From d502dea9a451c290f602ba18bc61f4f79c51be0c Mon Sep 17 00:00:00 2001
From: Alexey <AlexeyAB@users.noreply.github.com>
Date: Mon, 04 Jun 2018 10:55:27 +0000
Subject: [PATCH] Update Readme.md
---
src/yolo_console_dll.cpp | 320 ++++++++++++++++++++++++++++++++++++++++++++++++-----
1 files changed, 289 insertions(+), 31 deletions(-)
diff --git a/src/yolo_console_dll.cpp b/src/yolo_console_dll.cpp
index 58b3893..2eca267 100644
--- a/src/yolo_console_dll.cpp
+++ b/src/yolo_console_dll.cpp
@@ -2,6 +2,7 @@
#include <iomanip>
#include <string>
#include <vector>
+#include <queue>
#include <fstream>
#include <thread>
#include <atomic>
@@ -10,8 +11,16 @@
#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
+
+//#include "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v9.1\include\cuda_runtime.h"
+//#pragma comment(lib, "C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v9.1/lib/x64/cudart.lib")
+//static std::shared_ptr<image_t> device_ptr(NULL, [](void *img) { cudaDeviceReset(); });
+
#include "yolo_v2_class.hpp" // imported functions from DLL
#ifdef OPENCV
@@ -19,31 +28,170 @@
#include "opencv2/core/version.hpp"
#ifndef CV_VERSION_EPOCH
#include "opencv2/videoio/videoio.hpp"
-#pragma comment(lib, "opencv_world320.lib")
+#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
-#pragma comment(lib, "opencv_core2413.lib")
-#pragma comment(lib, "opencv_imgproc2413.lib")
-#pragma comment(lib, "opencv_highgui2413.lib")
-#endif
+#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 // 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,
- 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) {
- int const offset = i.obj_id * 123457 % 6;
- int const color_scale = 150 + (i.obj_id * 123457) % 100;
- cv::Scalar color(colors[offset][0], colors[offset][1], colors[offset][2]);
- color *= color_scale;
- cv::rectangle(mat_img, cv::Rect(i.x, i.y, i.w, i.h), color, 5);
+ 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, 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);
@@ -53,8 +201,6 @@
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
@@ -80,14 +226,30 @@
int main(int argc, char *argv[])
{
+ std::string names_file = "data/coco.names";
+ std::string cfg_file = "cfg/yolov3.cfg";
+ std::string weights_file = "yolov3.weights";
std::string filename;
- if (argc > 1) filename = argv[1];
- Detector detector("yolo-voc.cfg", "yolo-voc.weights");
+ if (argc > 4) { //voc.names yolo-voc.cfg yolo-voc.weights test.mp4
+ names_file = argv[1];
+ cfg_file = argv[2];
+ weights_file = argv[3];
+ filename = argv[4];
+ }
+ else if (argc > 1) filename = argv[1];
- auto obj_names = objects_names_from_file("data/voc.names");
+ 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
while (true)
{
@@ -97,16 +259,25 @@
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
protocol == "rtmp://" || protocol == "rtsp://" || protocol == "http://" || protocol == "https:/") // video network stream
{
cv::Mat cap_frame, cur_frame, det_frame, write_frame;
+ std::queue<cv::Mat> track_optflow_queue;
+ int passed_flow_frames = 0;
std::shared_ptr<image_t> det_image;
std::vector<bbox_t> result_vec, thread_result_vec;
detector.nms = 0.02; // comment it - if track_id is not required
std::atomic<bool> consumed, videowrite_ready;
+ bool exit_flag = false;
consumed = true;
videowrite_ready = true;
std::atomic<int> fps_det_counter, fps_cap_counter;
@@ -115,7 +286,7 @@
int current_det_fps = 0, current_cap_fps = 0;
std::thread t_detect, t_cap, t_videowrite;
std::mutex mtx;
- std::condition_variable cv;
+ std::condition_variable cv_detected, cv_pre_tracked;
std::chrono::steady_clock::time_point steady_start, steady_end;
cv::VideoCapture cap(filename); cap >> cur_frame;
