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1203276f
编写于
6月 09, 2021
作者:
L
LDOUBLEV
浏览文件
操作
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电子邮件补丁
差异文件
add env, add infer det imgs, add infer_gpu_id to params.txt
上级
04fb6148
变更
3
隐藏空白更改
内联
并排
Showing
3 changed file
with
29 addition
and
20 deletion
+29
-20
test/infer.sh
test/infer.sh
+10
-7
test/params.txt
test/params.txt
+1
-1
test/test.sh
test/test.sh
+18
-12
未找到文件。
test/infer.sh
浏览文件 @
1203276f
...
...
@@ -14,8 +14,6 @@ function func_parser(){
IFS
=
$'
\n
'
# The training params
train_model_list
=
$(
func_parser
"
${
lines
[0]
}
"
)
gpu_list
=
$(
func_parser
"
${
lines
[1]
}
"
)
auto_cast_list
=
$(
func_parser
"
${
lines
[2]
}
"
)
slim_trainer_list
=
$(
func_parser
"
${
lines
[3]
}
"
)
python
=
$(
func_parser
"
${
lines
[4]
}
"
)
# inference params
...
...
@@ -27,13 +25,15 @@ rec_batch_size_list=$(func_parser "${lines[9]}")
gpu_trt_list
=
$(
func_parser
"
${
lines
[10]
}
"
)
gpu_precision_list
=
$(
func_parser
"
${
lines
[11]
}
"
)
infer_gpu_id
=
$(
func_parser
"
${
lines
[12]
}
"
)
log_path
=
$(
func_parser
"
${
lines
[13]
}
"
)
function
status_check
(){
last_status
=
$1
# the exit code
run_model
=
$2
run_command
=
$3
save_log
=
$4
echo
${
case3
}
if
[
$last_status
-eq
0
]
;
then
echo
-e
"
\0
33[33m
$run_model
successfully with command -
${
run_command
}
!
\0
33[0m"
|
tee
-a
${
save_log
}
else
...
...
@@ -45,11 +45,13 @@ for train_model in ${train_model_list[*]}; do
if
[
${
train_model
}
=
"det"
]
;
then
model_name
=
"det"
yml_file
=
"configs/det/det_mv3_db.yml"
img_dir
=
""
wget
-nc
-P
./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar
&&
tar
xf ./inference/ch_det_data_50.tar
img_dir
=
"./inference/ch_det_data_50/"
elif
[
${
train_model
}
=
"rec"
]
;
then
model_name
=
"rec"
yml_file
=
"configs/rec/rec_mv3_none_bilstm_ctc.yml"
img_dir
=
""
wget
-nc
-P
./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_rec_data_200.tar
&&
tar
xf ./inference/ch_rec_data_200.tar
img_dir
=
"./inference/ch_rec_data_200/"
fi
# eval
...
...
@@ -126,6 +128,7 @@ for train_model in ${train_model_list[*]}; do
done
done
else
env
=
"CUDA_VISIBLE_DEVICES=
${
infer_gpu_id
}
"
for
use_trt
in
${
gpu_trt_list
[*]
}
;
do
for
precision
in
${
gpu_precision_list
[*]
}
;
do
if
[
${
use_trt
}
=
"False"
]
&&
[
${
precision
}
!=
"fp32"
]
;
then
...
...
@@ -133,8 +136,8 @@ for train_model in ${train_model_list[*]}; do
fi
for
rec_batch_size
in
${
rec_batch_size_list
[*]
}
;
do
save_log_path
=
"
${
log_path
}
/
${
model_name
}
_
${
slim_trainer
}
_gpu_usetensorrt_
${
use_trt
}
_usefp16_
${
precision
}
_recbatchnum_
${
rec_batch_size
}
_infer.log"
command
=
"
${
python
}
${
inference
}
--use_gpu=True --use_tensorrt=
${
use_trt
}
--precision=
${
precision
}
--benchmark=True --det_model_dir=
${
log_path
}
/
${
eval_model_name
}
_infer --rec_batch_num=
${
rec_batch_size
}
--rec_model_dir=
${
rec_model_dir
}
--image_dir=
${
img_dir
}
--save_log_path=
${
save_log_path
}
"
${
python
}
${
inference
}
--use_gpu
=
True
--use_tensorrt
=
${
use_trt
}
--precision
=
${
precision
}
--benchmark
=
True
--det_model_dir
=
${
log_path
}
/
${
eval_model_name
}
_infer
--rec_batch_num
=
${
rec_batch_size
}
--rec_model_dir
=
${
rec_model_dir
}
--image_dir
=
${
img_dir
}
--save_log_path
=
${
save_log_path
}
command
=
"
${
env
}
${
python
}
${
inference
}
--use_gpu=True --use_tensorrt=
${
use_trt
}
--precision=
${
precision
}
--benchmark=True --det_model_dir=
${
log_path
}
/
${
eval_model_name
}
_infer --rec_batch_num=
${
rec_batch_size
}
--rec_model_dir=
${
rec_model_dir
}
--image_dir=
${
img_dir
}
--save_log_path=
${
save_log_path
}
"
${
env
}
${
python
}
${
inference
}
--use_gpu
=
True
--use_tensorrt
=
${
use_trt
}
--precision
=
${
precision
}
--benchmark
=
True
--det_model_dir
=
${
log_path
}
/
${
eval_model_name
}
_infer
--rec_batch_num
=
${
rec_batch_size
}
--rec_model_dir
=
${
rec_model_dir
}
--image_dir
=
${
img_dir
}
--save_log_path
=
${
save_log_path
}
status_check
$?
