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PaddleDetection
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9378909c
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PaddleDetection
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9378909c
编写于
11月 06, 2021
作者:
W
wangguanzhong
提交者:
GitHub
11月 06, 2021
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电子邮件补丁
差异文件
[MOT] Add stream input (#4489)
* add stream input * add stream input & add save_result
上级
b2f3ad7c
变更
6
隐藏空白更改
内联
并排
Showing
6 changed file
with
186 addition
and
50 deletion
+186
-50
deploy/pptracking/CMakeLists.txt
deploy/pptracking/CMakeLists.txt
+1
-1
deploy/pptracking/include/pipeline.h
deploy/pptracking/include/pipeline.h
+25
-10
deploy/pptracking/include/postprocess.h
deploy/pptracking/include/postprocess.h
+1
-1
deploy/pptracking/src/main.cc
deploy/pptracking/src/main.cc
+9
-5
deploy/pptracking/src/pipeline.cc
deploy/pptracking/src/pipeline.cc
+126
-30
deploy/pptracking/src/postprocess.cc
deploy/pptracking/src/postprocess.cc
+24
-3
未找到文件。
deploy/pptracking/CMakeLists.txt
浏览文件 @
9378909c
...
@@ -19,7 +19,7 @@ include_directories("${CMAKE_SOURCE_DIR}/")
...
@@ -19,7 +19,7 @@ include_directories("${CMAKE_SOURCE_DIR}/")
include_directories
(
"
${
CMAKE_CURRENT_BINARY_DIR
}
/ext/yaml-cpp/src/ext-yaml-cpp/include"
)
include_directories
(
"
${
CMAKE_CURRENT_BINARY_DIR
}
/ext/yaml-cpp/src/ext-yaml-cpp/include"
)
link_directories
(
"
${
CMAKE_CURRENT_BINARY_DIR
}
/ext/yaml-cpp/lib"
)
link_directories
(
"
${
CMAKE_CURRENT_BINARY_DIR
}
/ext/yaml-cpp/lib"
)
set
(
SRCS src/main.cc src/preprocess_op.cc src/pipeline.cc src/
predictor.cc src/
jde_predictor.cc src/sde_predictor.cc src/tracker.cc src/trajectory.cc src/lapjv.cpp src/base_predictor.cc src/postprocess.cc
)
set
(
SRCS src/main.cc src/preprocess_op.cc src/pipeline.cc src/jde_predictor.cc src/sde_predictor.cc src/tracker.cc src/trajectory.cc src/lapjv.cpp src/base_predictor.cc src/postprocess.cc
)
macro
(
safe_set_static_flag
)
macro
(
safe_set_static_flag
)
foreach
(
flag_var
foreach
(
flag_var
...
...
deploy/pptracking/include/pipeline.h
浏览文件 @
9378909c
...
@@ -31,7 +31,8 @@
...
@@ -31,7 +31,8 @@
#include <sys/stat.h>
#include <sys/stat.h>
#endif
#endif
#include "include/predictor.h"
#include "include/jde_predictor.h"
#include "include/sde_predictor.h"
namespace
PaddleDetection
{
namespace
PaddleDetection
{
...
@@ -46,7 +47,10 @@ class Pipeline {
...
@@ -46,7 +47,10 @@ class Pipeline {
const
int
cpu_threads
=
1
,
const
int
cpu_threads
=
1
,
const
bool
trt_calib_mode
=
false
,
const
bool
trt_calib_mode
=
false
,
const
bool
count
=
false
,
const
bool
count
=
false
,
const
bool
save_result
=
false
)
{
const
bool
save_result
=
false
,
const
std
::
string
&
scene
=
"pedestrian"
,
const
bool
tiny_obj
=
false
,
const
bool
is_mtmct
=
false
)
{
std
::
vector
<
std
::
string
>
input
;
std
::
vector
<
std
::
string
>
input
;
this
->
input_
=
input
;
this
->
input_
=
input
;
this
->
device_
=
device
;
this
->
device_
=
device
;
...
