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4b56069d
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体验新版 GitCode,发现更多精彩内容 >>
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4b56069d
编写于
6月 09, 2021
作者:
L
LDOUBLEV
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差异文件
fix bug
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0f84fc1e
变更
2
隐藏空白更改
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并排
Showing
2 changed file
with
24 addition
and
15 deletion
+24
-15
test/infer.sh
test/infer.sh
+22
-13
test/test.sh
test/test.sh
+2
-2
未找到文件。
test/infer.sh
浏览文件 @
4b56069d
...
...
@@ -45,13 +45,14 @@ for train_model in ${train_model_list[*]}; do
if
[
${
train_model
}
=
"ocr_det"
]
;
then
model_name
=
"det"
yml_file
=
"configs/det/det_mv3_db.yml"
# 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
wget
-nc
-P
./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar
cd
./inference
&&
tar
xf ch_det_data_50.tar
&&
cd
../
img_dir
=
"./inference/ch_det_data_50/"
elif
[
${
train_model
}
=
"ocr_rec"
]
;
then
model_name
=
"rec"
yml_file
=
"configs/rec/rec_mv3_none_bilstm_ctc.yml"
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
wget
-nc
-P
./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_rec_data_200.tar
cd
./inference
&&
tar
xf ch_rec_data_200.tar
&&
cd
../
img_dir
=
"./inference/ch_rec_data_200/"
fi
...
...
@@ -59,45 +60,53 @@ for train_model in ${train_model_list[*]}; do
for
slim_trainer
in
${
slim_trainer_list
[*]
}
;
do
if
[
${
slim_trainer
}
=
"norm"
]
;
then
if
[
${
model_name
}
=
"det"
]
;
then
eval_model_name
=
"ch_ppocr_mobile_v2.0_det_
infer
"
eval_model_name
=
"ch_ppocr_mobile_v2.0_det_
train
"
wget
-nc
-P
./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_train.tar
cd
./inference
&&
tar
xf
${
eval_model_name
}
.tar
&&
cd
../
else
eval_model_name
=
"ch_ppocr_mobile_v2.0_rec_
infer
"
eval_model_name
=
"ch_ppocr_mobile_v2.0_rec_
train
"
wget
-nc
-P
./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_train.tar
cd
./inference
&&
tar
xf
${
eval_model_name
}
.tar
&&
cd
../
fi
elif
[
${
slim_trainer
}
=
"quant"
]
;
then
if
[
${
model_name
}
=
"det"
]
;
then
eval_model_name
=
"ch_ppocr_mobile_v2.0_det_quant_
infer
"
eval_model_name
=
"ch_ppocr_mobile_v2.0_det_quant_
train
"
wget
-nc
-P
./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_det_quant_train.tar
cd
./inference
&&
tar
xf
${
eval_model_name
}
.tar
&&
cd
../
else
eval_model_name
=
"ch_ppocr_mobile_v2.0_rec_quant_
infer
"
eval_model_name
=
"ch_ppocr_mobile_v2.0_rec_quant_
train
"
wget
-nc
-P
./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_rec_quant_train.tar
cd
./inference
&&
tar
xf
${
eval_model_name
}
.tar
&&
cd
../
fi
elif
[
${
slim_trainer
}
=
"distill"
]
;
then
if
[
${
model_name
}
=
"det"
]
;
then
eval_model_name
=
"ch_ppocr_mobile_v2.0_det_distill_
infer
"
eval_model_name
=
"ch_ppocr_mobile_v2.0_det_distill_
train
"
wget
-nc
-P
./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_det_distill_train.tar
cd
./inference
&&
tar
xf
${
eval_model_name
}
.tar
&&
cd
../
else
eval_model_name
=
"ch_ppocr_mobile_v2.0_rec_distill_
infer
"
eval_model_name
=
"ch_ppocr_mobile_v2.0_rec_distill_
train
"
wget
-nc
-P