"
${
trainer
}
"
"
${
command
}
"
"
${
save_log_path
}
"
done
done
...
...
test/params.txt
浏览文件 @
1203276f
...
...
@@ -11,5 +11,5 @@ cpu_threads_list: 1|6
rec_batch_size_list: 1|6
gpu_trt_list: True|False
gpu_precision_list: fp32|fp16|int8
infer_gpu_id: 0
log_path: ./output
test/test.sh
浏览文件 @
1203276f
...
...
@@ -64,14 +64,13 @@ rec_batch_size_list=$(func_parser "${lines[9]}")
gpu_trt_list
=
$(
func_parser
"
${
lines
[10]
}
"
)
gpu_precision_list
=
$(
func_parser
"
${
lines
[11]
}
"
)
log_path
=
$(
func_parser
"
${
lines
[1
2
]
}
"
)
log_path
=
$(
func_parser
"
${
lines
[1
3
]
}
"
)
function
status_check
(){
last_status
=
$1
# the exit code
run_model
=
$2
run_command
=
$3
save_log
=
$4
echo
${
case3
}
if
[
$last_status
-eq
0
]
;
then
echo
-e
"
\0
33[33m
$run_model
successfully with command -
${
run_command
}
!
\0
33[0m"
|
tee
-a
${
save_log
}
else
...
...
@@ -97,10 +96,16 @@ for train_model in ${train_model_list[*]}; do
if
[
${
gpu
}
=
"-1"
]
;
then
lanuch
=
""
use_gpu
=
False
env
=
""
elif
[
${#
gpu
}
-le
1
]
;
then
launch
=
""
env
=
"CUDA_VISIBLE_DEVICES=
${
gpu
}
"
else
launch
=
"-m paddle.distributed.launch --log_dir=./debug/ --gpus
${
gpu
}
"
IFS
=
","
array
=(
${
gpu
}
)
env
=
"CUDA_VISIBLE_DEVICES=
${
array
[0]
}
"
IFS
=
"|"
fi
for
auto_cast
in
${
auto_cast_list
[*]
}
;
do
...
...
@@ -122,13 +127,13 @@ for train_model in ${train_model_list[*]}; do
export_model
=
"tools/export_model.py"
fi
save_log
=
${
log_path
}
/
${
model_name
}
_
${
slim_trainer
}
_autocast_
${
auto_cast
}
_gpuid_
${
gpu
}
command
=
"
${
python
}
${
launch
}
${
trainer
}
-c
${
yml_file
}
-o Global.epoch_num=
${
epoch
}
Global.eval_batch_step=
${
eval_batch_step
}
Global.auto_cast=
${
auto_cast
}
Global.save_model_dir=
${
save_log
}
Global.use_gpu=
${
use_gpu
}
"
echo
${
python
}
${
launch
}
${
trainer
}
-c
${
yml_file
}
-o
Global.epoch_num
=
${
epoch
}
Global.eval_batch_step
=
${
eval_batch_step
}
Global.auto_cast
=
${
auto_cast
}
Global.save_model_dir
=
${
save_log
}
Global.use_gpu
=
${
use_gpu
}
#
status_check $? "${trainer}" "${command}" "${save_log}/train.log"
command
=
"
${
env
}
${
python
}
${
launch
}
${
trainer
}
-c
${
yml_file
}
-o Global.epoch_num=
${
epoch
}
Global.eval_batch_step=
${
eval_batch_step
}
Global.auto_cast=
${
auto_cast
}
Global.save_model_dir=
${
save_log
}
Global.use_gpu=
${
use_gpu
}
"
${
env
}
${
python
}
${
launch
}
${
trainer
}
-c
${
yml_file
}
-o
Global.epoch_num
=
${
epoch
}
Global.eval_batch_step
=
${
eval_batch_step
}
Global.auto_cast
=
${
auto_cast
}
Global.save_model_dir
=
${
save_log
}
Global.use_gpu
=
${
use_gpu
}
status_check
$?
