[MOT] add c++ implementation for flow_statistics (#4510)

* add implementment for FlowStatics

* rename count to entrance_count; rename count_set to id_set

* add a todo for entrance line setting

* rename count to do_entrance_counting

* convert print_save_file to the origin line

deploy/pptracking/include/pipeline.h

@@ -48,11 +48,12 @@ class Pipeline {
                     const bool use_mkldnn = false,
                     const int cpu_threads = 1,
                     const bool trt_calib_mode = false,
-                    const bool count = false,
+                    const bool do_entrance_counting = false,
                     const bool save_result = false,
                     const std::string& scene = "pedestrian",
                     const bool tiny_obj = false,
-                    const bool is_mtmct = false) {
+                    const bool is_mtmct = false,
+                    const int secs_interval = 10) {
     std::vector<std::string> input;
     this->input_ = input;
     this->device_ = device;
@@ -63,7 +64,8 @@ class Pipeline {
     this->use_mkldnn_ = use_mkldnn;
     this->cpu_threads_ = cpu_threads;
     this->trt_calib_mode_ = trt_calib_mode;
-    this->count_ = count;
+    this->do_entrance_counting_ = do_entrance_counting;
+    this->secs_interval_ = secs_interval_;
     this->save_result_ = save_result;
     SelectModel(scene, tiny_obj, is_mtmct);
     InitPredictor();
@@ -81,11 +83,16 @@ class Pipeline {
   // Run pipeline in stream
   void RunMOTStream(const cv::Mat img,
                     const int frame_id,
+                    const int video_fps,
+                    const Rect entrance,
                     cv::Mat out_img,
                     std::vector<std::string>* records,
-                    std::vector<int>* count_list,
+                    std::set<int>* count_set,
+                    std::set<int>* interval_count_set,
                     std::vector<int>* in_count_list,
-                    std::vector<int>* out_count_list);
+                    std::vector<int>* out_count_list,
+                    std::map<int, std::vector<float>>* prev_center,
+                    std::vector<std::string>* flow_records);
   void RunMTMCTStream(const std::vector<cv::Mat> imgs,
                       std::vector<std::string>* records);
 
@@ -114,8 +121,9 @@ class Pipeline {
   bool use_mkldnn_ = false;
   int cpu_threads_ = 1;
   bool trt_calib_mode_ = false;
-  bool count_ = false;
+  bool do_entrance_counting_ = false;
   bool save_result_ = false;
+  int secs_interval_ = 10;
 };
 
 }  // namespace PaddleDetection

deploy/pptracking/include/postprocess.h

@@ -14,11 +14,14 @@
 
 #pragma once
 
+#include <glog/logging.h>
+
 #include <ctime>
 #include <memory>
 #include <string>
 #include <utility>
 #include <vector>
+#include <set>
 
 #include <opencv2/core/core.hpp>
 #include <opencv2/highgui/highgui.hpp>
@@ -40,9 +43,17 @@ cv::Mat VisualizeTrackResult(const cv::Mat& img,
 // Pedestrian/Vehicle Counting
 void FlowStatistic(const MOTResult& results,
                    const int frame_id,
-                   std::vector<int>* count_list,
-                   std::vector<int>* in_count_list,
-                   std::vector<int>* out_count_list);
+                   const int secs_interval,
+                   const bool do_entrance_counting,
+                   const int video_fps,
+                   const Rect entrance,
+                   std::set<int>* id_set,
+                   std::set<int>* interval_id_set,
+                   std::vector<int>* in_id_list,
+                   std::vector<int>* out_id_list,
+                   std::map<int, std::vector<float>>* prev_center,
+                   std::vector<std::string>* records);
+
 
 // Save Tracking Results
 void SaveMOTResult(const MOTResult& results,

deploy/pptracking/src/main.cc

@@ -54,7 +54,10 @@ DEFINE_bool(trt_calib_mode,
             "If the model is produced by TRT offline quantitative calibration, "
             "trt_calib_mode need to set True");
 DEFINE_bool(tiny_obj, false, "Whether tracking tiny object");
-DEFINE_bool(count, false, "Whether counting after tracking");
+DEFINE_bool(do_entrance_counting, false,
+            "Whether counting the numbers of identifiers entering "
+            "or getting out from the entrance.");
+DEFINE_int32(secs_interval, 10, "The seconds interval to count after tracking");
 DEFINE_bool(save_result, false, "Whether saving result after tracking");
 DEFINE_string(
     scene,
@@ -140,11 +143,12 @@ int main(int argc, char** argv) {
                                      FLAGS_use_mkldnn,
                                      FLAGS_cpu_threads,
                                      FLAGS_trt_calib_mode,
-                                     FLAGS_count,
+                                     FLAGS_do_entrance_counting,
                                      FLAGS_save_result,
                                      FLAGS_scene,
                                      FLAGS_tiny_obj,
-                                     FLAGS_is_mtmct);
+                                     FLAGS_is_mtmct,
+                                     FLAGS_secs_interval);
 