@@ -59,34 +63,45 @@ class Pipeline {
...
@@ -59,34 +63,45 @@ class Pipeline {
this
->
trt_calib_mode_
=
trt_calib_mode
;
this
->
trt_calib_mode_
=
trt_calib_mode
;
this
->
count_
=
count
;
this
->
count_
=
count
;
this
->
save_result_
=
save_result
;
this
->
save_result_
=
save_result
;
SelectModel
(
scene
,
tiny_obj
,
is_mtmct
);
InitPredictor
();
}
}
// Select model according to scenes, it must execute before Run()
void
SelectModel
(
const
std
::
string
&
scene
=
"pedestrian"
,
const
bool
tiny_obj
=
false
,
const
bool
is_mct
=
false
);
// Set input, it must execute before Run()
// Set input, it must execute before Run()
void
SetInput
(
std
::
string
&
input_video
);
void
SetInput
(
std
::
string
&
input_video
);
void
ClearInput
();
// Run pipeline
// Run pipeline
in video
void
Run
();
void
Run
();
void
PredictMOT
(
const
std
::
string
&
video_path
);
void
PredictMTMCT
(
const
std
::
vector
<
std
::
string
>
video_inputs
);
void
PredictSCT
(
const
std
::
string
&
video_path
);
// Run pipeline in stream
void
PredictMCT
(
const
std
::
vector
<
std
::
string
>
video_inputs
);
void
RunMOTStream
(
const
cv
::
Mat
img
,
const
int
frame_id
,
cv
::
Mat
out_img
,
std
::
vector
<
std
::
string
>&
records
,
std
::
vector
<
int
>&
count_list
,
std
::
vector
<
int
>&
in_count_list
,
std
::
vector
<
int
>&
out_count_list
);
void
RunMTMCTStream
(
const
std
::
vector
<
cv
::
Mat
>
imgs
,
std
::
vector
<
std
::
string
>&
records
);
void
PrintBenchmarkLog
(
std
::
vector
<
double
>
det_time
,
int
img_num
);
void
PrintBenchmarkLog
(
std
::
vector
<
double
>
det_time
,
int
img_num
);
private:
private:
// Select model according to scenes, it must execute before Run()
void
SelectModel
(
const
std
::
string
&
scene
=
"pedestrian"
,
const
bool
tiny_obj
=
false
,
const
bool
is_mtmct
=
false
);
void
InitPredictor
();
std
::
shared_ptr
<
PaddleDetection
::
JDEPredictor
>
jde_sct_
;
std
::
shared_ptr
<
PaddleDetection
::
SDEPredictor
>
sde_sct_
;
std
::
vector
<
std
::
string
>
input_
;
std
::
vector
<
std
::
string
>
input_
;
std
::
vector
<
cv
::
Mat
>
stream_
;
std
::
string
device_
;
std
::
string
device_
;
double
threshold_
;
double
threshold_
;
std
::
string
output_dir_
;
std
::
string
output_dir_
;
std
::
string
track_model_dir_
;
std
::
string
track_model_dir_
;
std
::
string
det_model_dir_
;
std
::
string
det_model_dir_
;
std
::
string
reid_model_dir_
;
std
::
string
reid_model_dir_
;
std
::
string
mct_model_dir_
;
std
::
string
run_mode_
=
"fluid"
;
std
::
string
run_mode_
=
"fluid"
;
int
gpu_id_
=
0
;
int
gpu_id_
=
0
;
bool
use_mkldnn_
=
false
;
bool
use_mkldnn_
=
false
;
...
...
deploy/pptracking/include/postprocess.h
浏览文件 @
9378909c
...
@@ -43,6 +43,6 @@ void FlowStatistic(const MOTResult& results, const int frame_id,
...