./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_rec_distill_train.tar
cd
./inference
&&
tar
xf
${
eval_model_name
}
.tar
&&
cd
../
fi
elif
[
${
slim_trainer
}
=
"prune"
]
;
then
if
[
${
model_name
}
=
"det"
]
;
then
eval_model_name
=
"ch_ppocr_mobile_v2.0_det_prune_train"
wget
-nc
-P
./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_det_prune_train.tar
cd
./inference
&&
tar
xf
${
eval_model_name
}
.tar
&&
cd
../
else
eval_model_name
=
"ch_ppocr_mobile_v2.0_rec_prune_train"
wget
-nc
-P
./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/slim/ch_ppocr_mobile_v2.0_rec_prune_train.tar
cd
./inference
&&
tar
xf
${
eval_model_name
}
.tar
&&
cd
../
fi
fi
save_log_path
=
"
${
log_path
}
/
${
eval_model_name
}
"
command
=
"
${
python
}
tools/eval.py -c
${
yml_file
}
-o Global.pretrained_model=
${
eval_model_name
}
Global.save_model_dir=
${
save_log_path
}
"
${
python
}
tools/eval.py
-c
${
yml_file
}
-o
Global.pretrained_model
=
${
eval_model_name
}
Global.save_model_dir
=
${
save_log_path
}
command
=
"
${
python
}
tools/eval.py -c
${
yml_file
}
-o Global.pretrained_model=
"
${
eval_model_name
}
/best_accuracy
"
Global.save_model_dir=
${
save_log_path
}
"
${
python
}
tools/eval.py
-c
${
yml_file
}
-o
Global.pretrained_model
=
"
${
eval_model_name
}
/best_accuracy"
Global.save_model_dir
=
${
save_log_path
}
status_check
$?
"
${
trainer
}
"
"
${
command
}
"
"
${
save_log_path
}
/train.log"
command
=
"
${
python
}
tools/export_model.py -c
${
yml_file
}
-o Global.pretrained_model=
${
eval_model_name
}
Global.save_inference_dir=
${
log_path
}
/
${
eval_model_name
}
_infer Global.save_model_dir=
${
save_log_path
}
"
${
python
}
tools/export_model.py
-c
${
yml_file
}
-o
Global.pretrained_model
=
${
eval_model_name
}
Global.save_inference_dir
=
"
${
log_path
}
/
${
eval_model_name
}
_infer"
Global.save_model_dir
=
${
save_log_path
}
command
=
"
${
python
}
tools/export_model.py -c
${
yml_file
}
-o Global.pretrained_model=
"
${
eval_model_name
}
/best_accuracy
"
Global.save_inference_dir=
${
log_path
}
/
${
eval_model_name
}
_infer Global.save_model_dir=
${
save_log_path
}
"
${
python
}
tools/export_model.py
-c
${
yml_file
}
-o
Global.pretrained_model
=
"
${
eval_model_name
}
/best_accuracy"
Global.save_inference_dir
=
"
${
log_path
}
/
${
eval_model_name
}
_infer"
Global.save_model_dir
=
${
save_log_path
}
status_check
$?
"
${
trainer
}
"
"
${
command
}
"
"
${
save_log_path
}
/train.log"
if
[
$?
-eq
0
]
;
then
...
...
test/test.sh
浏览文件 @
4b56069d
...
...
@@ -127,8 +127,8 @@ 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
=
"
${
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
}
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
}
Train.loader.batch_size_per_card=2
"
${
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
}
Train.loader.batch_size_per_card
=
2
status_check
$?
"
${
trainer
}
"
"
${
command
}
"
"
${
save_log
}
/train.log"
command
=
"
${
env
}
${
python
}
${
export_model
}
-c
${
yml_file
}
-o Global.pretrained_model=
${
save_log
}
/latest Global.save_inference_dir=
${
save_log
}
/export_inference/ Global.save_model_dir=
${
save_log
}
"
...
...
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