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0b4106a6
编写于
4月 28, 2022
作者:
T
Topdu
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Merge branch 'dygraph' of
https://github.com/Topdu/PaddleOCR
into dygraph
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bde50863
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20 changed file
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609 addition
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145 deletion
+609
-145
applications/多模态表单识别.md
applications/多模态表单识别.md
+0
-0
doc/joinus.PNG
doc/joinus.PNG
+0
-0
ppocr/data/imaug/rec_img_aug.py
ppocr/data/imaug/rec_img_aug.py
+1
-1
test_tipc/configs/ch_PP-OCRv2_det/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/ch_PP-OCRv2_det_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/configs/ch_PP-OCRv2_rec/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/ch_PP-OCRv2_rec_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/configs/ch_ppocr_mobile_v2.0_det/det_mv3_db.yml
test_tipc/configs/ch_ppocr_mobile_v2.0_det/det_mv3_db.yml
+0
-126
test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt
...train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt
+12
-10
test_tipc/configs/ch_ppocr_mobile_v2.0_det_FPGM/train_infer_python.txt
...figs/ch_ppocr_mobile_v2.0_det_FPGM/train_infer_python.txt
+1
-1
test_tipc/configs/ch_ppocr_mobile_v2.0_det_FPGM/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/ch_ppocr_mobile_v2.0_det_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/configs/ch_ppocr_mobile_v2.0_rec/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/ch_ppocr_mobile_v2.0_rec_FPGM/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/ch_ppocr_mobile_v2.0_rec_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/configs/ch_ppocr_server_v2.0_det/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/ch_ppocr_server_v2.0_rec/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt
...train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt
+53
-0
tools/eval.py
tools/eval.py
+4
-2
tools/infer/utility.py
tools/infer/utility.py
+4
-3
tools/program.py
tools/program.py
+4
-2
未找到文件。
applications/多模态表单识别.md
0 → 100644
浏览文件 @
0b4106a6
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doc/joinus.PNG
查看替换文件 @
b0e18544
浏览文件 @
0b4106a6
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199.8 KB
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W:
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Swipe
Onion skin
ppocr/data/imaug/rec_img_aug.py
浏览文件 @
0b4106a6
...
...
@@ -82,7 +82,7 @@ class ClsResizeImg(object):
def
__call__
(
self
,
data
):
img
=
data
[
'image'
]
norm_img
=
resize_norm_img
(
img
,
self
.
image_shape
)
norm_img
,
_
=
resize_norm_img
(
img
,
self
.
image_shape
)
data
[
'image'
]
=
norm_img
return
data
...
...
test_tipc/configs/ch_PP-OCRv2_det/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt
0 → 100644
浏览文件 @
0b4106a6
===========================train_params===========================
model_name:ch_PPOCRv2_det
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=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
train_model_name:latest
train_infer_img_dir:./train_data/icdar2015/text_localization/ch4_test_images/
null:null
##
trainer:norm_train
norm_train:tools/train.py -c configs/det/ch_PP-OCRv2/ch_PP-OCRv2_det_cml.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 configs/det/ch_PP-OCRv2/ch_PP-OCRv2_det_cml.yml -o
quant_export:null
fpgm_export:
distill_export:null
export1:null
export2:null
inference_dir:Student
infer_model:./inference/ch_PP-OCRv2_det_infer/
infer_export:null
infer_quant:False
inference:tools/infer/predict_det.py
--use_gpu:True|False