@@ -43,6 +43,6 @@ void FlowStatistic(const MOTResult& results, const int frame_id,
std
::
vector
<
int
>*
out_count_list
);
std
::
vector
<
int
>*
out_count_list
);
// Save Tracking Results
// Save Tracking Results
void
Save
Result
(
const
MOTResult
&
results
,
const
std
::
string
&
output_dir
);
void
Save
MOTResult
(
const
MOTResult
&
results
,
const
int
frame_id
,
std
::
vector
<
std
::
string
>&
records
);
}
// namespace PaddleDetection
}
// namespace PaddleDetection
deploy/pptracking/src/main.cc
浏览文件 @
9378909c
...
@@ -36,7 +36,7 @@
...
@@ -36,7 +36,7 @@
DEFINE_string
(
video_file
,
""
,
"Path of input video."
);
DEFINE_string
(
video_file
,
""
,
"Path of input video."
);
DEFINE_string
(
video_other_file
,
""
,
"Path of other input video used for MCT."
);
DEFINE_string
(
video_other_file
,
""
,
"Path of other input video used for M
TM
CT."
);
DEFINE_string
(
device
,
"CPU"
,
"Choose the device you want to run, it can be: CPU/GPU/XPU, default is CPU."
);
DEFINE_string
(
device
,
"CPU"
,
"Choose the device you want to run, it can be: CPU/GPU/XPU, default is CPU."
);
DEFINE_double
(
threshold
,
0.5
,
"Threshold of score."
);
DEFINE_double
(
threshold
,
0.5
,
"Threshold of score."
);
DEFINE_string
(
output_dir
,
"output"
,
"Directory of output visualization files."
);
DEFINE_string
(
output_dir
,
"output"
,
"Directory of output visualization files."
);
...
@@ -49,7 +49,7 @@ DEFINE_bool(tiny_obj, false, "Whether tracking tiny object");
...
@@ -49,7 +49,7 @@ DEFINE_bool(tiny_obj, false, "Whether tracking tiny object");
DEFINE_bool
(
count
,
false
,
"Whether counting after tracking"
);
DEFINE_bool
(
count
,
false
,
"Whether counting after tracking"
);
DEFINE_bool
(
save_result
,
false
,
"Whether saving result after tracking"
);
DEFINE_bool
(
save_result
,
false
,
"Whether saving result after tracking"
);
DEFINE_string
(
scene
,
""
,
"scene of tracking system, it can be : pedestrian/vehicle/multiclass"
);
DEFINE_string
(
scene
,
""
,
"scene of tracking system, it can be : pedestrian/vehicle/multiclass"
);
DEFINE_bool
(
is_m
ct
,
false
,
"Whether use
multi-camera tracking"
);
DEFINE_bool
(
is_m
tmct
,
false
,
"Whether use multi-target
multi-camera tracking"
);
static
std
::
string
DirName
(
const
std
::
string
&
filepath
)
{
static
std
::
string
DirName
(
const
std
::
string
&
filepath
)
{
auto
pos
=
filepath
.
rfind
(
OS_PATH_SEP
);
auto
pos
=
filepath
.
rfind
(
OS_PATH_SEP
);
...
@@ -112,13 +112,17 @@ int main(int argc, char** argv) {
...
@@ -112,13 +112,17 @@ int main(int argc, char** argv) {
return
-
1
;
return
-
1
;
}
}
if
(
!
PathExists
(
FLAGS_output_dir
))
{
MkDirs
(
FLAGS_output_dir
);
}
PaddleDetection
::
Pipeline
pipeline
(
PaddleDetection
::
Pipeline
pipeline
(
FLAGS_device
,
FLAGS_threshold
,
FLAGS_device
,
FLAGS_threshold
,
FLAGS_output_dir
,
FLAGS_run_mode
,
FLAGS_gpu_id
,
FLAGS_output_dir
,
FLAGS_run_mode
,
FLAGS_gpu_id
,
FLAGS_use_mkldnn
,
FLAGS_cpu_threads
,
FLAGS_use_mkldnn
,
FLAGS_cpu_threads
,
FLAGS_trt_calib_mode
,
FLAGS_count
,
FLAGS_save_result
);
FLAGS_count
,
FLAGS_save_result
,
FLAGS_scene
,
FLAGS_tiny_obj
,
FLAGS_is_mtmct
);
pipeline
.
