  if (dx * dx_vec[i] < 0) dx = dx / 2;
                  if (dy * dy_vec[i] < 0) dy = dy / 2;
               } else {
                  if (dx * old_dx_vec[k] < 0) dx = dx / 2;
                  if (dy * old_dy_vec[k] < 0) dy = dy / 2;
               }
               dx_vec[index] = dx;
               dy_vec[index] = dy;

               //if (old_dx == dx && old_dy == dy) std::cout << "not shakin \n";
               //else std::cout << "shakin \n";

               if (dx_vec[index] > 1000 || dy_vec[index] > 1000) {
                  //std::cout << "!!! bad dx or dy, dx = " << dx_vec[index] << ", dy = " << dy_vec[index] << 
                  // ", delta_time = " << delta_time << ", update = " << update << std::endl;
                  dx_vec[index] = 0;
                  dy_vec[index] = 0;						
               }
               old_result_vec[k].x = new_result_vec[i].x;
               old_result_vec[k].y = new_result_vec[i].y;
               time_vec[k] = new_time;
               break;
            }
         }

         // draw object image
         if (draw_boxes) {
            cv::Mat dst = preview_box_track_id[i].mat_obj;
            if (preview_box_track_id[i].last_showed_frames_ago < frames_history &&
               dst.size() == cv::Size(preview_box_size, preview_box_size))
            {
               cv::Rect dst_rect_roi(cv::Point2i(i * preview_box_size, draw_mat.rows - bottom_offset), dst.size());
               cv::Mat dst_roi = draw_mat(dst_rect_roi);
               dst.copyTo(dst_roi);

               cv::Scalar color = obj_id_to_color(preview_box_track_id[i].obj_id);
               int thickness = (current_detection) ? 5 : 1;
               cv::rectangle(draw_mat, dst_rect_roi, color, thickness);
            }
         }
      }
   }

   std::vector<bbox_t> predict(float cur_time) {
      std::vector<bbox_t> result_vec = old_result_vec;
      for (size_t i = 0; i < old_result_vec.size(); ++i) {
         float const delta_time = cur_time - time_vec[i];
         auto &bbox = result_vec[i];
         float new_x = (float) bbox.x + dx_vec[i] * delta_time;
         float new_y = (float) bbox.y + dy_vec[i] * delta_time;
         if (new_x > 0) bbox.x = new_x;
         else bbox.x = 0;
         if (new_y > 0) bbox.y = new_y;
         else bbox.y = 0;
      }
      return result_vec;
   }

};


void draw_boxes(cv::Mat mat_img, std::vector<bbox_t> result_vec, std::vector<std::string> obj_names, 
   unsigned int wait_msec = 0, int current_det_fps = -1, int current_cap_fps = -1)
   int current_det_fps = -1, int current_cap_fps = -1)
{
   int const colors[6][3] = { { 1,0,1 },{ 0,0,1 },{ 0,1,1 },{ 0,1,0 },{ 1,1,0 },{ 1,0,0 } };

   for (auto &i : result_vec) {
      cv::Scalar color = obj_id_to_color(i.obj_id);
      cv::rectangle(mat_img, cv::Rect(i.x, i.y, i.w, i.h), color, 5);
      cv::rectangle(mat_img, cv::Rect(i.x, i.y, i.w, i.h), color, 2);
      if (obj_names.size() > i.obj_id) {
         std::string obj_name = obj_names[i.obj_id];
         if (i.track_id > 0) obj_name += " - " + std::to_string(i.track_id);
         cv::Size const text_size = getTextSize(obj_name, cv::FONT_HERSHEY_COMPLEX_SMALL, 1.2, 2, 0);
         int const max_width = (text_size.width > i.w + 2) ? text_size.width : (i.w + 2);
         cv::rectangle(mat_img, cv::Point2f(std::max((int)i.x - 3, 0), std::max((int)i.y - 30, 0)), 
         cv::rectangle(mat_img, cv::Point2f(std::max((int)i.x - 1, 0), std::max((int)i.y - 30, 0)), 
            cv::Point2f(std::min((int)i.x + max_width, mat_img.cols-1), std::min((int)i.y, mat_img.rows-1)), 
            color, CV_FILLED, 8, 0);
         putText(mat_img, obj_name, cv::Point2f(i.x, i.y - 10), cv::FONT_HERSHEY_COMPLEX_SMALL, 1.2, cv::Scalar(0, 0, 0), 2);
@@ -163,9 +194,6 @@
      std::string fps_str = "FPS detection: " + std::to_string(current_det_fps) + "   FPS capture: " + std::to_string(current_cap_fps);
      putText(mat_img, fps_str, cv::Point2f(10, 20), cv::FONT_HERSHEY_COMPLEX_SMALL, 1.2, cv::Scalar(50, 255, 0), 2);
   }