--enable_mkldnn:True|False
--cpu_threads:1|6
--rec_batch_num:1
--use_tensorrt:False|True
--precision:fp32|fp16|int8
--det_model_dir:
--image_dir:./inference/ch_det_data_50/all-sum-510/
null:null
--benchmark:True
null:null
===========================infer_benchmark_params==========================
random_infer_input:[{float32,[3,640,640]}];[{float32,[3,960,960]}]
test_tipc/configs/ch_PP-OCRv2_det_PACT/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt
0 → 100644
浏览文件 @
0b4106a6
===========================train_params===========================
model_name:ch_PPOCRv2_det_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=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
train_model_name:latest
train_infer_img_dir:./train_data/icdar2015/text_localization/ch4_test_images/
null:null
##
trainer:pact_train
norm_train:null
pact_train:deploy/slim/quantization/quant.py -c configs/det/ch_PP-OCRv2/ch_PP-OCRv2_det_cml.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 configs/det/ch_PP-OCRv2/ch_PP-OCRv2_det_cml.yml -o
fpgm_export:
distill_export:null
export1:null
export2:null
inference_dir:Student
infer_model:./inference/ch_PP-OCRv2_det_infer/
infer_export:null
infer_quant:False
inference:tools/infer/predict_det.py
--use_gpu:True|False
--enable_mkldnn:True|False
--cpu_threads:1|6
--rec_batch_num:1
--use_tensorrt:False|True
--precision:fp32|fp16|int8
--det_model_dir:
--image_dir:./inference/ch_det_data_50/all-sum-510/
null:null
--benchmark:True
null:null
===========================infer_benchmark_params==========================
random_infer_input:[{float32,[3,640,640]}];[{float32,[3,960,960]}]
test_tipc/configs/ch_PP-OCRv2_rec/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt
0 → 100644
浏览文件 @
0b4106a6
===========================train_params===========================
model_name:PPOCRv2_ocr_rec
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=300
Global.save_model_dir:./output/
Train.loader.batch_size_per_card:lite_train_lite_infer=16|whole_train_whole_infer=128
Global.pretrained_model:null
train_model_name:latest
train_infer_img_dir:./inference/rec_inference
null:null
##
trainer:norm_train
norm_train:tools/train.py -c test_tipc/configs/ch_PP-OCRv2_rec/ch_PP-OCRv2_rec_distillation.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/ch_PP-OCRv2_rec/ch_PP-OCRv2_rec_distillation.yml -o
quant_export:
fpgm_export:
distill_export:null
export1:null
export2:null
inference_dir:Student
infer_model:./inference/ch_PP-OCRv2_rec_infer
infer_export:null
infer_quant:False
inference:tools/infer/predict_rec.py
--use_gpu:True|False
--enable_mkldnn:True|False
--cpu_threads:1|6
--rec_batch_num:1|6
--use_tensorrt:False|True
--precision:fp32|int8
--rec_model_dir:
--image_dir:./inference/rec_inference
null:null
--benchmark:True
null:null
===========================infer_benchmark_params==========================
random_infer_input:[{float32,[3,32,320]}]
test_tipc/configs/ch_PP-OCRv2_rec_PACT/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt
0 → 100644
浏览文件 @
0b4106a6
===========================train_params===========================
model_name:ch_PPOCRv2_rec_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=3|whole_train_whole_infer=300
Global.save_model_dir:./output/
Train.loader.batch_size_per_card:lite_train_lite_infer=16|whole_train_whole_infer=128
Global.pretrained_model:null
train_model_name:latest
train_infer_img_dir:./inference/rec_inference
null:null
##
trainer:pact_train
norm_train:null
pact_train:deploy/slim/quantization/quant.py -c test_tipc/configs/ch_PP-OCRv2_rec/ch_PP-OCRv2_rec_distillation.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/ch_PP-OCRv2_rec/ch_PP-OCRv2_rec_distillation.yml -o
