fix formatting issues

This commit is contained in:
jario-jin 2023-08-17 15:44:18 +08:00
parent 8e1a62651d
commit 5867b339f4
5 changed files with 56 additions and 50 deletions

View File

@ -195,7 +195,7 @@ void SORT::update(TargetsInFrame& tgts)
tracklet.age = 0;
tracklet.hits = 1;
tracklet.misses = 0;
tracklet.frame_id=tgts.frame_id;
tracklet.frame_id = tgts.frame_id;
tracklet.tentative = true;
// initate the motion
pair<Matrix<double, 8, 1>, Matrix<double, 8, 8> > motion = kf.initiate(tracklet.bbox);
@ -245,13 +245,13 @@ void SORT::update(TargetsInFrame& tgts)
int detectionIndex = match.second;
if (trackletIndex >= 0 && detectionIndex >= 0)
{
if (iouMatrix[match.first][match.second] >= _iou_threshold)//iou_thrshold
if (iouMatrix[match.first][match.second] >= _iou_threshold) // iou_thrshold
{
sv::Box box;
tgts.targets[detectionIndex].getBox(box);
this->_tracklets[trackletIndex].age = 0;
this->_tracklets[trackletIndex].hits++;
this->_tracklets[trackletIndex].frame_id=tgts.frame_id;
this->_tracklets[trackletIndex].frame_id = tgts.frame_id;
this->_tracklets[trackletIndex].bbox << box.x1, box.y1, box.x2-box.x1, box.y2-box.y1;
auto[mean, covariance] = kf.update(this->_tracklets[trackletIndex].mean, this->_tracklets[trackletIndex].covariance, box);
@ -264,7 +264,7 @@ void SORT::update(TargetsInFrame& tgts)
}
}
// create new tracklets for unmatched detections
for (int i = 0; i < tgts.targets.size(); i++)
for (int i=0; i<tgts.targets.size(); i++)
{
if (match_det[i] == -1)
{
@ -277,7 +277,7 @@ void SORT::update(TargetsInFrame& tgts)
tracklet.age = 0;
tracklet.hits = 1;
tracklet.misses = 0;
tracklet.frame_id=tgts.frame_id;
tracklet.frame_id = tgts.frame_id;
tracklet.tentative = true;
auto[new_mean, new_covariance] = kf.initiate(tracklet.bbox);
@ -295,7 +295,7 @@ void SORT::update(TargetsInFrame& tgts)
{
tracklet.tentative = false;
}
if ((tgts.frame_id-tracklet.frame_id <= _max_age) || (!tracklet.tentative && tracklet.frame_id==tgts.frame_id))
if ((tgts.frame_id-tracklet.frame_id <= _max_age) || (!tracklet.tentative && tracklet.frame_id == tgts.frame_id))
{
_new_tracklets.push_back(tracklet);
}

View File

@ -51,11 +51,11 @@ struct Tracklet
/* data */
public:
Eigen::Vector4d bbox; // double x, y, w, h;
int id=0;
int id = 0;
int age;
int hits;
int misses;
int frame_id=0;
int frame_id = 0;
bool tentative;
std::vector<double> features;
Eigen::Matrix<double, 8, 1> mean;

View File

@ -9,12 +9,16 @@ using namespace cv;
//extract name
std::string GetImageFileName(const std::string& imagePath) {
size_t lastSlash = imagePath.find_last_of("/\\");
if (lastSlash == std::string::npos) {
if (lastSlash == std::string::npos)
{
return imagePath;
} else {
}
else
{
std::string fileName = imagePath.substr(lastSlash + 1);
size_t lastDot = fileName.find_last_of(".");
if (lastDot != std::string::npos) {
if (lastDot != std::string::npos)
{
return fileName.substr(0, lastDot);
}
return fileName;
@ -60,8 +64,8 @@ int main(int argc, char *argv[])
}
for (int i = 0; i < val_image.size(); i++) {
for (int i = 0; i < val_image.size(); i++)
{
//create pred file
std::string val_image_name = GetImageFileName(val_image[i]);
std::string filename = folder+"/"+ val_image_name + ".txt";
@ -86,7 +90,8 @@ int main(int argc, char *argv[])
{
sv::Box b;
tgts.targets[j].getBox(b);
file<<tgts.targets[j].category_id<<" "<<(float)(b.x1+b.x2)/(2*cols)<<" "<<(float)(b.y1+b.y2)/(2*rows)<<" "<<(float)(b.x2-b.x1)/cols<<" "<<(float)(b.y2-b.y1)/rows<<" "<<(float)tgts.targets[j].score<<"\n";
file << tgts.targets[j].category_id << " " << (float)(b.x1+b.x2) / (2*cols) << " " << (float)(b.y1+b.y2) / (2*rows) << \
" " << (float)(b.x2-b.x1) / cols << " " << (float)(b.y2-b.y1) / rows << " " << (float)tgts.targets[j].score << "\n";
}
file.close();
}

View File

@ -4,11 +4,11 @@ import os
import cv2
# revert prediction results to coco_json
path = os.path.abspath(os.path.join(os.getcwd(),"../../.."))
path = os.path.abspath(os.path.join(os.getcwd(), "../../.."))
# all files dir
images_path = path+'/val2017/val2017'
preds_path = path+'/val2017/preds'
images_path = path + '/val2017/val2017'
preds_path = path + '/val2017/preds'
coco_json_save ='pd_coco.json'
# config coco_json
@ -45,7 +45,8 @@ for image in images:
'image_id': int(image_name),
'category_id': int(category_id),
'bbox': [xmin, ymin, w, h],
'score': float(pred[5])})
'score': float(pred[5])
})
# save json
with open(os.path.join(coco_json_save), 'w') as f: