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2b88308f
编写于
5月 04, 2022
作者:
F
Feng Ni
提交者:
GitHub
5月 04, 2022
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电子邮件补丁
差异文件
fix pphuman vis when nothing detected (#5858)
上级
8b0a2721
变更
4
显示空白变更内容
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并排
Showing
4 changed file
with
12 addition
and
11 deletion
+12
-11
configs/mot/bytetrack/README_cn.md
configs/mot/bytetrack/README_cn.md
+1
-1
deploy/pphuman/docs/mot.md
deploy/pphuman/docs/mot.md
+2
-2
deploy/pphuman/pipeline.py
deploy/pphuman/pipeline.py
+3
-2
deploy/pptracking/python/README.md
deploy/pptracking/python/README.md
+6
-6
未找到文件。
configs/mot/bytetrack/README_cn.md
浏览文件 @
2b88308f
...
...
@@ -86,7 +86,7 @@ CUDA_VISIBLE_DEVICES=0 python tools/export_model.py -c configs/mot/deepsort/reid
### 4. 用导出的模型基于Python去预测
```
bash
python deploy/pptracking/python/mot_sde_infer.py
--model_dir
=
output_inference/ppyoloe_crn_l_36e_640x640_mot17half/
--tracker_config
=
tracker_config.yml
--video_file
={
your video name
}
.mp4
--device
=
GPU
--scaled
=
True
--save_mot_txts
python deploy/pptracking/python/mot_sde_infer.py
--model_dir
=
output_inference/ppyoloe_crn_l_36e_640x640_mot17half/
--tracker_config
=
deploy/pptracking/python/
tracker_config.yml
--video_file
={
your video name
}
.mp4
--device
=
GPU
--scaled
=
True
--save_mot_txts
```
**注意:**
-
跟踪模型是对视频进行预测,不支持单张图的预测,默认保存跟踪结果可视化后的视频,可添加
`--save_mot_txts`
(对每个视频保存一个txt)或
`--save_mot_txt_per_img`
(对每张图片保存一个txt)表示保存跟踪结果的txt文件,或
`--save_images`
表示保存跟踪结果可视化图片。
...
...
deploy/pphuman/docs/mot.md
浏览文件 @
2b88308f
...
...
@@ -34,9 +34,9 @@ python deploy/pphuman/pipeline.py --config deploy/pphuman/config/infer_cfg.yml \
python
deploy
/
pphuman
/
pipeline
.
py
--
config
deploy
/
pphuman
/
config
/
infer_cfg
.
yml
\
--
video_file
=
test_video
.
mp4
\
--
device
=
gpu
\
--
model_dir
det
=
ppyoloe
/
--
do_entrance_counting
\
--
draw_center_traj
--
draw_center_traj
\
--
model_dir
det
=
ppyoloe
/
```
**注意:**
...
...
deploy/pphuman/pipeline.py
浏览文件 @
2b88308f
...
...
@@ -537,8 +537,9 @@ class PipePredictor(object):
self
.
pipe_timer
.
total_time
.
end
()
if
self
.
cfg
[
'visual'
]:
_
,
_
,
fps
=
self
.
pipe_timer
.
get_total_time
()
im
=
self
.
visualize_video
(
frame
,
mot_res
,
frame_id
,
fps
)
# visualize
im
=
self
.
visualize_video
(
frame
,
mot_res
,
frame_id
,
fps
,
entrance
,
records
,
center_traj
)
# visualize
writer
.
write
(
im
)
if
self
.
file_name
is
None
:
# use camera_id
cv2
.
imshow
(
'PPHuman'
,
im
)
...
...
deploy/pptracking/python/README.md
浏览文件 @
2b88308f
...
...
@@ -89,9 +89,9 @@ CUDA_VISIBLE_DEVICES=0 python tools/export_model.py -c configs/mot/deepsort/reid
wget https://bj.bcebos.com/v1/paddledet/data/mot/demo/mot17_demo.mp4
# 用导出的PPYOLOv2行人检测模型和PPLCNet ReID模型
python deploy/pptracking/python/mot_sde_infer.py
--model_dir
=
output_inference/ppyolov2_r50vd_dcn_365e_640x640_mot17half/
--reid_model_dir
=
output_inference/deepsort_pplcnet/
--tracker_config
=
tracker_config.yml
--video_file
=
mot17_demo.mp4
--device
=
GPU
--threshold
=
0.5
--save_mot_txts
--save_images
python deploy/pptracking/python/mot_sde_infer.py
--model_dir
=
output_inference/ppyolov2_r50vd_dcn_365e_640x640_mot17half/
--reid_model_dir
=
output_inference/deepsort_pplcnet/
--tracker_config
=
deploy/pptracking/python/
tracker_config.yml
--video_file
=
mot17_demo.mp4
--device
=
GPU
--threshold
=
0.5
--save_mot_txts
--save_images
# 或用导出的PPYOLOe行人检测模型和PPLCNet ReID模型
python deploy/pptracking/python/mot_sde_infer.py
--model_dir
=
output_inference/ppyoloe_crn_l_36e_640x640_mot17half/
--reid_model_dir
=
output_inference/deepsort_pplcnet/
--tracker_config
=
tracker_config.yml
--video_file
=
mot17_demo.mp4
--device
=
GPU
--threshold
=
0.5
--save_mot_txts
--save_images
python deploy/pptracking/python/mot_sde_infer.py
--model_dir
=
output_inference/ppyoloe_crn_l_36e_640x640_mot17half/
--reid_model_dir
=
output_inference/deepsort_pplcnet/
--tracker_config
=
deploy/pptracking/python/
tracker_config.yml
--video_file
=
mot17_demo.mp4
--device
=
GPU
--threshold
=
0.5
--save_mot_txts
--save_images
```
### 2.3 用导出的模型基于Python去预测车辆跟踪
...