fpgm_export: null
distill_export:null
export1:null
export2:null
inference_dir:Student
infer_model:./inference/ch_PP-OCRv2_rec_slim_quant_infer
infer_export:null
infer_quant:True
inference:tools/infer/predict_rec.py
--use_gpu:True|False
--enable_mkldnn:True|False
--cpu_threads:1|6
--rec_batch_num:1|6
--use_tensorrt:False|True
--precision:fp32|int8
--rec_model_dir:
--image_dir:./inference/rec_inference
null:null
--benchmark:True
null:null
===========================infer_benchmark_params==========================
random_infer_input:[{float32,[3,32,320]}]
test_tipc/configs/ch_ppocr_mobile_v2.0_det/det_mv3_db.yml
已删除
100644 → 0
浏览文件 @
b0e18544
Global
:
use_gpu
:
false
epoch_num
:
5
log_smooth_window
:
20
print_batch_step
:
1
save_model_dir
:
./output/db_mv3/
save_epoch_step
:
1200
# evaluation is run every 2000 iterations
eval_batch_step
:
[
0
,
400
]
cal_metric_during_train
:
False
pretrained_model
:
./pretrain_models/MobileNetV3_large_x0_5_pretrained
checkpoints
:
save_inference_dir
:
use_visualdl
:
False
infer_img
:
doc/imgs_en/img_10.jpg
save_res_path
:
./output/det_db/predicts_db.txt
Architecture
:
model_type
:
det
algorithm
:
DB
Transform
:
Backbone
:
name
:
MobileNetV3
scale
:
0.5
model_name
:
large
disable_se
:
False
Neck
:
name
:
DBFPN
out_channels
:
256
Head
:
name
:
DBHead
k
:
50
Loss
:
name
:
DBLoss
balance_loss
:
true
main_loss_type
:
DiceLoss
alpha
:
5
beta
:
10
ohem_ratio
:
3
Optimizer
:
name
:
Adam
#Momentum
#momentum: 0.9
beta1
:
0.9
beta2
:
0.999
lr
:
learning_rate
:
0.001
regularizer
:
name
:
'
L2'
factor
:
0
PostProcess
:
name
:
DBPostProcess
thresh
:
0.3
box_thresh
:
0.6
max_candidates
:
1000
unclip_ratio
:
1.5
Metric
:
name
:
DetMetric
main_indicator
:
hmean
Train
:
dataset
:
name
:
SimpleDataSet
data_dir
:
./train_data/icdar2015/text_localization/
label_file_list
:
-
./train_data/icdar2015/text_localization/train_icdar2015_label.txt
ratio_list
:
[
1.0
]
transforms
:
-
DecodeImage
:
# load image
img_mode
:
BGR
channel_first
:
False
-
DetLabelEncode
:
# Class handling label
-
Resize
:
size
:
[
640
,
640
]
-
MakeBorderMap
:
shrink_ratio
:
0.4
thresh_min
:
0.3
thresh_max
:
0.7
-
MakeShrinkMap
:
shrink_ratio
:
0.4
min_text_size
:
8
-
NormalizeImage
:
scale
:
1./255.
mean
:
[
0.485
,
0.456
,
0.406
]
std
:
[
0.229
,
0.224
,
0.225
]
order
:
'
hwc'
-
ToCHWImage
:
-
KeepKeys
:
keep_keys
:
[
'
image'
,
'
threshold_map'
,
'
threshold_mask'
,
'
shrink_map'
,
'
shrink_mask'
]
# the order of the dataloader list
loader
:
shuffle
:
False
drop_last
:
False
batch_size_per_card
:
1
num_workers
:
0
use_shared_memory
:
False
Eval
:
dataset
:
name
:
SimpleDataSet
data_dir
:
./train_data/icdar2015/text_localization/
label_file_list
:
-
./train_data/icdar2015/text_localization/test_icdar2015_label.txt
transforms
:
-
DecodeImage
:
# load image
img_mode
:
BGR
channel_first
:
False
-
DetLabelEncode
:
# Class handling label
-
DetResizeForTest
:
image_shape
:
[
736
,
1280
]
-
NormalizeImage
:
scale
:
1./255.
mean
:
[
0.485
,
0.456
,
0.406
]
std
:
[
0.229
,
0.224
,
0.225
]
order
:
'
hwc'
-
ToCHWImage
:
-
KeepKeys
:
keep_keys
:
[
'
image'
,
'
shape'
,
'
polys'
,
'
ignore_tags'
]
loader
:
shuffle
:
False
drop_last
:
False
batch_size_per_card
:
1
# must be 1
num_workers
:
0
use_shared_memory
:
False
test_tipc/configs/ch_ppocr_mobile_v2.0_det/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt
浏览文件 @
0b4106a6
===========================train_params===========================
model_name:
ocr
_det
model_name:
ch_ppocr_mobile_v2.0
_det
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=300
Global.epoch_num:lite_train_lite_infer=1
00
|whole_train_whole_infer=300
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
...