SelectModel
(
FLAGS_scene
,
FLAGS_tiny_obj
,
FLAGS_is_mct
);
pipeline
.
SetInput
(
FLAGS_video_file
);
pipeline
.
SetInput
(
FLAGS_video_file
);
if
(
!
FLAGS_video_other_file
.
empty
())
{
if
(
!
FLAGS_video_other_file
.
empty
())
{
pipeline
.
SetInput
(
FLAGS_video_other_file
);
pipeline
.
SetInput
(
FLAGS_video_other_file
);
...
...
deploy/pptracking/src/pipeline.cc
浏览文件 @
9378909c
...
@@ -29,34 +29,64 @@ void Pipeline::SetInput(std::string& input_video) {
...
@@ -29,34 +29,64 @@ void Pipeline::SetInput(std::string& input_video) {
input_
.
push_back
(
input_video
);
input_
.
push_back
(
input_video
);
}
}
void
Pipeline
::
ClearInput
()
{
input_
.
clear
();
stream_
.
clear
();
}
void
Pipeline
::
SelectModel
(
const
std
::
string
&
scene
,
void
Pipeline
::
SelectModel
(
const
std
::
string
&
scene
,
const
bool
tiny_obj
,
const
bool
tiny_obj
,
const
bool
is_mct
)
{
const
bool
is_mtmct
)
{
// Single camera model
// Single camera model, based on FairMot
// use deepsort for multiclass tracking
// use fairmot for single class tracking
if
(
scene
==
"pedestrian"
)
{
if
(
scene
==
"pedestrian"
)
{
if
(
tiny_obj
)
{
track_model_dir_
=
"../pedestrian_track_tiny"
;
}
else
{
track_model_dir_
=
"../pedestrian_track"
;
track_model_dir_
=
"../pedestrian_track"
;
}
}
else
if
(
scene
!=
"vehicle"
)
{
}
else
if
(
scene
!=
"vehicle"
)
{
if
(
tiny_obj
)
{
track_model_dir_
=
"../vehicle_track_tiny"
;
}
else
{
track_model_dir_
=
"../vehicle_track"
;
track_model_dir_
=
"../vehicle_track"
;
}
}
else
if
(
scene
==
"multiclass"
)
{
}
else
if
(
scene
==
"multiclass"
)
{
det_model_dir_
=
"../multiclass_det"
;
if
(
tiny_obj
)
{
reid_model_dir_
=
"../multiclass_reid"
;
track_model_dir_
=
"../multiclass_track_tiny"
;
}
else
{
track_model_dir_
=
"../multiclass_track"
;
}
}
}
// Multi-camera model
// Multi-camera model, based on PicoDet & LCNet
if
(
is_mct
&&
scene
==
"pedestrian"
)
{
if
(
is_mtmct
&&
scene
==
"pedestrian"
)
{
mct_model_dir_
=
"../pedestrian_mct"
;
det_model_dir_
=
"../pedestrian_det"
;
}
else
if
(
is_mct
&&
scene
==
"vehicle"
)
{
reid_model_dir_
=
"../pedestrian_reid"
;
mct_model_dir_
=
"../vehicle_mct"
;
}
else
if
(
is_mtmct
&&
scene
==
"vehicle"
)
{
}
else
if
(
is_mct
&&
scene
==
"multiclass"
)
{
det_model_dir_
=
"../vehicle_det"
;
reid_model_dir_
=
"../vehicle_reid"
;
}
else
if
(
is_mtmct
&&
scene
==
"multiclass"
)
{
throw
"Multi-camera tracking is not supported in multiclass scene now."