...
@@ -108,10 +108,10 @@ wget https://paddledet.bj.bcebos.com/models/mot/deepsort/deepsort_pplcnet_vehicl
tar
-xvf
deepsort_pplcnet_vehicle.tar
# 用导出的PicoDet车辆检测模型和PPLCNet车辆ReID模型
python deploy/pptracking/python/mot_sde_infer.py
--model_dir
=
picodet_l_640_aic21mtmct_vehicle/
--reid_model_dir
=
deepsort_pplcnet_vehicle/
--tracker_config
=
tracker_config.yml
--device
=
GPU
--threshold
=
0.5
--video_file
={
your video
}
.mp4
--save_mot_txts
--save_images
python deploy/pptracking/python/mot_sde_infer.py
--model_dir
=
picodet_l_640_aic21mtmct_vehicle/
--reid_model_dir
=
deepsort_pplcnet_vehicle/
--tracker_config
=
deploy/pptracking/python/
tracker_config.yml
--device
=
GPU
--threshold
=
0.5
--video_file
={
your video
}
.mp4
--save_mot_txts
--save_images
# 用导出的PP-YOLOv2车辆检测模型和PPLCNet车辆ReID模型
python deploy/pptracking/python/mot_sde_infer.py
--model_dir
=
ppyolov2_r50vd_dcn_365e_aic21mtmct_vehicle/
--reid_model_dir
=
deepsort_pplcnet_vehicle/
--tracker_config
=
tracker_config.yml
--device
=
GPU
--threshold
=
0.5
--video_file
={
your video
}
.mp4
--save_mot_txts
--save_images
python deploy/pptracking/python/mot_sde_infer.py
--model_dir
=
ppyolov2_r50vd_dcn_365e_aic21mtmct_vehicle/
--reid_model_dir
=
deepsort_pplcnet_vehicle/
--tracker_config
=
deploy/pptracking/python/
tracker_config.yml
--device
=
GPU
--threshold
=
0.5
--video_file
={
your video
}
.mp4
--save_mot_txts
--save_images
```
**注意:**
...
...
@@ -135,10 +135,10 @@ CUDA_VISIBLE_DEVICES=0 python tools/export_model.py -c configs/mot/deepsort/dete
wget https://bj.bcebos.com/v1/paddledet/data/mot/demo/mot17_demo.mp4
# 用导出的PPYOLOe行人检测模型
python deploy/pptracking/python/mot_sde_infer.py
--model_dir
=
output_inference/ppyoloe_crn_l_36e_640x640_mot17half/
--tracker_config
=
tracker_config.yml
--video_file
=
mot17_demo.mp4
--device
=
GPU
--threshold
=
0.5
--save_mot_txts
--save_images
python deploy/pptracking/python/mot_sde_infer.py
--model_dir
=
output_inference/ppyoloe_crn_l_36e_640x640_mot17half/
--tracker_config
=
deploy/pptracking/python/
tracker_config.yml
--video_file
=
mot17_demo.mp4
--device
=
GPU
--threshold
=
0.5
--save_mot_txts
--save_images
# 用导出的PPYOLOe行人检测模型和PPLCNet ReID模型
python deploy/pptracking/python/mot_sde_infer.py
--model_dir
=
output_inference/ppyoloe_crn_l_36e_640x640_mot17half/
--reid_model_dir
=
output_inference/deepsort_pplcnet/
--tracker_config
=
tracker_config.yml
--video_file
=
mot17_demo.mp4
--device
=
GPU
--threshold
=
0.5
--save_mot_txts
--save_images
python deploy/pptracking/python/mot_sde_infer.py
--model_dir
=
output_inference/ppyoloe_crn_l_36e_640x640_mot17half/
--reid_model_dir
=
output_inference/deepsort_pplcnet/
--tracker_config
=
deploy/pptracking/python/
tracker_config.yml
--video_file
=
mot17_demo.mp4
--device
=
GPU
--threshold
=
0.5
--save_mot_txts
--save_images
```
**注意:**
-
ByteTrack模型是加载导出的检测器和单独配置的
`--tracker_config`
文件运行的,为了实时跟踪所以不需要reid模型,
`--reid_model_dir`
表示reid导出模型的路径,默认为空,加不加具体视效果而定;
...
...
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