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Code Issues 46 Pull Requests 12 Releases 4 Activity

Fix tracker for batch size > 1

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This commit is contained in:
Fabio Bagni
2021-05-04 11:21:05 +02:00
parent 2367519799
commit 10f39d1055
2 changed files with 92 additions and 88 deletions
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include/tkDNN/CenternetDetection3DTrack.h
+6 -6
View File
@@ -1,11 +1,11 @@
#ifndef CENTERNETDETECTION3DTRACK_H
#define CENTERNETDETECTION3DTRACK_H
#include <opencv2/videoio.hpp>
#include "opencv2/opencv.hpp"
#include "kernels.h"
#include "utils.h"
#include "tkdnn.h"
#include <opencv2/videoio.hpp>
#include "opencv2/opencv.hpp"
#include <time.h>
#include <vector>
#include <numeric> // std::iota
@@ -51,7 +51,7 @@ struct trackingRes
class CenternetDetection3DTrack : public DetectionNN3D
{
private:
public:
tk::dnn::dataDim_t dim;
tk::dnn::dataDim_t dim2;
tk::dnn::dataDim_t dim_hm;
@@ -148,9 +148,9 @@ private:
std::vector<struct detectionRes> det_res;
int count_det;
//tracks
std::vector<struct trackingRes> tr_res;
std::vector<std::vector<struct trackingRes>> tr_res;
std::vector<std::vector<struct trackingRes>> batchTracked;
int count_tr;
std::vector<int> count_tr;
int track_id=0;
@@ -161,7 +161,7 @@ private:
void pre_inf(const int bi);
void _get_additional_inputs();
cv::Mat transform_preds_with_trans(float x1, float x2);
void tracking();
void tracking(int bi);
public:
tk::dnn::Network *pre_phase_net = nullptr;
src/CenternetDetection3DTrack.cpp
+86 -82
View File
@@ -13,12 +13,13 @@ bool CenternetDetection3DTrack::init(const std::string& tensor_path, const int n
nBatches = n_batches;
confThreshold = conf_thresh;
inputCalibs = k_calibs;
tr_res.resize(nBatches);
init_preprocessing();
init_pre_inf();
init_postprocessing();
init_visualization(n_classes);
count_tr = 0;
count_tr.resize(nBatches, 0);
}
bool CenternetDetection3DTrack::init_preprocessing(){
@@ -30,6 +31,7 @@ bool CenternetDetection3DTrack::init_preprocessing(){
trans2 = cv::Mat(cv::Size(3,2), CV_32F);
trans_out = cv::Mat(cv::Size(3,2), CV_32F);
dst2.at<float>(0,0)=width * 0.5;
dst2.at<float>(0,1)=width * 0.5;
dst2.at<float>(1,0)=width * 0.5;
@@ -372,6 +374,8 @@ void CenternetDetection3DTrack::preprocess(cv::Mat &frame, const int bi, const s
sz = imageF.size();
cv::warpAffine(imageF, imageF, trans, cv::Size(dim.w, dim.h), cv::INTER_LINEAR );
cv::imshow("warp", imageF);
sz = imageF.size();
imageF.convertTo(imageF, CV_32FC3, 1/255.0);
@@ -414,7 +418,7 @@ cv::Mat CenternetDetection3DTrack::transform_preds_with_trans(float x1, float x2
return trans_out * target_coords;
}
void CenternetDetection3DTrack::tracking(){
void CenternetDetection3DTrack::tracking(int bi){
float item_size[count_det];
int item_cl[count_det];
@@ -427,44 +431,44 @@ void CenternetDetection3DTrack::tracking(){
dets[i*2+1] = det_res[i].ct.at<float>(0,1);
