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e0d38233
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e0d38233
编写于
6月 14, 2022
作者:
A
andyjpaddle
提交者:
GitHub
6月 14, 2022
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差异文件
Merge pull request #6582 from andyjpaddle/table
[TIPC] add table to tipc
上级
6437875b
5017ff4b
变更
8
显示空白变更内容
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Showing
8 changed file
with
376 addition
and
7 deletion
+376
-7
test_tipc/configs/det_r50_vd_sast_icdar15_v2.0/train_infer_python.txt
...nfigs/det_r50_vd_sast_icdar15_v2.0/train_infer_python.txt
+2
-2
test_tipc/configs/en_table_structure/table_mv3.yml
test_tipc/configs/en_table_structure/table_mv3.yml
+117
-0
test_tipc/configs/en_table_structure/train_infer_python.txt
test_tipc/configs/en_table_structure/train_infer_python.txt
+53
-0
test_tipc/configs/en_table_structure/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt
...train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt
+53
-0
test_tipc/configs/en_table_structure_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt
...el_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt
+21
-0
test_tipc/configs/en_table_structure_PACT/train_infer_python.txt
...pc/configs/en_table_structure_PACT/train_infer_python.txt
+53
-0
test_tipc/configs/en_table_structure_PACT/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt
...train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt
+53
-0
test_tipc/prepare.sh
test_tipc/prepare.sh
+24
-5
未找到文件。
test_tipc/configs/det_r50_vd_sast_icdar15_v2.0/train_infer_python.txt
浏览文件 @
e0d38233
...
...
@@ -4,7 +4,7 @@ python:python3.7
gpu_list:0|0,1
Global.use_gpu:True|True
Global.auto_cast:null
Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=500
0
Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=500
Global.save_model_dir:./output/
Train.loader.batch_size_per_card:lite_train_lite_infer=2|whole_train_whole_infer=4
Global.pretrained_model:null
...
...
@@ -45,7 +45,7 @@ inference:tools/infer/predict_det.py
--use_tensorrt:False
--precision:fp32
--det_model_dir:
--image_dir:./inference/ch_det_data_50/all-sum-510/
--image_dir:./inference/ch_det_data_50/all-sum-510/
00008790.jpg
null:null
--benchmark:True
--det_algorithm:SAST
...
...
test_tipc/configs/en_table_structure/table_mv3.yml
0 → 100755
浏览文件 @
e0d38233
Global
:
use_gpu
:
true
epoch_num
:
10
log_smooth_window
:
20
print_batch_step
:
5
save_model_dir
:
./output/table_mv3/
save_epoch_step
:
3
# evaluation is run every 400 iterations after the 0th iteration
eval_batch_step
:
[
0
,
400
]
cal_metric_during_train
:
True
pretrained_model
:
checkpoints
:
save_inference_dir
:
use_visualdl
:
False
infer_img
:
doc/table/table.jpg
# for data or label process
character_dict_path
:
ppocr/utils/dict/table_structure_dict.txt
character_type
:
en
max_text_length
:
100
max_elem_length
:
800
max_cell_num
:
500
infer_mode
:
False
process_total_num
:
0
process_cut_num
:
0
Optimizer
:
name
:
Adam
beta1
:
0.9
beta2
:
0.999
clip_norm
:
5.0
lr
:
learning_rate
:
0.001
regularizer
:
name
:
'
L2'
factor
:
0.00000
Architecture
:
model_type
:
table
algorithm
:
TableAttn
Backbone
:
name
:
MobileNetV3
scale
:
1.0
model_name
:
large
Head
:
name
:
TableAttentionHead
hidden_size
:
256
l2_decay
:
0.00001
loc_type
:
2
max_text_length
:
100
max_elem_length
:
800
max_cell_num
:
500
Loss
:
name
:
TableAttentionLoss
structure_weight
:
100.0
loc_weight
:
10000.0
PostProcess
:
name
:
TableLabelDecode
Metric
:
name
:
TableMetric
main_indicator
:
acc
Train
:
dataset
:
name
:
PubTabDataSet
data_dir
:
./train_data/pubtabnet/train
label_file_path
:
./train_data/pubtabnet/train.jsonl
transforms
:
-
DecodeImage
:
# load image
img_mode
:
BGR
channel_first
:
False
-
ResizeTableImage
:
max_len
:
488
-
TableLabelEncode
:
-
NormalizeImage
:
scale
:
1./255.
