From ced198e9390195875d743d77eadece99c7fd5b38 Mon Sep 17 00:00:00 2001
From: AlexeyAB <alexeyab84@gmail.com>
Date: Mon, 19 Mar 2018 23:17:26 +0000
Subject: [PATCH] Fixed gpu_id for DLL/SO
---
src/yolo_console_dll.cpp | 178 +++++++++++++++++++++++++++++++++++++++++++++++++++++++----
1 files changed, 166 insertions(+), 12 deletions(-)
diff --git a/src/yolo_console_dll.cpp b/src/yolo_console_dll.cpp
index 6aaebc5..cb0b063 100644
--- a/src/yolo_console_dll.cpp
+++ b/src/yolo_console_dll.cpp
@@ -11,10 +11,11 @@
#ifdef _WIN32
#define OPENCV
+#define GPU
#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
@@ -25,17 +26,153 @@
#include "opencv2/videoio/videoio.hpp"
#define OPENCV_VERSION CVAUX_STR(CV_VERSION_MAJOR)""CVAUX_STR(CV_VERSION_MINOR)""CVAUX_STR(CV_VERSION_REVISION)
#pragma comment(lib, "opencv_world" OPENCV_VERSION ".lib")
+#ifdef TRACK_OPTFLOW
#pragma comment(lib, "opencv_cudaoptflow" OPENCV_VERSION ".lib")
#pragma comment(lib, "opencv_cudaimgproc" OPENCV_VERSION ".lib")
#pragma comment(lib, "opencv_core" OPENCV_VERSION ".lib")
#pragma comment(lib, "opencv_imgproc" OPENCV_VERSION ".lib")
#pragma comment(lib, "opencv_highgui" OPENCV_VERSION ".lib")
+#endif // TRACK_OPTFLOW
#else
#define OPENCV_VERSION CVAUX_STR(CV_VERSION_EPOCH)""CVAUX_STR(CV_VERSION_MAJOR)""CVAUX_STR(CV_VERSION_MINOR)
#pragma comment(lib, "opencv_core" OPENCV_VERSION ".lib")
#pragma comment(lib, "opencv_imgproc" OPENCV_VERSION ".lib")
#pragma comment(lib, "opencv_highgui" OPENCV_VERSION ".lib")
-#endif
+#endif // CV_VERSION_EPOCH
+
+class track_kalman {
+public:
+ cv::KalmanFilter kf;
+ int state_size, meas_size, contr_size;
+
+
+ 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)
+ {
+ kf.init(state_size, meas_size, contr_size, CV_32F);
+
+ 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);
+ }
+
+ 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;
+ }
+ }
+
+ // 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;
+ }
+
+ // 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;
+ }
+ }
+ }
+ }
+
+ 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,
int current_det_fps = -1, int current_cap_fps = -1)
@@ -104,7 +241,7 @@
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;
@@ -118,6 +255,9 @@
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;
@@ -159,6 +299,7 @@
cur_frame = cap_frame.clone();
}
t_cap = std::thread([&]() { cap >> cap_frame; });
+ ++cur_time_extrapolate;
// swap result bouned-boxes and input-frame
if(consumed)
@@ -177,18 +318,23 @@
while (track_optflow_queue.size() > 1) {
track_optflow_queue.pop();
- result_vec = tracker_flow.tracking_flow(track_optflow_queue.front(), false);
+ result_vec = tracker_flow.tracking_flow(track_optflow_queue.front(), true);
}
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);
+ auto tmp_result_vec = detector.tracking_id(detected_result_vec, false);
small_preview.set(first_frame, tmp_result_vec);
- }
-#endif
- result_vec = detector.tracking_id(result_vec); // comment it - if track_id is not required
+ 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) {
auto it = std::find_if(result_vec.begin(), result_vec.end(),
@@ -204,7 +350,7 @@
}
#ifdef TRACK_OPTFLOW
tracker_flow.update_cur_bbox_vec(result_vec);
- result_vec = tracker_flow.tracking_flow(cur_frame, false); // track optical flow
+ result_vec = tracker_flow.tracking_flow(cur_frame, true); // track optical flow
#endif
consumed = false;
cv_pre_tracked.notify_all();
@@ -215,7 +361,8 @@
auto current_image = det_image;
consumed = true;
while (current_image.use_count() > 0) {
- auto result = detector.detect_resized(*current_image, frame_size, thresh, false); // true
+ auto result = detector.detect_resized(*current_image, frame_size.width, frame_size.height,
+ thresh, false); // true
++fps_det_counter;
std::unique_lock<std::mutex> lock(mtx);
thread_result_vec = result;
@@ -245,16 +392,23 @@
++passed_flow_frames;
track_optflow_queue.push(cur_frame.clone());
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
-
- draw_boxes(cur_frame, result_vec, obj_names, current_det_fps, current_cap_fps);
+ 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();
--
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