}
float track_size[count_tr];
int track_cl[count_tr];
float tracks[2*count_tr];
for(int i=0; i<count_tr; i++){
track_size[i] = (tr_res[i].det_res.bb1.at<float>(0,0) - tr_res[i].det_res.bb0.at<float>(0,0)) *
(tr_res[i].det_res.bb1.at<float>(0,1) - tr_res[i].det_res.bb0.at<float>(0,1));
track_cl[i] = tr_res[i].det_res.cl;
tracks[i*2] = tr_res[i].det_res.ct.at<float>(0,0);
tracks[i*2+1] = tr_res[i].det_res.ct.at<float>(0,1);
float track_size[count_tr[bi]];
int track_cl[count_tr[bi]];
float tracks[2*count_tr[bi]];
for(int i=0; i<count_tr[bi]; i++){
track_size[i] = (tr_res[bi][i].det_res.bb1.at<float>(0,0) - tr_res[bi][i].det_res.bb0.at<float>(0,0)) *
(tr_res[bi][i].det_res.bb1.at<float>(0,1) - tr_res[bi][i].det_res.bb0.at<float>(0,1));
track_cl[i] = tr_res[bi][i].det_res.cl;
tracks[i*2] = tr_res[bi][i].det_res.ct.at<float>(0,0);
tracks[i*2+1] = tr_res[bi][i].det_res.ct.at<float>(0,1);
}
float dist[count_tr*count_det];
float dist[count_tr[bi]*count_det];
bool invalid;
for(int i=0; i<count_tr; i++){
for(int i=0; i<count_tr[bi]; i++){
for(int j=0; j<count_det; j++){
dist[j*count_tr+i] = pow((tracks[i*2] - dets[j*2]), 2) +
dist[j*count_tr[bi]+i] = pow((tracks[i*2] - dets[j*2]), 2) +
pow((tracks[i*2+1] - dets[j*2+1]), 2);
invalid = dist[j*count_tr+i] > track_size[i] || dist[j*count_tr+i] > item_size[j] || item_cl[j] != track_cl[i];
dist[j*count_tr+i] = dist[j*count_tr+i] + invalid * (1 << 18);
invalid = dist[j*count_tr[bi]+i] > track_size[i] || dist[j*count_tr[bi]+i] > item_size[j] || item_cl[j] != track_cl[i];
dist[j*count_tr[bi]+i] = dist[j*count_tr[bi]+i] + invalid * (1 << 18);
}
}
int matched_indices[2*count_tr];
int matched_indices[2*count_tr[bi]];
float min_tr;
int min_idtr=-1;
for(int i=0; i<count_tr; i++) {
for(int i=0; i<count_tr[bi]; i++) {
matched_indices[i*2] = -1;
matched_indices[i*2+1] = -1;
}
for(int i=0; i<count_det; i++){
min_tr=(1 << 18);
for(int j=0; j<count_tr; j++){
if(dist[i*count_tr+j]<min_tr) {
min_tr = dist[i*count_tr+j];
for(int j=0; j<count_tr[bi]; j++){
if(dist[i*count_tr[bi]+j]<min_tr) {
min_tr = dist[i*count_tr[bi]+j];
min_idtr = j;
}
}
if(min_tr < (1<<16)) {
for(int j=0; j<count_det; j++){
dist[j*count_tr+min_idtr] = (1 << 18);
dist[j*count_tr[bi]+min_idtr] = (1 << 18);
}
matched_indices[2*min_idtr] = min_idtr;
matched_indices[2*min_idtr+1] = i;
@@ -474,10 +478,10 @@ void CenternetDetection3DTrack::tracking(){
bool unmatched_dets[count_det];
for(int i=0; i<count_det; i++)
unmatched_dets[i] = false;
bool unmatched_tracks[count_tr];
for(int i=0; i<count_tr; i++)
bool unmatched_tracks[count_tr[bi]];
for(int i=0; i<count_tr[bi]; i++)
unmatched_tracks[i] = false;
for(int i=0; i<count_tr; i++) {
for(int i=0; i<count_tr[bi]; i++) {
if(matched_indices[2*i] != -1)
unmatched_tracks[matched_indices[2*i]]=true;
@@ -486,84 +490,84 @@ void CenternetDetection3DTrack::tracking(){
}
//match
for(int i=0; i<count_tr; i++) {