   pipeline.SetInput(FLAGS_video_file);
   if (!FLAGS_video_other_file.empty()) {

deploy/pptracking/src/pipeline.cc

@@ -18,6 +18,7 @@
 #include <iomanip>
 #include <iostream>
 #include <string>
+
 #include "include/pipeline.h"
 #include "include/postprocess.h"
 #include "include/predictor.h"
@@ -159,9 +160,14 @@ void Pipeline::PredictMOT(const std::string& video_path) {
 
   PaddleDetection::MOTResult result;
   std::vector<double> det_times(3);
-  std::vector<int> count_list;
-  std::vector<int> in_count_list;
-  std::vector<int> out_count_list;
+  std::set<int> id_set;
+  std::set<int> interval_id_set;
+  std::vector<int> in_id_list;
+  std::vector<int> out_id_list;
+  std::map<int, std::vector<float>> prev_center;
+  Rect entrance = {0, static_cast<float>(video_height) / 2,
+                   static_cast<float>(video_width),
+                   static_cast<float>(video_height) / 2};
   double times;
   double total_time;
   // Capture all frames and do inference
@@ -169,6 +175,7 @@ void Pipeline::PredictMOT(const std::string& video_path) {
   int frame_id = 0;
 
   std::vector<std::string> records;
+  std::vector<std::string> flow_records;
   records.push_back("result format: frame_id, track_id, x1, y1, w, h\n");
 
   LOG(INFO) << "------------------- Predict info ------------------------";
@@ -188,13 +195,13 @@ void Pipeline::PredictMOT(const std::string& video_path) {
 
     cv::Mat out_img = PaddleDetection::VisualizeTrackResult(
         frame, result, 1000. / times, frame_id);
+    
+   // TODO: the entrance line can be set by users
+    PaddleDetection::FlowStatistic(
+        result, frame_id, secs_interval_, do_entrance_counting_, video_fps, entrance,
+        &id_set, &interval_id_set, &in_id_list, &out_id_list,
+        &prev_center, &flow_records);
 
-    if (count_) {
-      // Count total number
-      // Count in & out number
-      PaddleDetection::FlowStatistic(
-          result, frame_id, &count_list, &in_count_list, &out_count_list);
-    }
     if (save_result_) {
       PaddleDetection::SaveMOTResult(result, frame_id, &records);
     }
@@ -221,6 +228,17 @@ void Pipeline::PredictMOT(const std::string& video_path) {
 
     fclose(fp);
     LOG(INFO) << "txt result output saved as " << result_output_path.c_str();
+    
+    result_output_path = output_dir_ + OS_PATH_SEP + "flow_statistic.txt";
+    if ((fp = fopen(result_output_path.c_str(), "w+")) == NULL) {
+      printf("Open %s error.\n", result_output_path);
+      return;
+    }
+    for (int l; l < flow_records.size(); ++l) {
+      fprintf(fp, flow_records[l].c_str());
+    }
+    fclose(fp);
+    LOG(INFO) << "txt flow statistic saved as " << result_output_path.c_str();
   }
 }
 
@@ -230,11 +248,16 @@ void Pipeline::PredictMTMCT(const std::vector<std::string> video_path) {
 
 void Pipeline::RunMOTStream(const cv::Mat img,
                             const int frame_id,
+                            const int video_fps,
+                            const Rect entrance,
                             cv::Mat out_img,
                             std::vector<std::string>* records,
-                            std::vector<int>* count_list,
-                            std::vector<int>* in_count_list,
-                            std::vector<int>* out_count_list) {
+                            std::set<int>* id_set,
+                            std::set<int>* interval_id_set,
+                            std::vector<int>* in_id_list,
+                            std::vector<int>* out_id_list,
+                            std::map<int, std::vector<float>>* prev_center,
+                            std::vector<std::string>* flow_records) {
   PaddleDetection::MOTResult result;
   std::vector<double> det_times(3);
   double times;
@@ -250,15 +273,15 @@ void Pipeline::RunMOTStream(const cv::Mat img,
   LOG(INFO) << "frame_id: " << frame_id
             << " predict time(s): " << total_time / 1000;
 