...
@@ -12,10 +12,10 @@ train_model_name:latest
train_infer_img_dir:./train_data/icdar2015/text_localization/ch4_test_images/
null:null
##
trainer:norm_train
|pact_train|fpgm_train
norm_train:tools/train.py -c
test_tipc/configs/ppocr_det_mobile/det_mv3_db
.yml -o Global.pretrained_model=./pretrain_models/MobileNetV3_large_x0_5_pretrained
pact_train:
deploy/slim/quantization/quant.py -c test_tipc/configs/ppocr_det_mobile/det_mv3_db.yml -o
fpgm_train:
deploy/slim/prune/sensitivity_anal.py -c test_tipc/configs/ppocr_det_mobile/det_mv3_db.yml -o Global.pretrained_model=./pretrain_models/det_mv3_db_v2.0_train/best_accuracy
trainer:norm_train
norm_train:tools/train.py -c
configs/det/ch_ppocr_v2.0/ch_det_mv3_db_v2.0
.yml -o Global.pretrained_model=./pretrain_models/MobileNetV3_large_x0_5_pretrained
pact_train:
null
fpgm_train:
null
distill_train:null
null:null
null:null
...
...
@@ -26,10 +26,10 @@ null:null
##
===========================infer_params===========================
Global.save_inference_dir:./output/
Global.
pretrained_model
:
norm_export:tools/export_model.py -c
test_tipc/configs/ppocr_det_mobile/det_mv3_db
.yml -o
quant_export:
deploy/slim/quantization/export_model.py -c test_tipc/configs/ppocr_det_mobile/det_mv3_db.yml -o
fpgm_export:
deploy/slim/prune/export_prune_model.py -c test_tipc/configs/ppocr_det_mobile/det_mv3_db.yml -o
Global.
checkpoints
:
norm_export:tools/export_model.py -c
configs/det/ch_ppocr_v2.0/ch_det_mv3_db_v2.0
.yml -o
quant_export:
null
fpgm_export:
null
distill_export:null
export1:null
export2:null
...
...
@@ -49,3 +49,5 @@ inference:tools/infer/predict_det.py
null:null
--benchmark:True
null:null
===========================infer_benchmark_params==========================
random_infer_input:[{float32,[3,640,640]}];[{float32,[3,960,960]}]
\ No newline at end of file
test_tipc/configs/ch_ppocr_mobile_
V
2.0_det_FPGM/train_infer_python.txt
→
test_tipc/configs/ch_ppocr_mobile_
v
2.0_det_FPGM/train_infer_python.txt
浏览文件 @
0b4106a6
===========================train_params===========================
model_name:
ocr_det
model_name:
ch_ppocr_mobile_v2.0_det_FPGM
python:python3.7
gpu_list:0|0,1
Global.use_gpu:True|True
...
...