   cv::imshow("window name", mat_img);
   cv::waitKey(wait_msec);
}
#endif   // OPENCV

@@ -204,16 +232,17 @@
   }
   else if (argc > 1) filename = argv[1];

   float const thresh = (argc > 5) ? std::stof(argv[5]) : 0.20;

   Detector detector(cfg_file, weights_file);

   auto obj_names = objects_names_from_file(names_file);
   std::string out_videofile = "result.avi";
   bool const save_output_videofile = false;
   bool const save_output_videofile = true;
#ifdef TRACK_OPTFLOW
   Tracker_optflow tracker_flow;
   detector.wait_stream = true;
#endif
   preview_boxes_t large_preview(100, 150, false), small_preview(50, 50, true);

   while (true) 
   {     
@@ -223,6 +252,12 @@
      
      try {
#ifdef OPENCV
         extrapolate_coords_t extrapolate_coords;
         bool extrapolate_flag = false;
         float cur_time_extrapolate = 0, old_time_extrapolate = 0;
         preview_boxes_t large_preview(100, 150, false), small_preview(50, 50, true);
         bool show_small_boxes = false;

         std::string const file_ext = filename.substr(filename.find_last_of(".") + 1);
         std::string const protocol = filename.substr(0, 7);
         if (file_ext == "avi" || file_ext == "mp4" || file_ext == "mjpg" || file_ext == "mov" ||  // video file
@@ -261,33 +296,41 @@
                  cur_frame = cap_frame.clone();
               }
               t_cap = std::thread([&]() { cap >> cap_frame; });
               ++cur_time_extrapolate;

               // swap result bouned-boxes and input-frame
               if(consumed)
               {
                  std::unique_lock<std::mutex> lock(mtx);
                  det_image = detector.mat_to_image_resize(cur_frame);
                  auto old_result_vec = result_vec;
                  result_vec = thread_result_vec;
                  result_vec = detector.tracking_id(result_vec);  // comment it - if track_id is not required
                  auto old_result_vec = detector.tracking_id(result_vec);
                  auto detected_result_vec = thread_result_vec;
                  result_vec = detected_result_vec;
#ifdef TRACK_OPTFLOW
                  // track optical flow
                  if (track_optflow_queue.size() > 0) {
                     small_preview.draw_preview_boxes(track_optflow_queue.front(), cur_frame, result_vec, false);

                     std::queue<cv::Mat> new_track_optflow_queue;
                     //std::cout << "\n !!!! all = " << track_optflow_queue.size() << ", cur = " << passed_flow_frames << std::endl;
                     tracker_flow.update_tracking_flow(track_optflow_queue.front());
                     cv::Mat first_frame = track_optflow_queue.front();
                     tracker_flow.update_tracking_flow(track_optflow_queue.front(), result_vec);

                     while (track_optflow_queue.size() > 1) {
                        track_optflow_queue.pop();
                        result_vec = tracker_flow.tracking_flow(track_optflow_queue.front(), result_vec);
                        if (track_optflow_queue.size() <= passed_flow_frames && new_track_optflow_queue.size() == 0)
                           new_track_optflow_queue = track_optflow_queue;
                        result_vec = tracker_flow.tracking_flow(track_optflow_queue.front(), true);
                     }
                     track_optflow_queue = new_track_optflow_queue;
                     track_optflow_queue.pop();
                     passed_flow_frames = 0;

                     result_vec = detector.tracking_id(result_vec);
                     auto tmp_result_vec = detector.tracking_id(detected_result_vec, false);
                     small_preview.set(first_frame, tmp_result_vec);

                     extrapolate_coords.new_result(tmp_result_vec, old_time_extrapolate);
                     old_time_extrapolate = cur_time_extrapolate;
                     extrapolate_coords.update_result(result_vec, cur_time_extrapolate - 1);
                  }
#else
                  result_vec = detector.tracking_id(result_vec);  // comment it - if track_id is not required					
                  extrapolate_coords.new_result(result_vec, cur_time_extrapolate - 1);
#endif
                  // add old tracked objects
                  for (auto &i : old_result_vec) {
@@ -298,10 +341,14 @@
                        if (i.frames_counter-- > 1)
                           result_vec.push_back(i);
                     }
                     else
                     else {
                        it->frames_counter = std::min((unsigned)3, i.frames_counter + 1);
                     }
                  }

#ifdef TRACK_OPTFLOW
                  tracker_flow.update_cur_bbox_vec(result_vec);
                  result_vec = tracker_flow.tracking_flow(cur_frame, true);   // track optical flow
#endif
                  consumed = false;
                  cv_pre_tracked.notify_all();
               }
@@ -311,18 +358,20 @@
                     auto current_image = det_image;
                     consumed = true;
                     while (current_image.use_count() > 0) {
                        auto result = detector.detect_resized(*current_image, frame_size, 0.20, false);  // true
                        auto result = detector.detect_resized(*current_image, frame_size, thresh, false);   // true
                        ++fps_det_counter;
                        std::unique_lock<std::mutex> lock(mtx);
                        thread_result_vec = result;
                        current_image = det_image;
                        consumed = true;
                        cv_detected.notify_all();
                        if(detector.wait_stream)
                        if (detector.wait_stream) {
                           while (consumed) cv_pre_tracked.wait(lock);
                        }
                        current_image = det_image;
                     }
                  });
               }
               //while (!consumed); // sync detection

               if (!cur_frame.empty()) {
                  steady_end = std::chrono::steady_clock::now();
@@ -334,16 +383,28 @@
                     fps_cap_counter = 0;
                  }

                  large_preview.set(cur_frame, result_vec);
#ifdef TRACK_OPTFLOW
                  ++passed_flow_frames;
                  track_optflow_queue.push(cur_frame.clone());
                  result_vec = tracker_flow.tracking_flow(cur_frame, result_vec, true);   // track optical flow
                  small_preview.draw_preview_boxes(cur_frame.clone(), cur_frame, result_vec, true);
#endif
                  large_preview.draw_preview_boxes(cur_frame.clone(), cur_frame, result_vec, true);

                  draw_boxes(cur_frame, result_vec, obj_names, 3, current_det_fps, current_cap_fps);  // 3 or 16ms
                  result_vec = tracker_flow.tracking_flow(cur_frame);   // track optical flow
                  extrapolate_coords.update_result(result_vec, cur_time_extrapolate);
                  small_preview.draw(cur_frame, show_small_boxes);
#endif						
                  auto result_vec_draw = result_vec;
                  if (extrapolate_flag) {
                     result_vec_draw = extrapolate_coords.predict(cur_time_extrapolate);
                     cv::putText(cur_frame, "extrapolate", cv::Point2f(10, 40), cv::FONT_HERSHEY_COMPLEX_SMALL, 1.0, cv::Scalar(50, 50, 0), 2);
                  }
                  draw_boxes(cur_frame, result_vec_draw, obj_names, current_det_fps, current_cap_fps);
                  //show_console_result(result_vec, obj_names);
                  large_preview.draw(cur_frame);

                  cv::imshow("window name", cur_frame);
                  int key = cv::waitKey(3);  // 3 or 16ms
                  if (key == 'f') show_small_boxes = !show_small_boxes;
                  if (key == 'p') while (true) if(cv::waitKey(100) == 'p') break;
                  if (key == 'e') extrapolate_flag = !extrapolate_flag;

                  if (output_video.isOpened() && videowrite_ready) {
                     if (t_videowrite.joinable()) t_videowrite.join();
@@ -387,6 +448,8 @@
            std::vector<bbox_t> result_vec = detector.detect(mat_img);
            result_vec = detector.tracking_id(result_vec);  // comment it - if track_id is not required
            draw_boxes(mat_img, result_vec, obj_names);
            cv::imshow("window name", mat_img);
            cv::waitKey(3);   // 3 or 16ms
            show_console_result(result_vec, obj_names);
         }
#else