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[Model] add tracking trail on vis_mot (#461)

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* add override mark

* delete some

* recovery

* recovery

* add tracking

* add tracking py_bind and example

* add pptracking

* add pptracking

* iomanip head file

* add opencv_video lib

* add python libs package

Signed-off-by: ChaoII <849453582@qq.com>

* complete comments

Signed-off-by: ChaoII <849453582@qq.com>

* add jdeTracker_ member variable

Signed-off-by: ChaoII <849453582@qq.com>

* add 'FASTDEPLOY_DECL' macro

Signed-off-by: ChaoII <849453582@qq.com>

* remove kwargs params

Signed-off-by: ChaoII <849453582@qq.com>

* [Doc]update pptracking docs

* delete 'ENABLE_PADDLE_FRONTEND' switch

* add pptracking unit test

* update pptracking unit test

Signed-off-by: ChaoII <849453582@qq.com>

* modify test video file path and remove trt test

* update unit test model url

* remove 'FASTDEPLOY_DECL' macro

Signed-off-by: ChaoII <849453582@qq.com>

* fix build python packages about pptracking on win32

Signed-off-by: ChaoII <849453582@qq.com>

* update comment

Signed-off-by: ChaoII <849453582@qq.com>

* add pptracking model explain

Signed-off-by: ChaoII <849453582@qq.com>

* add tracking trail on vis_mot

* add tracking trail

* modify code for  some suggestion

* remove unused import

* fix import bug

Signed-off-by: ChaoII <849453582@qq.com>
Co-authored-by: Jason <jiangjiajun@baidu.com>
This commit is contained in:
ChaoII
2022-11-03 09:57:07 +08:00
committed by GitHub
parent 328212f270
commit 22d60fdadf
16 changed files with 208 additions and 116 deletions
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54
examples/vision/tracking/pptracking/cpp/infer.cc
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@@ -33,25 +33,29 @@ void CpuInfer(const std::string& model_dir, const std::string& video_file) {
}
fastdeploy::vision::MOTResult result;
fastdeploy::vision::tracking::TrailRecorder recorder;
// during each prediction, data is inserted into the recorder. As the number of predictions increases,
// the memory will continue to grow. You can cancel the insertion through 'UnbindRecorder'.
// int count = 0; // unbind condition
model.BindRecorder(&recorder);
cv::Mat frame;
int frame_id=0;
cv::VideoCapture capture(video_file);
// according to the time of prediction to calculate fps
float fps= 0.0f;
while (capture.read(frame)) {
if (frame.empty()) {
break;
break;
}
if (!model.Predict(&frame, &result)) {
std::cerr << "Failed to predict." << std::endl;
return;
std::cerr << "Failed to predict." << std::endl;
return;
}
// such as adding this code can cancel trail datat bind
// if(count++ == 10) model.UnbindRecorder();
// std::cout << result.Str() << std::endl;
cv::Mat out_img = fastdeploy::vision::VisMOT(frame, result, fps , frame_id);
cv::Mat out_img = fastdeploy::vision::VisMOT(frame, result, 0.0, &recorder);
cv::imshow("mot",out_img);
cv::waitKey(30);
frame_id++;
}
model.UnbindRecorder();
capture.release();
cv::destroyAllWindows();
}
@@ -72,25 +76,29 @@ void GpuInfer(const std::string& model_dir, const std::string& video_file) {
}
fastdeploy::vision::MOTResult result;
fastdeploy::vision::tracking::TrailRecorder trail_recorder;
// during each prediction, data is inserted into the recorder. As the number of predictions increases,
// the memory will continue to grow. You can cancel the insertion through 'UnbindRecorder'.
// int count = 0; // unbind condition
model.BindRecorder(&trail_recorder);
cv::Mat frame;
int frame_id=0;
cv::VideoCapture capture(video_file);
// according to the time of prediction to calculate fps
float fps= 0.0f;
while (capture.read(frame)) {
if (frame.empty()) {
break;
break;
}
if (!model.Predict(&frame, &result)) {
std::cerr << "Failed to predict." << std::endl;
return;
std::cerr << "Failed to predict." << std::endl;
return;
}
// such as adding this code can cancel trail datat bind
//if(count++ == 10) model.UnbindRecorder();
// std::cout << result.Str() << std::endl;
cv::Mat out_img = fastdeploy::vision::VisMOT(frame, result, fps , frame_id);
cv::Mat out_img = fastdeploy::vision::VisMOT(frame, result, 0.0, &trail_recorder);
cv::imshow("mot",out_img);
cv::waitKey(30);
frame_id++;
}
model.UnbindRecorder();
capture.release();
cv::destroyAllWindows();
}
@@ -112,11 +120,13 @@ void TrtInfer(const std::string& model_dir, const std::string& video_file) {
}
fastdeploy::vision::MOTResult result;
fastdeploy::vision::tracking::TrailRecorder recorder;
//during each prediction, data is inserted into the recorder. As the number of predictions increases,
//the memory will continue to grow. You can cancel the insertion through 'UnbindRecorder'.
// int count = 0; // unbind condition
model.BindRecorder(&recorder);
cv::Mat frame;
int frame_id=0;
cv::VideoCapture capture(video_file);
// according to the time of prediction to calculate fps
float fps= 0.0f;
while (capture.read(frame)) {
if (frame.empty()) {
break;
@@ -125,12 +135,14 @@ void TrtInfer(const std::string& model_dir, const std::string& video_file) {
std::cerr << "Failed to predict." << std::endl;
return;
}
// such as adding this code can cancel trail datat bind
// if(count++ == 10) model.UnbindRecorder();
// std::cout << result.Str() << std::endl;
cv::Mat out_img = fastdeploy::vision::VisMOT(frame, result, fps , frame_id);
cv::Mat out_img = fastdeploy::vision::VisMOT(frame, result, 0.0, &recorder);
cv::imshow("mot",out_img);
cv::waitKey(30);
frame_id++;
}
model.UnbindRecorder();
capture.release();
cv::destroyAllWindows();
}