-  out_img = PaddleDetection::VisualizeTrackResult(
-      img, result, 1000. / times, frame_id);
+  out_img = PaddleDetection::VisualizeTrackResult(img, result, 1000. / times,
+                                                  frame_id);
 
-  if (count_) {
-    // Count total number
-    // Count in & out number
-    PaddleDetection::FlowStatistic(
-        result, frame_id, count_list, in_count_list, out_count_list);
-  }
+  // Count total number
+  // Count in & out number
+  PaddleDetection::FlowStatistic(result, frame_id, secs_interval_, do_entrance_counting_,
+                                 video_fps, entrance, id_set,
+                                 interval_id_set, in_id_list,
+                                 out_id_list, prev_center, flow_records);
 
   PrintBenchmarkLog(det_times, frame_id);
   if (save_result_) {
@@ -303,4 +326,4 @@ void Pipeline::PrintBenchmarkLog(const std::vector<double> det_time,
             << ", postprocess_time(ms): " << det_time[2] / num;
 }
 
-}  // namespace PaddleDetection
+} // namespace PaddleDetection

deploy/pptracking/src/postprocess.cc

@@ -16,6 +16,7 @@
 // for setprecision
 #include <chrono>
 #include <iomanip>
+#include <iostream>
 #include "include/postprocess.h"
 
 namespace PaddleDetection {
@@ -101,10 +102,80 @@ cv::Mat VisualizeTrackResult(const cv::Mat& img,
 
 void FlowStatistic(const MOTResult& results,
                    const int frame_id,
-                   std::vector<int>* count_list,
-                   std::vector<int>* in_count_list,
-                   std::vector<int>* out_count_list) {
-  throw "Not Implement";
+                   const int secs_interval,
+                   const bool do_entrance_counting,
+                   const int video_fps,
+                   const Rect entrance, 
+                   std::set<int>* id_set,
+                   std::set<int>* interval_id_set, 
+                   std::vector<int>* in_id_list, 
+                   std::vector<int>* out_id_list,
+                   std::map<int, std::vector<float>>* prev_center,
+                   std::vector<std::string>* records) {
+  if (frame_id == 0)
+    interval_id_set->clear();
+  
+  if (do_entrance_counting) {
+    // Count in and out number: 
+    // Use horizontal center line as the entrance just for simplification.
+    // If a person located in the above the horizontal center line 
+    // at the previous frame and is in the below the line at the current frame,
+    // the in number is increased by one.
+    // If a person was in the below the horizontal center line 
+    // at the previous frame and locates in the below the line at the current frame,
+    // the out number is increased by one.
+    // TODO: if the entrance is not the horizontal center line,
+    // the counting method should be optimized.
+    
+    float entrance_y = entrance.top; 
+    for (const auto& result : results) {
+      float center_x = (result.rects.left + result.rects.right) / 2;
+      float center_y = (result.rects.top + result.rects.bottom) / 2;
+      int ids = result.ids;
+      std::map<int, std::vector<float>>::iterator iter;  
+      iter = prev_center->find(ids);
+      if (iter != prev_center->end()) {
+        if (iter->second[1] <= entrance_y && center_y > entrance_y) {
+          in_id_list->push_back(ids);
+        }
+        if (iter->second[1] >= entrance_y && center_y < entrance_y) {
+          out_id_list->push_back(ids);
+        }
+        (*prev_center)[ids][0] = center_x;
+        (*prev_center)[ids][1] = center_y;
+      } else {
+        prev_center->insert(
+          std::pair<int, std::vector<float>>(ids, {center_x, center_y}));
+      }
+    }
+  }
+
+  // Count totol number, number at a manual-setting interval
+  for (const auto& result : results) {
+    id_set->insert(result.ids);
+    interval_id_set->insert(result.ids);
+  }
+
+  std::ostringstream os;
+  os << "Frame id: " << frame_id
+     << ", Total count: " << id_set->size();
+  if (do_entrance_counting) {
+    os << ", In count: " << in_id_list->size()
+       << ", Out count: " << out_id_list->size();
+  }
+
+  // Reset counting at the interval beginning
+  int curr_interval_count = -1;
+  if (frame_id % video_fps == 0 && frame_id / video_fps % secs_interval == 0) {
+    curr_interval_count = interval_id_set->size();
+    os << ", Count during " << secs_interval
+       << " secs: " << curr_interval_count;
+    interval_id_set->clear();
+  }
+  os << "\n";
+  std::string record = os.str();
+  records->push_back(record);
+  LOG(INFO) << record;
 }
 
 void SaveMOTResult(const MOTResult& results,