test_tipc/configs/ch_ppocr_mobile_v2.0_det_FPGM/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt
0 → 100644
浏览文件 @
0b4106a6
===========================train_params===========================
model_name:ch_ppocr_mobile_v2.0_det_FPGM
python:python3.7
gpu_list:0|0,1
Global.use_gpu:True|True
Global.auto_cast:amp
Global.epoch_num:lite_train_lite_infer=5|whole_train_whole_infer=300
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
train_model_name:latest
train_infer_img_dir:./train_data/icdar2015/text_localization/ch4_test_images/
null:null
##
trainer:fpgm_train
norm_train:null
pact_train:null
fpgm_train:deploy/slim/prune/sensitivity_anal.py -c configs/det/ch_ppocr_v2.0/ch_det_mv3_db_v2.0.yml -o Global.pretrained_model=./pretrain_models/det_mv3_db_v2.0_train/best_accuracy
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:null
fpgm_export:deploy/slim/prune/export_prune_model.py -c configs/det/ch_ppocr_v2.0/ch_det_mv3_db_v2.0.yml -o
distill_export:null
export1:null
export2:null
inference_dir:null
train_model:null
infer_export:null
infer_quant:False
inference:tools/infer/predict_det.py
--use_gpu:True|False
--enable_mkldnn:True|False
--cpu_threads:1|6
--rec_batch_num:1
--use_tensorrt:False|True
--precision:fp32|fp16|int8
--det_model_dir:
--image_dir:./inference/ch_det_data_50/all-sum-510/
null:null
--benchmark:True
null:null
===========================infer_benchmark_params==========================
random_infer_input:[{float32,[3,640,640]}];[{float32,[3,960,960]}]
\ No newline at end of file
test_tipc/configs/ch_ppocr_mobile_v2.0_det_PACT/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt
0 → 100644
浏览文件 @
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===========================train_params===========================
model_name:ch_ppocr_mobile_v2.0_det_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=20|whole_train_whole_infer=300
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
train_model_name:latest
train_infer_img_dir:./train_data/icdar2015/text_localization/ch4_test_images/
null:null
##
trainer:pact_train
norm_train:null
pact_train:deploy/slim/quantization/quant.py -c configs/det/ch_ppocr_v2.0/ch_det_mv3_db_v2.0.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 configs/det/ch_ppocr_v2.0/ch_det_mv3_db_v2.0.yml -o
fpgm_export:null
distill_export:null
export1:null
export2:null
inference_dir:null
train_model:./inference/ch_ppocr_mobile_v2.0_det_prune_infer/
infer_export:null
infer_quant:False
inference:tools/infer/predict_det.py
--use_gpu:True|False
--enable_mkldnn:True|False
--cpu_threads:1|6
--rec_batch_num:1
--use_tensorrt:False|True
--precision:fp32|fp16|int8
--det_model_dir:
--image_dir:./inference/ch_det_data_50/all-sum-510/
null:null
--benchmark:True
null:null
===========================infer_benchmark_params==========================
random_infer_input:[{float32,[3,640,640]}];[{float32,[3,960,960]}]
test_tipc/configs/ch_ppocr_mobile_v2.0_rec/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt
0 → 100644
浏览文件 @
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===========================train_params===========================
model_name:ch_ppocr_mobile_v2.0_rec
python:python3.7
gpu_list:0|0,1
Global.use_gpu:True|True
Global.auto_cast:amp
Global.epoch_num:lite_train_lite_infer=2|whole_train_whole_infer=300
Global.save_model_dir:./output/
Train.loader.batch_size_per_card:lite_train_lite_infer=128|whole_train_whole_infer=128
Global.pretrained_model:null
train_model_name:latest
train_infer_img_dir:./inference/rec_inference
null:null
##
trainer:norm_train
norm_train:tools/train.py -c configs/rec/rec_icdar15_train.yml -o
pact_train:null
fpgm_train:null
distill_train:null
null:null
null:null
##
===========================eval_params===========================
eval:tools/eval.py -c configs/rec/rec_icdar15_train.yml -o
null:null
##
===========================infer_params===========================
Global.save_inference_dir:./output/
Global.checkpoints:
norm_export:tools/export_model.py -c configs/rec/rec_icdar15_train.yml -o
quant_export:null
fpgm_export:null
distill_export:null
export1:null
export2:null
##
train_model:./inference/ch_ppocr_mobile_v2.0_rec_train/best_accuracy
infer_export:tools/export_model.py -c configs/rec/rec_icdar15_train.yml -o
infer_quant:False
inference:tools/infer/predict_rec.py
--use_gpu:True|False
--enable_mkldnn:True|False
--cpu_threads:1|6
--rec_batch_num:1|6
--use_tensorrt:True|False
--precision:fp32|int8
--rec_model_dir:
--image_dir:./inference/rec_inference
--save_log_path:./test/output/
--benchmark:True
null:null
===========================infer_benchmark_params==========================
random_infer_input:[{float32,[3,32,100]}]
test_tipc/configs/ch_ppocr_mobile_v2.0_rec_FPGM/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt
0 → 100644
浏览文件 @
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===========================train_params===========================
model_name:ch_ppocr_mobile_v2.0_rec_FPGM
python:python3.7
gpu_list:0
Global.use_gpu:True|True
Global.auto_cast:amp
Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=300
Global.save_model_dir:./output/
Train.loader.batch_size_per_card:lite_train_lite_infer=128|whole_train_whole_infer=128
Global.pretrained_model:null
train_model_name:latest
train_infer_img_dir:./train_data/ic15_data/test/word_1.png
null:null
##
trainer:fpgm_train
norm_train:null
pact_train:null
fpgm_train:deploy/slim/prune/sensitivity_anal.py -c test_tipc/configs/ch_ppocr_mobile_v2.0_rec_FPGM/rec_chinese_lite_train_v2.0.yml -o Global.pretrained_model=./pretrain_models/ch_ppocr_mobile_v2.0_rec_train/best_accuracy
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:null
fpgm_export:deploy/slim/prune/export_prune_model.py -c test_tipc/configs/ch_ppocr_mobile_v2.0_rec_FPGM/rec_chinese_lite_train_v2.0.yml -o
distill_export:null
export1:null
export2:null
inference_dir:null
train_model:null
infer_export:null
infer_quant:False
inference:tools/infer/predict_rec.py
--use_gpu:True|False
--enable_mkldnn:True|False
--cpu_threads:1|6
--rec_batch_num:1
--use_tensorrt:False|True
--precision:fp32|int8
--rec_model_dir:
--image_dir:./inference/rec_inference
null:null
--benchmark:True
null:null
===========================infer_benchmark_params==========================
random_infer_input:[{float32,[3,32,320]}]
\ No newline at end of file
test_tipc/configs/ch_ppocr_mobile_v2.0_rec_PACT/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt
0 → 100644
浏览文件 @
0b4106a6
===========================train_params===========================
model_name:ch_ppocr_mobile_v2.0_rec_PACT
python:python3.7
gpu_list:0
Global.use_gpu:True|True
Global.auto_cast:amp
Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=300
Global.save_model_dir:./output/
Train.loader.batch_size_per_card:lite_train_lite_infer=128|whole_train_whole_infer=128
Global.checkpoints:null
train_model_name:latest
train_infer_img_dir:./train_data/ic15_data/test/word_1.png
null:null
##
trainer:pact_train
norm_train:null
pact_train:deploy/slim/quantization/quant.py -c test_tipc/configs/ch_ppocr_mobile_v2.0_rec_PACT/rec_chinese_lite_train_v2.0.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/ch_ppocr_mobile_v2.0_rec_PACT/rec_chinese_lite_train_v2.0.yml -o
fpgm_export:null
distill_export:null
export1:null
export2:null
inference_dir:null
infer_model:./inference/ch_ppocr_mobile_v2.0_rec_slim_infer/
infer_export:null
infer_quant:False
inference:tools/infer/predict_rec.py --rec_char_dict_path=./ppocr/utils/ppocr_keys_v1.txt --rec_image_shape="3,32,100"
--use_gpu:True|False
--enable_mkldnn:True|False
--cpu_threads:1|6
--rec_batch_num:1|6
--use_tensorrt:False|True
--precision:fp32|int8
--rec_model_dir:
--image_dir:./inference/rec_inference
--save_log_path:./test/output/
--benchmark:True
null:null
===========================infer_benchmark_params==========================
random_infer_input:[{float32,[3,32,320]}]