;
throw
"Multi-camera tracking is not supported in multiclass scene now."
;
}
}
}
}
void
Pipeline
::
InitPredictor
()
{
if
(
track_model_dir_
.
empty
()
&&
det_model_dir_
.
empty
())
{
throw
"Predictor must receive track_model or det_model!"
;
}
if
(
!
track_model_dir_
.
empty
())
{
jde_sct_
=
std
::
make_shared
<
PaddleDetection
::
JDEPredictor
>
(
device_
,
track_model_dir_
,
threshold_
,
run_mode_
,
gpu_id_
,
use_mkldnn_
,
cpu_threads_
,
trt_calib_mode_
);
}
if
(
!
det_model_dir_
.
empty
())
{
sde_sct_
=
std
::
make_shared
<
PaddleDetection
::
SDEPredictor
>
(
device_
,
det_model_dir_
,
reid_model_dir_
,
threshold_
,
run_mode_
,
gpu_id_
,
use_mkldnn_
,
cpu_threads_
,
trt_calib_mode_
);
}
}
void
Pipeline
::
Run
()
{
void
Pipeline
::
Run
()
{
if
(
track_model_dir_
.
empty
())
{
if
(
track_model_dir_
.
empty
()
&&
det_model_dir_
.
empty
()
)
{
std
::
cout
<<
"Pipeline must use SelectModel before Run"
;
std
::
cout
<<
"Pipeline must use SelectModel before Run"
;
return
;
return
;
}
}
...
@@ -65,24 +95,24 @@ void Pipeline::Run() {
...
@@ -65,24 +95,24 @@ void Pipeline::Run() {
return
;
return
;
}
}
if
(
mct
_model_dir_
.
empty
())
{
if
(
!
track
_model_dir_
.
empty
())
{
// single camera
// single camera
if
(
input_
.
size
()
>
1
)
{
if
(
input_
.
size
()
>
1
)
{
throw
"Single camera tracking except single video, but received %d"
,
input_
.
size
();
throw
"Single camera tracking except single video, but received %d"
,
input_
.
size
();
}
}
Predict
SC
T
(
input_
[
0
]);
Predict
MO
T
(
input_
[
0
]);
}
else
{
}
else
{
// multi cameras
// multi cameras
if
(
input_
.
size
()
!=
2
)
{
if
(
input_
.
size
()
!=
2
)
{
throw
"Multi camera tracking except two videos, but received %d"
,
input_
.
size
();
throw
"Multi camera tracking except two videos, but received %d"
,
input_
.
size
();
}
}
PredictMCT
(
input_
);
PredictM
TM
CT
(
input_
);
}
}
}
}
void
Pipeline
::
PredictSCT
(
const
std
::
string
&
video_path
)
{
PaddleDetection
::
Predictor
sct
(
device_
,
track_model_dir_
,
det_model_dir_
,
reid_model_dir_
,
threshold_
,
run_mode_
,
gpu_id_
,
use_mkldnn_
,
cpu_threads_
,
trt_calib_mode_
);
void
Pipeline
::
PredictMOT
(
const
std
::
string
&
video_path
)
{
// Open video
// Open video
cv
::
VideoCapture
capture
;
cv
::
VideoCapture
capture
;
capture
.
open
(
video_path
.
c_str
());
capture
.
open
(
video_path
.
c_str
());
...
@@ -96,9 +126,14 @@ void Pipeline::PredictSCT(const std::string& video_path) {
...
