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 | 317 +++++++++++++++++++++++++++++++++++++++++++---------
1 files changed, 262 insertions(+), 55 deletions(-)
diff --git a/src/yolo_console_dll.cpp b/src/yolo_console_dll.cpp
index 0e291a4..ea4330e 100644
--- a/src/yolo_console_dll.cpp
+++ b/src/yolo_console_dll.cpp
@@ -11,10 +11,16 @@
#ifdef _WIN32
#define OPENCV
-#include "windows.h"
+#define GPU
#endif
-#define TRACK_OPTFLOW
+// 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
@@ -24,36 +30,168 @@
#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,
- 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);
@@ -63,8 +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
@@ -90,17 +226,29 @@
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("cfg/yolo-voc.cfg", "yolo-voc.weights");
- //Detector detector("tiny-yolo-voc_air.cfg", "backup/tiny-yolo-voc_air_5000.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)
@@ -111,6 +259,12 @@
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
@@ -123,6 +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;
@@ -131,7 +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);
@@ -149,58 +304,83 @@
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);
- result_vec = thread_result_vec;
- result_vec = detector.tracking(result_vec); // comment it - if track_id is not required
- consumed = false;
-
+ std::unique_lock<std::mutex> lock(mtx);
+ det_image = detector.mat_to_image_resize(cur_frame);
+ 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::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());
+ // 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();
- while (track_optflow_queue.size() > 0) {
- 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.pop();
+ passed_flow_frames = 0;
- track_optflow_queue.pop();
- }
- track_optflow_queue = new_track_optflow_queue;
- new_track_optflow_queue.swap(std::queue<cv::Mat>());
- 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 - 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, false); // true
- //Sleep(200);
- Sleep(50);
+ 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();
@@ -212,14 +392,29 @@
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); // track optical flow
-#endif
-
- draw_boxes(cur_frame, result_vec, obj_names, 3, current_det_fps, current_cap_fps);
+ 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();
@@ -231,16 +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);
- //}
+ if (protocol != "rtsp://" && protocol != "http://" && protocol != "https:/") {
+ std::unique_lock<std::mutex> lock(mtx);
+ 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);
@@ -258,10 +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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