for(int i=0; i<count_tr[bi]; i++) {
if(matched_indices[2*i+1] != -1 && matched_indices[2*i] != -1) { //second condition is optional
int tr_id = matched_indices[2*i];
int d_id = matched_indices[2*i+1];
// tr_res[tr_id].det_res = det_res[d_id];
tr_res[tr_id].det_res.score = det_res[d_id].score;
tr_res[tr_id].det_res.cl = det_res[d_id].cl;
tr_res[tr_id].det_res.ct = det_res[d_id].ct;
tr_res[tr_id].det_res.tr = det_res[d_id].tr;
tr_res[tr_id].det_res.bb0 = det_res[d_id].bb0;
tr_res[tr_id].det_res.bb1 = det_res[d_id].bb1;
tr_res[tr_id].det_res.dep = det_res[d_id].dep;
tr_res[tr_id].det_res.dim[0] = det_res[d_id].dim[0];
tr_res[tr_id].det_res.dim[1] = det_res[d_id].dim[1];
tr_res[tr_id].det_res.dim[2] = det_res[d_id].dim[2];
tr_res[tr_id].det_res.alpha = det_res[d_id].alpha;
tr_res[tr_id].det_res.x = det_res[d_id].x;
tr_res[tr_id].det_res.y = det_res[d_id].y;
tr_res[tr_id].det_res.z = det_res[d_id].z;
tr_res[tr_id].det_res.rot_y = det_res[d_id].rot_y;
// tr_res[matched_indices[2*i]].tracking_id = ; is the same
// tr_res[matched_indices[2*i]].color = ; is the same
tr_res[tr_id].age = 1;
tr_res[tr_id].active = tr_res[tr_id].active+1;
// tr_res[bi][tr_id].det_res = det_res[d_id];
tr_res[bi][tr_id].det_res.score = det_res[d_id].score;
tr_res[bi][tr_id].det_res.cl = det_res[d_id].cl;
tr_res[bi][tr_id].det_res.ct = det_res[d_id].ct;
tr_res[bi][tr_id].det_res.tr = det_res[d_id].tr;
tr_res[bi][tr_id].det_res.bb0 = det_res[d_id].bb0;
tr_res[bi][tr_id].det_res.bb1 = det_res[d_id].bb1;
tr_res[bi][tr_id].det_res.dep = det_res[d_id].dep;
tr_res[bi][tr_id].det_res.dim[0] = det_res[d_id].dim[0];
tr_res[bi][tr_id].det_res.dim[1] = det_res[d_id].dim[1];
tr_res[bi][tr_id].det_res.dim[2] = det_res[d_id].dim[2];
tr_res[bi][tr_id].det_res.alpha = det_res[d_id].alpha;
tr_res[bi][tr_id].det_res.x = det_res[d_id].x;
tr_res[bi][tr_id].det_res.y = det_res[d_id].y;
tr_res[bi][tr_id].det_res.z = det_res[d_id].z;
tr_res[bi][tr_id].det_res.rot_y = det_res[d_id].rot_y;
// tr_res[bi][matched_indices[2*i]].tracking_id = ; is the same
// tr_res[bi][matched_indices[2*i]].color = ; is the same
tr_res[bi][tr_id].age = 1;
tr_res[bi][tr_id].active = tr_res[bi][tr_id].active+1;
}
}
//delete target umatched track
int new_count_tr = 0;
for(int i=0; i<count_tr; i++) {
for(int i=0; i<count_tr[bi]; i++) {
if(unmatched_tracks[i])
new_count_tr++;
}
if(new_count_tr == 0 && count_tr != 0) { //reset
tr_res.clear();
count_tr = 0;
if(new_count_tr == 0 && count_tr[bi] != 0) { //reset
tr_res[bi].clear();
count_tr[bi] = 0;
}
int old_count_tr = count_tr;
if(count_tr != 0 && new_count_tr != count_tr) {
int old_count_tr = count_tr[bi];
if(count_tr[bi] != 0 && new_count_tr != count_tr[bi]) {
std::vector<struct trackingRes> new_tr_res;
int id_new_tr=0;
for(int i=0; i<count_tr; i++) {
for(int i=0; i<count_tr[bi]; i++) {
if(unmatched_tracks[i]) {
struct trackingRes new_tr_res_;
// new_tr_res_new_det_res.det_res = tr_res[i].det_res;
