From 1b5afb45838e603fa6780762eb8cc59246dc2d81 Mon Sep 17 00:00:00 2001
From: IlyaOvodov <b@ovdv.ru>
Date: Tue, 08 May 2018 11:09:35 +0000
Subject: [PATCH] Output improvements for detector results: When printing detector results, output was done in random order, obfuscating results for interpreting. Now: 1. Text output includes coordinates of rects in (left,right,top,bottom in pixels) along with label and score 2. Text output is sorted by rect lefts to simplify finding appropriate rects on image 3. If several class probs are > thresh for some detection, the most probable is written first and coordinates for others are not repeated 4. Rects are imprinted in image in order by their best class prob, so most probable rects are always on top and not overlayed by less probable ones 5. Most probable label for rect is always written first Also: 6. Message about low GPU memory include required amount
---
src/yolo_console_dll.cpp | 204 ++++++++++++++++++++++++++++++++++++++++++++++----
1 files changed, 186 insertions(+), 18 deletions(-)
diff --git a/src/yolo_console_dll.cpp b/src/yolo_console_dll.cpp
index 686ea33..ea4330e 100644
--- a/src/yolo_console_dll.cpp
+++ b/src/yolo_console_dll.cpp
@@ -11,11 +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
@@ -25,17 +30,153 @@
#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)
@@ -85,9 +226,9 @@
int main(int argc, char *argv[])
{
- std::string names_file = "data/voc.names";
- std::string cfg_file = "cfg/yolo-voc.cfg";
- std::string weights_file = "yolo-voc.weights";
+ 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 > 4) { //voc.names yolo-voc.cfg yolo-voc.weights test.mp4
@@ -104,7 +245,7 @@
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 +259,9 @@
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;
@@ -133,6 +277,7 @@
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;
@@ -159,6 +304,7 @@
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 +323,23 @@
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 +355,7 @@
}
#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();
@@ -214,15 +365,16 @@
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, thresh, false); // 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;
consumed = true;
cv_detected.notify_all();
if (detector.wait_stream) {
- while (consumed) cv_pre_tracked.wait(lock);
+ while (consumed && !exit_flag) cv_pre_tracked.wait(lock);
}
current_image = det_image;
}
@@ -245,16 +397,24 @@
++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 (key == 27) { exit_flag = true; break; }
if (output_video.isOpened() && videowrite_ready) {
if (t_videowrite.joinable()) t_videowrite.join();
@@ -274,10 +434,12 @@
}
#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);
@@ -295,12 +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_id(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);
- cv::waitKey(3); // 3 or 16ms
show_console_result(result_vec, obj_names);
+ cv::waitKey(0);
}
#else
//std::vector<bbox_t> result_vec = detector.detect(filename);
--
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