mean
:
[
0.485
,
0.456
,
0.406
]
std
:
[
0.229
,
0.224
,
0.225
]
order
:
'
hwc'
-
PaddingTableImage
:
-
ToCHWImage
:
-
KeepKeys
:
keep_keys
:
[
'
image'
,
'
structure'
,
'
bbox_list'
,
'
sp_tokens'
,
'
bbox_list_mask'
]
loader
:
shuffle
:
True
batch_size_per_card
:
32
drop_last
:
True
num_workers
:
1
Eval
:
dataset
:
name
:
PubTabDataSet
data_dir
:
./train_data/pubtabnet/test/
label_file_path
:
./train_data/pubtabnet/test.jsonl
transforms
:
-
DecodeImage
:
# load image
img_mode
:
BGR
channel_first
:
False
-
ResizeTableImage
:
max_len
:
488
-
TableLabelEncode
:
-
NormalizeImage
:
scale
:
1./255.
mean
:
[
0.485
,
0.456
,
0.406
]
std
:
[
0.229
,
0.224
,
0.225
]
order
:
'
hwc'
-
PaddingTableImage
:
-
ToCHWImage
:
-
KeepKeys
:
keep_keys
:
[
'
image'
,
'
structure'
,
'
bbox_list'
,
'
sp_tokens'
,
'
bbox_list_mask'
]
loader
:
shuffle
:
False
drop_last
:
False
batch_size_per_card
:
16
num_workers
:
1
test_tipc/configs/en_table_structure/train_infer_python.txt
0 → 100644
浏览文件 @
e0d38233
===========================train_params===========================
model_name:en_table_structure
python:python3.7
gpu_list:0|0,1
Global.use_gpu:True|True
Global.auto_cast:fp32
Global.epoch_num:lite_train_lite_infer=3|whole_train_whole_infer=50
Global.save_model_dir:./output/
Train.loader.batch_size_per_card:lite_train_lite_infer=16|whole_train_whole_infer=128
Global.pretrained_model:./pretrain_models/en_ppocr_mobile_v2.0_table_structure_train/best_accuracy
train_model_name:latest
train_infer_img_dir:./ppstructure/docs/table/table.jpg
null:null
##
trainer:norm_train
norm_train:tools/train.py -c test_tipc/configs/en_table_structure/table_mv3.yml -o
pact_train:null
fpgm_train:null
distill_train:null
null:null
null:null
##
===========================eval_params===========================
eval:null
null:null
##
===========================infer_params===========================
Global.save_inference_dir:./output/
Global.checkpoints:
norm_export:tools/export_model.py -c test_tipc/configs/en_table_structure/table_mv3.yml -o
quant_export:
fpgm_export:
distill_export:null
export1:null
export2:null
##
infer_model:./inference/en_ppocr_mobile_v2.0_table_structure_infer
infer_export:null
infer_quant:False
inference:ppstructure/table/predict_table.py --det_model_dir=./inference/en_ppocr_mobile_v2.0_table_det_infer --rec_model_dir=./inference/en_ppocr_mobile_v2.0_table_rec_infer --rec_char_dict_path=./ppocr/utils/dict/table_dict.txt --table_char_dict_path=./ppocr/utils/dict/table_structure_dict.txt --image_dir=./ppstructure/docs/table/table.jpg --det_limit_side_len=736 --det_limit_type=min --output ./output/table
--use_gpu:True|False
--enable_mkldnn:False
--cpu_threads:6
--rec_batch_num:1
--use_tensorrt:False
--precision:fp32
--table_model_dir:
--image_dir:./ppstructure/docs/table/table.jpg
null:null
--benchmark:False
null:null
===========================infer_benchmark_params==========================
random_infer_input:[{float32,[3,488,488]}]
test_tipc/configs/en_table_structure/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt
0 → 100644
浏览文件 @
e0d38233
===========================train_params===========================
model_name:en_table_structure
python:python3.7
gpu_list:0|0,1
Global.use_gpu:True|True
Global.auto_cast:amp
Global.epoch_num:lite_train_lite_infer=3|whole_train_whole_infer=50
Global.save_model_dir:./output/
Train.loader.batch_size_per_card:lite_train_lite_infer=16|whole_train_whole_infer=128
Global.pretrained_model:./pretrain_models/en_ppocr_mobile_v2.0_table_structure_train/best_accuracy
train_model_name:latest
train_infer_img_dir:./ppstructure/docs/table/table.jpg
null:null
##
trainer:norm_train
norm_train:tools/train.py -c test_tipc/configs/en_table_structure/table_mv3.yml -o
pact_train:null
fpgm_train:null
distill_train:null
null:null
null:null
##
===========================eval_params===========================
eval:null
null:null
##
===========================infer_params===========================
Global.save_inference_dir:./output/
Global.checkpoints:
norm_export:tools/export_model.py -c test_tipc/configs/en_table_structure/table_mv3.yml -o
quant_export:
fpgm_export:
distill_export:null
export1:null
export2:null
##
infer_model:./inference/en_ppocr_mobile_v2.0_table_structure_infer
infer_export:null
infer_quant:False
inference:ppstructure/table/predict_table.py --det_model_dir=./inference/en_ppocr_mobile_v2.0_table_det_infer --rec_model_dir=./inference/en_ppocr_mobile_v2.0_table_rec_infer --rec_char_dict_path=./ppocr/utils/dict/table_dict.txt --table_char_dict_path=./ppocr/utils/dict/table_structure_dict.txt --image_dir=./ppstructure/docs/table/table.jpg --det_limit_side_len=736 --det_limit_type=min --output ./output/table
--use_gpu:True|False
--enable_mkldnn:False
--cpu_threads:6
--rec_batch_num:1
--use_tensorrt:False
--precision:fp32
--table_model_dir:
--image_dir:./ppstructure/docs/table/table.jpg
null:null
--benchmark:False
null:null
===========================infer_benchmark_params==========================
random_infer_input:[{float32,[3,488,488]}]
test_tipc/configs/en_table_structure_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt
0 → 100644
浏览文件 @
e0d38233
===========================train_params===========================
model_name:en_table_structure_KL
python:python3.7
Global.pretrained_model:
Global.save_inference_dir:null
infer_model:./inference/en_ppocr_mobile_v2.0_table_structure_infer/
infer_export:deploy/slim/quantization/quant_kl.py -c test_tipc/configs/en_table_structure/table_mv3.yml -o
infer_quant:True
inference:ppstructure/table/predict_table.py --det_model_dir=./inference/en_ppocr_mobile_v2.0_table_det_infer --rec_model_dir=./inference/en_ppocr_mobile_v2.0_table_rec_infer --rec_char_dict_path=./ppocr/utils/dict/table_dict.txt --table_char_dict_path=./ppocr/utils/dict/table_structure_dict.txt --image_dir=./ppstructure/docs/table/table.jpg --det_limit_side_len=736 --det_limit_type=min --output ./output/table
--use_gpu:True|False
--enable_mkldnn:False
--cpu_threads:6
--rec_batch_num:1
--use_tensorrt:False
--precision:int8
--table_model_dir:
--image_dir:./ppstructure/docs/table/table.jpg
null:null
--benchmark:False
null:null
null:null
test_tipc/configs/en_table_structure_PACT/train_infer_python.txt
0 → 100644
浏览文件 @
e0d38233
===========================train_params===========================
model_name:en_table_structure_PACT
python:python3.7
gpu_list:0|0,1
Global.use_gpu:True|True
Global.auto_cast:fp32
Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=50
Global.save_model_dir:./output/
Train.loader.batch_size_per_card:lite_train_lite_infer=16|whole_train_whole_infer=128
Global.pretrained_model:./pretrain_models/en_ppocr_mobile_v2.0_table_structure_train/best_accuracy
train_model_name:latest
train_infer_img_dir:./ppstructure/docs/table/table.jpg
null:null
##
trainer:pact_train
norm_train:null
pact_train:deploy/slim/quantization/quant.py -c test_tipc/configs/en_table_structure/table_mv3.yml -o
fpgm_train:null
distill_train:null
null:null
null:null
##
===========================eval_params===========================
eval:null
null:null
##
===========================infer_params===========================
Global.save_inference_dir:./output/
Global.checkpoints:
norm_export:null
quant_export:deploy/slim/quantization/export_model.py -c test_tipc/configs/en_table_structure/table_mv3.yml -o
fpgm_export:
distill_export:null
export1:null
export2:null
##
infer_model:./inference/en_ppocr_mobile_v2.0_table_structure_infer
infer_export:null
infer_quant:True
inference:ppstructure/table/predict_table.py --det_model_dir=./inference/en_ppocr_mobile_v2.0_table_det_infer --rec_model_dir=./inference/en_ppocr_mobile_v2.0_table_rec_infer --rec_char_dict_path=./ppocr/utils/dict/table_dict.txt --table_char_dict_path=./ppocr/utils/dict/table_structure_dict.txt --image_dir=./ppstructure/docs/table/table.jpg --det_limit_side_len=736 --det_limit_type=min --output ./output/table
--use_gpu:True|False
--enable_mkldnn:False
--cpu_threads:6
--rec_batch_num:1
--use_tensorrt:False
--precision:fp32
--table_model_dir:
--image_dir:./ppstructure/docs/table/table.jpg
null:null
--benchmark:False
null:null
===========================infer_benchmark_params==========================
random_infer_input:[{float32,[3,488,488]}]