int const video_fps = cap.get(CV_CAP_PROP_FPS);
@@ -124,39 +295,92 @@
if (save_output_videofile)
output_video.open(out_videofile, CV_FOURCC('D', 'I', 'V', 'X'), std::max(35, video_fps), frame_size, true);
- while (!cur_frame.empty()) {
+ while (!cur_frame.empty())
+ {
+ // always sync
if (t_cap.joinable()) {
t_cap.join();
++fps_cap_counter;
cur_frame = cap_frame.clone();
}
t_cap = std::thread([&]() { cap >> cap_frame; });
+ ++cur_time_extrapolate;
- // swap result and input-frame
+ // 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);
- result_vec = thread_result_vec;
- result_vec = detector.tracking(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) {
+ //std::cout << "\n !!!! all = " << track_optflow_queue.size() << ", cur = " << passed_flow_frames << std::endl;
+ 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(), 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, 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) {
+ auto it = std::find_if(result_vec.begin(), result_vec.end(),
+ [&i](bbox_t const& b) { return b.track_id == i.track_id && b.obj_id == i.obj_id; });
+ bool track_id_absent = (it == result_vec.end());
+ if (track_id_absent) {
+ if (i.frames_counter-- > 1)
+ result_vec.push_back(i);
+ }
+ 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();
}
- // launch thread once
+ // launch thread once - Detection
if (!t_detect.joinable()) {
t_detect = std::thread([&]() {
auto current_image = det_image;
consumed = true;
- while (current_image.use_count() > 0) {
- auto result = detector.detect_resized(*current_image, frame_size, 0.24, true);
+ while (current_image.use_count() > 0 && !exit_flag) {
+ 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;
- current_image = det_image;
consumed = true;
- cv.notify_all();
+ cv_detected.notify_all();
+ if (detector.wait_stream) {
+ while (consumed && !exit_flag) cv_pre_tracked.wait(lock);
+ }
+ current_image = det_image;
}
});
}
+ //while (!consumed); // sync detection
if (!cur_frame.empty()) {
steady_end = std::chrono::steady_clock::now();
@@ -167,8 +391,30 @@
fps_det_counter = 0;
fps_cap_counter = 0;
}
- draw_boxes(cur_frame, result_vec, obj_names, 3, current_det_fps, current_cap_fps);
+
+ 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); // 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 (key == 27) { exit_flag = true; break; }
if (output_video.isOpened() && videowrite_ready) {
if (t_videowrite.joinable()) t_videowrite.join();
@@ -180,16 +426,20 @@
}
}
+#ifndef TRACK_OPTFLOW
// wait detection result for video-file only (not for net-cam)
if (protocol != "rtsp://" && protocol != "http://" && protocol != "https:/") {
std::unique_lock<std::mutex> lock(mtx);
- while (!consumed) cv.wait(lock);
+ while (!consumed) cv_detected.wait(lock);
}
+#endif
}
+ exit_flag = true;
if (t_cap.joinable()) t_cap.join();
if (t_detect.joinable()) t_detect.join();
if (t_videowrite.joinable()) t_videowrite.join();
std::cout << "Video ended \n";
+ break;
}
else if (file_ext == "txt") { // list of image files
std::ifstream file(filename);
@@ -207,10 +457,18 @@
}
else { // image file
cv::Mat mat_img = cv::imread(filename);
+
+ auto start = std::chrono::steady_clock::now();
std::vector<bbox_t> result_vec = detector.detect(mat_img);
- result_vec = detector.tracking(result_vec); // comment it - if track_id is not required
+ auto end = std::chrono::steady_clock::now();
+ std::chrono::duration<double> spent = end - start;
+ std::cout << " Time: " << spent.count() << " sec \n";
+
+ //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);
show_console_result(result_vec, obj_names);
+ cv::waitKey(0);
}
#else
//std::vector<bbox_t> result_vec = detector.detect(filename);
--
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