@@ -96,9 +126,14 @@ void Pipeline::PredictSCT(const std::string& video_path) {
int
video_height
=
static_cast
<
int
>
(
capture
.
get
(
CV_CAP_PROP_FRAME_HEIGHT
));
int
video_height
=
static_cast
<
int
>
(
capture
.
get
(
CV_CAP_PROP_FRAME_HEIGHT
));
int
video_fps
=
static_cast
<
int
>
(
capture
.
get
(
CV_CAP_PROP_FPS
));
int
video_fps
=
static_cast
<
int
>
(
capture
.
get
(
CV_CAP_PROP_FPS
));
LOG
(
INFO
)
<<
"----------------------- Input info -----------------------"
;
LOG
(
INFO
)
<<
"video_width: "
<<
video_width
;
LOG
(
INFO
)
<<
"video_height: "
<<
video_height
;
LOG
(
INFO
)
<<
"input fps: "
<<
video_fps
;
// Create VideoWriter for output
// Create VideoWriter for output
cv
::
VideoWriter
video_out
;
cv
::
VideoWriter
video_out
;
std
::
string
video_out_path
=
"mot_output.mp4"
;
std
::
string
video_out_path
=
output_dir_
+
OS_PATH_SEP
+
"mot_output.mp4"
;
int
fcc
=
cv
::
VideoWriter
::
fourcc
(
'm'
,
'p'
,
'4'
,
'v'
);
int
fcc
=
cv
::
VideoWriter
::
fourcc
(
'm'
,
'p'
,
'4'
,
'v'
);
video_out
.
open
(
video_out_path
.
c_str
(),
video_out
.
open
(
video_out_path
.
c_str
(),
fcc
,
//0x00000021,
fcc
,
//0x00000021,
...
@@ -116,21 +151,30 @@ void Pipeline::PredictSCT(const std::string& video_path) {
...
@@ -116,21 +151,30 @@ void Pipeline::PredictSCT(const std::string& video_path) {
std
::
vector
<
int
>
in_count_list
;
std
::
vector
<
int
>
in_count_list
;
std
::
vector
<
int
>
out_count_list
;
std
::
vector
<
int
>
out_count_list
;
double
times
;
double
times
;
double
total_time
;
// Capture all frames and do inference
// Capture all frames and do inference
cv
::
Mat
frame
;
cv
::
Mat
frame
;
int
frame_id
=
0
;
int
frame_id
=
0
;
std
::
vector
<
std
::
string
>
records
;
records
.
push_back
(
"result format: frame_id, track_id, x1, y1, w, h
\n
"
);
LOG
(
INFO
)
<<
"------------------- Predict info ------------------------"
;
while
(
capture
.
read
(
frame
))
{
while
(
capture
.
read
(
frame
))
{
if
(
frame
.
empty
())
{
if
(
frame
.
empty
())
{
break
;
break
;
}
}
std
::
vector
<
cv
::
Mat
>
imgs
;
std
::
vector
<
cv
::
Mat
>
imgs
;
imgs
.
push_back
(
frame
);
imgs
.
push_back
(
frame
);
printf
(
"frame_id: %d
\n
"
,
frame_id
);
jde_sct_
->
Predict
(
imgs
,
threshold_
,
&
result
,
&
det_times
);
sct
.
Predict
(
imgs
,
threshold_
,
&
result
,
&
det_times
);
frame_id
+=
1
;
frame_id
+=
1
;
times
=
std
::
accumulate
(
det_times
.
begin
(),
det_times
.
end
(),
0
)
/
frame_id
;
total_time
=
std
::
accumulate
(
det_times
.
begin
(),
det_times
.
end
(),
0.
);
times
=
total_time
/
frame_id
;
LOG
(
INFO
)
<<
"frame_id: "
<<
frame_id
<<
" predict time(s): "
<<
total_time
/
1000
;
cv
::
Mat
out_im
=
PaddleDetection
::
VisualizeTrackResult
(
cv
::
Mat
out_im
g
=
PaddleDetection
::
VisualizeTrackResult
(
frame
,
result
,
1000.
/
times
,
frame_id
);
frame
,
result
,
1000.
/
times
,
frame_id
);
if
(
count_
)
{
if
(
count_
)
{
...