test_tipc/configs/en_table_structure_PACT/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt
0 → 100644
浏览文件 @
e0d38233
===========================train_params===========================
model_name:en_table_structure_PACT
python:python3.7
gpu_list:0|0,1
Global.use_gpu:True|True
Global.auto_cast:amp
Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=50
Global.save_model_dir:./output/
Train.loader.batch_size_per_card:lite_train_lite_infer=16|whole_train_whole_infer=128
Global.pretrained_model:./pretrain_models/en_ppocr_mobile_v2.0_table_structure_train/best_accuracy
train_model_name:latest
train_infer_img_dir:./ppstructure/docs/table/table.jpg
null:null
##
trainer:pact_train
norm_train:null
pact_train:deploy/slim/quantization/quant.py -c test_tipc/configs/en_table_structure/table_mv3.yml -o
fpgm_train:null
distill_train:null
null:null
null:null
##
===========================eval_params===========================
eval:null
null:null
##
===========================infer_params===========================
Global.save_inference_dir:./output/
Global.checkpoints:
norm_export:null
quant_export:deploy/slim/quantization/export_model.py -c test_tipc/configs/en_table_structure/table_mv3.yml -o
fpgm_export:
distill_export:null
export1:null
export2:null
##
infer_model:./inference/en_ppocr_mobile_v2.0_table_structure_infer
infer_export:null
infer_quant:True
inference:ppstructure/table/predict_table.py --det_model_dir=./inference/en_ppocr_mobile_v2.0_table_det_infer --rec_model_dir=./inference/en_ppocr_mobile_v2.0_table_rec_infer --rec_char_dict_path=./ppocr/utils/dict/table_dict.txt --table_char_dict_path=./ppocr/utils/dict/table_structure_dict.txt --image_dir=./ppstructure/docs/table/table.jpg --det_limit_side_len=736 --det_limit_type=min --output ./output/table
--use_gpu:True|False
--enable_mkldnn:False
--cpu_threads:6
--rec_batch_num:1
--use_tensorrt:False
--precision:fp32
--table_model_dir:
--image_dir:./ppstructure/docs/table/table.jpg
null:null
--benchmark:False
null:null
===========================infer_benchmark_params==========================
random_infer_input:[{float32,[3,488,488]}]
test_tipc/prepare.sh
浏览文件 @
e0d38233
...
...
@@ -55,6 +55,9 @@ if [ ${MODE} = "lite_train_lite_infer" ];then
if
[
${
model_name
}
==
"en_table_structure"
]
;
then
wget
-nc
-P
./pretrain_models/ https://paddleocr.bj.bcebos.com/dygraph_v2.1/table/en_ppocr_mobile_v2.0_table_structure_train.tar
--no-check-certificate
cd
./pretrain_models/
&&
tar
xf en_ppocr_mobile_v2.0_table_structure_train.tar
&&
cd
../
wget
-nc
-P
./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_det_infer.tar
--no-check-certificate
wget
-nc
-P
./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_rec_infer.tar
--no-check-certificate
cd
./inference/
&&
tar
xf en_ppocr_mobile_v2.0_table_det_infer.tar
&&
tar
xf en_ppocr_mobile_v2.0_table_rec_infer.tar
&&
cd
../
fi
cd
./pretrain_models/
&&
tar
xf det_mv3_db_v2.0_train.tar
&&
cd
../
rm
-rf
./train_data/icdar2015
...
...
@@ -147,9 +150,12 @@ elif [ ${MODE} = "whole_train_whole_infer" ];then
wget
-nc
-P
./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/total_text_lite.tar
--no-check-certificate
cd
./train_data
&&
tar
xf total_text.tar
&&
ln
-s
total_text_lite total_text
&&
cd
../
fi
if
[
${
model_name
}
==
"en_table_structure"
]
;
then
if
[
[
${
model_name
}
=
~
"en_table_structure"
]
]
;
then
wget
-nc
-P
./pretrain_models/ https://paddleocr.bj.bcebos.com/dygraph_v2.1/table/en_ppocr_mobile_v2.0_table_structure_train.tar
--no-check-certificate
cd
./pretrain_models/
&&
tar
xf en_ppocr_mobile_v2.0_table_structure_train.tar
&&
cd
../
wget
-nc
-P
./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_det_infer.tar
--no-check-certificate
wget
-nc
-P
./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_rec_infer.tar
--no-check-certificate
cd
./inference/
&&
tar
xf en_ppocr_mobile_v2.0_table_det_infer.tar
&&
tar
xf en_ppocr_mobile_v2.0_table_rec_infer.tar
&&
cd
../
fi
elif
[
${
MODE
}
=
"lite_train_whole_infer"
]
;
then
wget
-nc
-P
./pretrain_models/ https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/MobileNetV3_large_x0_5_pretrained.pdparams
--no-check-certificate
...