"
${
trainer
}
"
"
${
command
}
"
"
${
save_log
}
/train.log"
command
=
"
${
python
}
${
export_model
}
-c
${
yml_file
}
-o Global.pretrained_model=
${
save_log
}
/best_accuracy Global.save_inference_dir=
${
save_log
}
/export_inference/ Global.save_model_dir=
${
save_log
}
"
echo
${
python
}
${
export_model
}
-c
${
yml_file
}
-o
Global.pretrained_model
=
${
save_log
}
/best_accuracy Global.save_inference_dir
=
${
save_log
}
/export_inference/ Global.save_model_dir
=
${
save_log
}
#
status_check $? "${trainer}" "${command}" "${save_log}/train.log"
command
=
"
${
env
}
${
python
}
${
export_model
}
-c
${
yml_file
}
-o Global.pretrained_model=
${
save_log
}
/best_accuracy Global.save_inference_dir=
${
save_log
}
/export_inference/ Global.save_model_dir=
${
save_log
}
"
${
env
}
${
python
}
${
export_model
}
-c
${
yml_file
}
-o
Global.pretrained_model
=
${
save_log
}
/best_accuracy Global.save_inference_dir
=
${
save_log
}
/export_inference/ Global.save_model_dir
=
${
save_log
}
status_check
$?
"
${
trainer
}
"
"
${
command
}
"
"
${
save_log
}
/train.log"
if
[
"
${
model_name
}
"
=
"det"
]
;
then
export
rec_batch_size_list
=(
"1"
)
...
...
@@ -148,8 +153,8 @@ for train_model in ${train_model_list[*]}; do
for
rec_batch_size
in
${
rec_batch_size_list
[*]
}
;
do
save_log_path
=
"
${
log_path
}
/
${
model_name
}
_
${
slim_trainer
}
_cpu_usemkldnn_
${
use_mkldnn
}
_cputhreads_
${
threads
}
_recbatchnum_
${
rec_batch_size
}
_infer.log"
command
=
"
${
python
}
${
inference
}
--enable_mkldnn=
${
use_mkldnn
}
--use_gpu=False --cpu_threads=
${
threads
}
--benchmark=True --det_model_dir=
${
save_log
}
/export_inference/ --rec_batch_num=
${
rec_batch_size
}
--rec_model_dir=
${
rec_model_dir
}
--image_dir=
${
img_dir
}
--save_log_path=
${
save_log_path
}
"
echo
${
python
}
${
inference
}
--enable_mkldnn
=
${
use_mkldnn
}
--use_gpu
=
False
--cpu_threads
=
${
threads
}
--benchmark
=
True
--det_model_dir
=
${
save_log
}
/export_inference/
--rec_batch_num
=
${
rec_batch_size
}
--rec_model_dir
=
${
rec_model_dir
}
--image_dir
=
${
img_dir
}
--save_log_path
=
${
save_log_path
}
#
status_check $? "${inference}" "${command}" "${save_log}"
${
python
}
${
inference
}
--enable_mkldnn
=
${
use_mkldnn
}
--use_gpu
=
False
--cpu_threads
=
${
threads
}
--benchmark
=
True
--det_model_dir
=
${
save_log
}
/export_inference/
--rec_batch_num
=
${
rec_batch_size
}
--rec_model_dir
=
${
rec_model_dir
}
--image_dir
=
${
img_dir
}
--save_log_path
=
${
save_log_path
}
status_check
$?
"
${
inference
}
"
"
${
command
}
"
"
${
save_log
}
"
done
done
done
...
...
@@ -161,8 +166,9 @@ for train_model in ${train_model_list[*]}; do
fi
for
rec_batch_size
in
${
rec_batch_size_list
[*]
}
;
do
save_log_path
=
"
${
log_path
}
/
${
model_name
}
_
${
slim_trainer
}
_gpu_usetensorrt_
${
use_trt
}
_usefp16_
${
precision
}
_recbatchnum_
${
rec_batch_size
}
_infer.log"
echo
${
python
}
${
inference
}
--use_gpu
=
True
--use_tensorrt
=
${
use_trt
}
--precision
=
${
precision
}
--benchmark
=
True
--det_model_dir
=
${
save_log
}
/export_inference/
--rec_batch_num
=
${
rec_batch_size
}
--rec_model_dir
=
${
rec_model_dir
}
--image_dir
=
${
img_dir
}
--save_log_path
=
${
save_log_path
}
# status_check $? "${inference}" "${command}" "${save_log}"
command
=
"
${
env
}
${
python
}
${
inference
}
--use_gpu=True --use_tensorrt=
${
use_trt
}
--precision=
${
precision
}
--benchmark=True --det_model_dir=
${
save_log
}
/export_inference/ --rec_batch_num=
${
rec_batch_size
}
--rec_model_dir=
${
rec_model_dir
}
--image_dir=
${
img_dir
}
--save_log_path=
${
save_log_path
}
"
${
env
}
${
python
}
${
inference
}
--use_gpu
=
True
--use_tensorrt
=
${
use_trt
}
--precision
=
${
precision
}
--benchmark
=
True
--det_model_dir
=
${
save_log
}
/export_inference/
--rec_batch_num
=
${
rec_batch_size
}
--rec_model_dir
=
${
rec_model_dir
}
--image_dir
=
${
img_dir
}
--save_log_path
=
${
save_log_path
}
status_check
$?
"
${
inference
}
"
"
${
command
}
"
"
${
save_log
}
"
done
done
done
...
...
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