@@ -139,17 +183,69 @@ void Pipeline::PredictSCT(const std::string& video_path) {
...
@@ -139,17 +183,69 @@ void Pipeline::PredictSCT(const std::string& video_path) {
PaddleDetection
::
FlowStatistic
(
result
,
frame_id
,
&
count_list
,
&
in_count_list
,
&
out_count_list
);
PaddleDetection
::
FlowStatistic
(
result
,
frame_id
,
&
count_list
,
&
in_count_list
,
&
out_count_list
);
}
}
if
(
save_result_
)
{
if
(
save_result_
)
{
PaddleDetection
::
Save
Result
(
result
,
output_dir_
);
PaddleDetection
::
Save
MOTResult
(
result
,
frame_id
,
records
);
}
}
video_out
.
write
(
out_im
);
video_out
.
write
(
out_im
g
);
}
}
capture
.
release
();
capture
.
release
();
video_out
.
release
();
video_out
.
release
();
PrintBenchmarkLog
(
det_times
,
frame_id
);
PrintBenchmarkLog
(
det_times
,
frame_id
);
printf
(
"Visualized output saved as %s
\n
"
,
video_out_path
.
c_str
());
LOG
(
INFO
)
<<
"-------------------- Final Output info -------------------"
;
LOG
(
INFO
)
<<
"Total frame: "
<<
frame_id
;
LOG
(
INFO
)
<<
"Visualized output saved as "
<<
video_out_path
.
c_str
();
if
(
save_result_
)
{
FILE
*
fp
;
std
::
string
result_output_path
=
output_dir_
+
OS_PATH_SEP
+
"mot_output.txt"
;
if
((
fp
=
fopen
(
result_output_path
.
c_str
(),
"w+"
))
==
NULL
)
{
printf
(
"Open %s error.
\n
"
,
result_output_path
.
c_str
());
return
;
}
for
(
int
l
;
l
<
records
.
size
();
++
l
)
{
fprintf
(
fp
,
records
[
l
].
c_str
());
}
fclose
(
fp
);
LOG
(
INFO
)
<<
"txt result output saved as "
<<
result_output_path
.
c_str
();
}
}
void
Pipeline
::
PredictMTMCT
(
const
std
::
vector
<
std
::
string
>
video_path
)
{
throw
"Not Implement!"
;
}
void
Pipeline
::
RunMOTStream
(
const
cv
::
Mat
img
,
const
int
frame_id
,
cv
::
Mat
out_img
,
std
::
vector
<
std
::
string
>&
records
,
std
::
vector
<
int
>&
count_list
,
std
::
vector
<
int
>&
in_count_list
,
std
::
vector
<
int
>&
out_count_list
)
{
PaddleDetection
::
MOTResult
result
;
std
::
vector
<
double
>
det_times
(
3
);
double
times
;
double
total_time
;
LOG
(
INFO
)
<<
"------------------- Predict info ------------------------"
;
std
::
vector
<
cv
::
Mat
>
imgs
;
imgs
.
push_back
(
img
);
jde_sct_
->
Predict
(
imgs
,
threshold_
,
&
result
,
&
det_times
);
total_time
=
std
::
accumulate
(
det_times
.
begin
(),
det_times
.
end
(),
0.
);
times
=
total_time
/
frame_id
;
LOG
(
INFO
)
<<
"frame_id: "
<<
frame_id
<<
" predict time(s): "
<<
total_time
/
1000
;
out_img
=
PaddleDetection
::
VisualizeTrackResult
(
img
,
result
,
1000.