...
@@ -172,9 +178,12 @@ elif [ ${MODE} = "lite_train_whole_infer" ];then
wget
-nc
-P
./pretrain_models/ https://paddleocr.bj.bcebos.com/PP-OCRv3/chinese/ch_PP-OCRv3_det_distill_train.tar
--no-check-certificate
cd
./pretrain_models/
&&
tar
xf ch_PP-OCRv3_det_distill_train.tar
&&
cd
../
fi
if
[
${
model_name
}
==
"en_table_structure"
]
;
then
if
[
[
${
model_name
}
=
~
"en_table_structure"
]
]
;
then
wget
-nc
-P
./pretrain_models/ https://paddleocr.bj.bcebos.com/dygraph_v2.1/table/en_ppocr_mobile_v2.0_table_structure_train.tar
--no-check-certificate
cd
./pretrain_models/
&&
tar
xf en_ppocr_mobile_v2.0_table_structure_train.tar
&&
cd
../
wget
-nc
-P
./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_det_infer.tar
--no-check-certificate
wget
-nc
-P
./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_rec_infer.tar
--no-check-certificate
cd
./inference/
&&
tar
xf en_ppocr_mobile_v2.0_table_det_infer.tar
&&
tar
xf en_ppocr_mobile_v2.0_table_rec_infer.tar
&&
cd
../
fi
elif
[
${
MODE
}
=
"whole_infer"
]
;
then
wget
-nc
-P
./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar
--no-check-certificate
...
...
@@ -335,9 +344,11 @@ elif [ ${MODE} = "whole_infer" ];then
wget
-nc
-P
./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_r50_vd_east_v2.0_train.tar
--no-check-certificate
cd
./inference/
&&
tar
xf det_r50_vd_east_v2.0_train.tar &
cd
../
fi
if
[
${
model_name
}
==
"en_table_structure"
]
;
then
if
[
[
${
model_name
}
=
~
"en_table_structure"
]
]
;
then
wget
-nc
-P
./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_structure_infer.tar
--no-check-certificate
cd
./inference/
&&
tar
xf en_ppocr_mobile_v2.0_table_structure_infer.tar
&&
cd
../
wget
-nc
-P
./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_det_infer.tar
--no-check-certificate
wget
-nc
-P
./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_rec_infer.tar
--no-check-certificate
cd
./inference/
&&
tar
xf en_ppocr_mobile_v2.0_table_structure_infer.tar
&&
tar
xf en_ppocr_mobile_v2.0_table_det_infer.tar
&&
tar
xf en_ppocr_mobile_v2.0_table_rec_infer.tar
&&
cd
../
fi
fi
...
...
@@ -383,6 +394,14 @@ if [ ${MODE} = "klquant_whole_infer" ]; then
cd
./train_data/
&&
tar
xf ic15_data.tar
&&
cd
../
cd
./inference
&&
tar
xf ch_ppocr_mobile_v2.0_rec_infer.tar
&&
tar
xf rec_inference.tar
&&
cd
../
fi
if
[
${
model_name
}
=
"en_table_structure_KL"
]
;
then
wget
-nc
-P
./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_structure_infer.tar
--no-check-certificate
wget
-nc
-P
./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_det_infer.tar
--no-check-certificate
wget
-nc
-P
./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_rec_infer.tar
--no-check-certificate
wget
-nc
-P
./train_data/ https://paddleocr.bj.bcebos.com/dataset/pubtabnet.tar
--no-check-certificate
cd
./inference/
&&
tar
xf en_ppocr_mobile_v2.0_table_structure_infer.tar
&&
tar
xf en_ppocr_mobile_v2.0_table_det_infer.tar
&&
tar
xf en_ppocr_mobile_v2.0_table_rec_infer.tar
&&
cd
../
cd
./train_data/
&&
tar
xf pubtabnet.tar
&&
cd
../
fi
fi
if
[
${
MODE
}
=
"cpp_infer"
]
;
then
...
...
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