new_tr_res_.det_res.score = tr_res[i].det_res.score;
new_tr_res_.det_res.cl = tr_res[i].det_res.cl;
new_tr_res_.det_res.ct = tr_res[i].det_res.ct;
new_tr_res_.det_res.tr = tr_res[i].det_res.tr;
new_tr_res_.det_res.bb0 = tr_res[i].det_res.bb0;
new_tr_res_.det_res.bb1 = tr_res[i].det_res.bb1;
new_tr_res_.det_res.dep = tr_res[i].det_res.dep;
new_tr_res_.det_res.dim[0] = tr_res[i].det_res.dim[0];
new_tr_res_.det_res.dim[1] = tr_res[i].det_res.dim[1];
new_tr_res_.det_res.dim[2] = tr_res[i].det_res.dim[2];
new_tr_res_.det_res.alpha = tr_res[i].det_res.alpha;
new_tr_res_.det_res.x = tr_res[i].det_res.x;
new_tr_res_.det_res.y = tr_res[i].det_res.y;
new_tr_res_.det_res.z = tr_res[i].det_res.z;
new_tr_res_.det_res.rot_y = tr_res[i].det_res.rot_y;
new_tr_res_.tracking_id = tr_res[i].tracking_id;
new_tr_res_.age = tr_res[i].age;
new_tr_res_.active = tr_res[i].active;
new_tr_res_.color = tr_res[i].color;
// new_tr_res_new_det_res.det_res = tr_res[bi][i].det_res;
new_tr_res_.det_res.score = tr_res[bi][i].det_res.score;
new_tr_res_.det_res.cl = tr_res[bi][i].det_res.cl;
new_tr_res_.det_res.ct = tr_res[bi][i].det_res.ct;
new_tr_res_.det_res.tr = tr_res[bi][i].det_res.tr;
new_tr_res_.det_res.bb0 = tr_res[bi][i].det_res.bb0;
new_tr_res_.det_res.bb1 = tr_res[bi][i].det_res.bb1;
new_tr_res_.det_res.dep = tr_res[bi][i].det_res.dep;
new_tr_res_.det_res.dim[0] = tr_res[bi][i].det_res.dim[0];
new_tr_res_.det_res.dim[1] = tr_res[bi][i].det_res.dim[1];
new_tr_res_.det_res.dim[2] = tr_res[bi][i].det_res.dim[2];
new_tr_res_.det_res.alpha = tr_res[bi][i].det_res.alpha;
new_tr_res_.det_res.x = tr_res[bi][i].det_res.x;
new_tr_res_.det_res.y = tr_res[bi][i].det_res.y;
new_tr_res_.det_res.z = tr_res[bi][i].det_res.z;
new_tr_res_.det_res.rot_y = tr_res[bi][i].det_res.rot_y;
new_tr_res_.tracking_id = tr_res[bi][i].tracking_id;
new_tr_res_.age = tr_res[bi][i].age;
new_tr_res_.active = tr_res[bi][i].active;
new_tr_res_.color = tr_res[bi][i].color;
id_new_tr++;
new_tr_res.push_back(new_tr_res_);
}
}
if(count_tr) {
tr_res.clear();
if(count_tr[bi]) {
tr_res[bi].clear();
}
count_tr = new_count_tr;
tr_res=new_tr_res;
count_tr[bi] = new_count_tr;
tr_res[bi]=new_tr_res;
}
int count_tr_ = count_tr;
int count_tr_ = count_tr[bi];
for(int i=0; i<count_det; i++) {
if((!unmatched_dets[i]) && det_res[i].score > new_thresh) {
count_tr_ ++;
@@ -587,10 +591,10 @@ void CenternetDetection3DTrack::tracking(){
new_tr_res_.age = 1;
new_tr_res_.active = 1;
new_tr_res_.color = rand() % 256;
tr_res.push_back(new_tr_res_);
tr_res[bi].push_back(new_tr_res_);
}
}
count_tr = count_tr_;
count_tr[bi] = count_tr_;
if(track_id==1000)
track_id=0;
@@ -729,8 +733,8 @@ void CenternetDetection3DTrack::postprocess(const int bi, const bool mAP) {
}
// track step
tracking();
batchTracked.push_back(tr_res);
tracking(bi);
batchTracked.push_back(tr_res[bi]);
}
void CenternetDetection3DTrack::draw(std::vector<cv::Mat>& frames) {