/
times
,
frame_id
);
if
(
count_
)
{
// Count total number
// Count in & out number
PaddleDetection
::
FlowStatistic
(
result
,
frame_id
,
&
count_list
,
&
in_count_list
,
&
out_count_list
);
}
PrintBenchmarkLog
(
det_times
,
frame_id
);
if
(
save_result_
)
{
PaddleDetection
::
SaveMOTResult
(
result
,
frame_id
,
records
);
}
}
}
void
Pipeline
::
PredictMCT
(
const
std
::
vector
<
std
::
string
>
video_path
)
{
void
Pipeline
::
RunMTMCTStream
(
const
std
::
vector
<
cv
::
Mat
>
imgs
,
std
::
vector
<
std
::
string
>&
records
)
{
throw
"Not Implement!"
;
throw
"Not Implement!"
;
}
}
...
@@ -171,8 +267,8 @@ void Pipeline::PrintBenchmarkLog(std::vector<double> det_time, int img_num){
...
@@ -171,8 +267,8 @@ void Pipeline::PrintBenchmarkLog(std::vector<double> det_time, int img_num){
LOG
(
INFO
)
<<
"cpu_math_library_num_threads: "
<<
cpu_threads_
;
LOG
(
INFO
)
<<
"cpu_math_library_num_threads: "
<<
cpu_threads_
;
LOG
(
INFO
)
<<
"----------------------- Perf info ------------------------"
;
LOG
(
INFO
)
<<
"----------------------- Perf info ------------------------"
;
LOG
(
INFO
)
<<
"Total number of predicted data: "
<<
img_num
LOG
(
INFO
)
<<
"Total number of predicted data: "
<<
img_num
<<
" and total time spent(
m
s): "
<<
" and total time spent(s): "
<<
std
::
accumulate
(
det_time
.
begin
(),
det_time
.
end
(),
0.
);
<<
std
::
accumulate
(
det_time
.
begin
(),
det_time
.
end
(),
0.
)
/
1000
;
img_num
=
std
::
max
(
1
,
img_num
);
img_num
=
std
::
max
(
1
,
img_num
);
LOG
(
INFO
)
<<
"preproce_time(ms): "
<<
det_time
[
0
]
/
img_num
LOG
(
INFO
)
<<
"preproce_time(ms): "
<<
det_time
[
0
]
/
img_num
<<
", inference_time(ms): "
<<
det_time
[
1
]
/
img_num
<<
", inference_time(ms): "
<<
det_time
[
1
]
/
img_num
...
...
deploy/pptracking/src/postprocess.cc
浏览文件 @
9378909c
...
@@ -104,9 +104,30 @@ void FlowStatistic(const MOTResult& results, const int frame_id,
...
@@ -104,9 +104,30 @@ void FlowStatistic(const MOTResult& results, const int frame_id,
throw
"Not Implement"
;
throw
"Not Implement"
;
}
}
void
SaveResult
(
const
MOTResult
&
results
,
const
std
::
string
&
output_dir
)
{
void
SaveMOTResult
(
const
MOTResult
&
results
,
const
int
frame_id
,
std
::
vector
<
std
::
string
>&
records
)
{
throw
"Not Implement"
;
// result format: frame_id, track_id, x1, y1, w, h
std
::
string
record
;
for
(
int
i
=
0
;
i
<
results
.
size
();
++
i
)
{
MOTTrack
mot_track
=
results
[
i
];
int
ids
=
mot_track
.
ids
;
float
score
=
mot_track
.
score
;
Rect
rects
=
mot_track
.
rects
;
float
x1
=
rects
.
left
;
float
y1
=
rects
.
top
;
float
x2
=
rects
.
right
;
float
y2
=
rects
.
bottom
;
float
w
=
x2
-
x1
;
float
h
=
y2
-
y1
;
if
(
w
==
0
||
h
==
0
)
{
continue
;
}
std
::
ostringstream
os
;
os
<<
frame_id
<<
" "
<<
ids
<<
""
<<
x1
<<
" "
<<
y1
<<
" "
<<
w
<<
" "
<<
h
<<
"
\n
"
;
record
=
os
.
str
();
records
.
push_back
(
record
);
}
}
}
}
// namespace PaddleDetection
}
// namespace PaddleDetection
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