test_tipc/configs/ch_ppocr_server_v2.0_det/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt
0 → 100644
浏览文件 @
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===========================train_params===========================
model_name:ch_ppocr_server_v2.0_det
python:python3.7
gpu_list:0|0,1
Global.use_gpu:True|True
Global.auto_cast:amp
Global.epoch_num:lite_train_lite_infer=2|whole_train_whole_infer=300
Global.save_model_dir:./output/
Train.loader.batch_size_per_card:lite_train_lite_infer=2|whole_train_lite_infer=4
Global.pretrained_model:null
train_model_name:latest
train_infer_img_dir:./train_data/icdar2015/text_localization/ch4_test_images/
null:null
##
trainer:norm_train
norm_train:tools/train.py -c test_tipc/configs/ch_ppocr_server_v2.0_det/det_r50_vd_db.yml -o
quant_train:null
fpgm_train:null
distill_train:null
null:null
null:null
##
===========================eval_params===========================
eval:tools/eval.py -c test_tipc/configs/ch_ppocr_server_v2.0_det/det_r50_vd_db.yml -o
null:null
##
===========================infer_params===========================
Global.save_inference_dir:./output/
Global.checkpoints:
norm_export:tools/export_model.py -c test_tipc/configs/ch_ppocr_server_v2.0_det/det_r50_vd_db.yml -o
quant_export:null
fpgm_export:null
distill_export:null
export1:null
export2:null
##
train_model:./inference/ch_ppocr_server_v2.0_det_train/best_accuracy
infer_export:tools/export_model.py -c configs/det/ch_ppocr_v2.0/ch_det_res18_db_v2.0.yml -o
infer_quant:False
inference:tools/infer/predict_det.py
--use_gpu:True|False
--enable_mkldnn:True|False
--cpu_threads:1|6
--rec_batch_num:1
--use_tensorrt:False|True
--precision:fp32|fp16|int8
--det_model_dir:
--image_dir:./inference/ch_det_data_50/all-sum-510/
--save_log_path:null
--benchmark:True
null:null
===========================infer_benchmark_params==========================
random_infer_input:[{float32,[3,640,640]}];[{float32,[3,960,960]}]
\ No newline at end of file
test_tipc/configs/ch_ppocr_server_v2.0_rec/train_linux_gpu_normal_amp_infer_python_linux_gpu_cpu.txt
0 → 100644
浏览文件 @
0b4106a6
===========================train_params===========================
model_name:ch_ppocr_server_v2.0_rec
python:python3.7
gpu_list:0|0,1
Global.use_gpu:True|True
Global.auto_cast:amp
Global.epoch_num:lite_train_lite_infer=5|whole_train_whole_infer=100
Global.save_model_dir:./output/
Train.loader.batch_size_per_card:lite_train_lite_infer=128|whole_train_whole_infer=128
Global.pretrained_model:null
train_model_name:latest
train_infer_img_dir:./inference/rec_inference
null:null
##
trainer:norm_train
norm_train:tools/train.py -c test_tipc/configs/ch_ppocr_server_v2.0_rec/rec_icdar15_train.yml -o
pact_train:null
fpgm_train:null
distill_train:null
null:null
null:null
##
===========================eval_params===========================
eval:tools/eval.py -c test_tipc/configs/ch_ppocr_server_v2.0_rec/rec_icdar15_train.yml -o
null:null
##
===========================infer_params===========================
Global.save_inference_dir:./output/
Global.checkpoints:
norm_export:tools/export_model.py -c test_tipc/configs/ch_ppocr_server_v2.0_rec/rec_icdar15_train.yml -o
quant_export:null
fpgm_export:null
distill_export:null
export1:null
export2:null
##
train_model:./inference/ch_ppocr_server_v2.0_rec_train/best_accuracy
infer_export:tools/export_model.py -c test_tipc/configs/ch_ppocr_server_v2.0_rec/rec_icdar15_train.yml -o
infer_quant:False
inference:tools/infer/predict_rec.py
--use_gpu:True|False
--enable_mkldnn:True|False
--cpu_threads:1|6
--rec_batch_num:1|6
--use_tensorrt:True|False
--precision:fp32|int8
--rec_model_dir:
--image_dir:./inference/rec_inference
--save_log_path:./test/output/
--benchmark:True
null:null
===========================infer_benchmark_params==========================
random_infer_input:[{float32,[3,32,100]}]
tools/eval.py
浏览文件 @
0b4106a6
...
...
@@ -74,8 +74,10 @@ def main():
model
=
build_model
(
config
[
'Architecture'
])
extra_input_models
=
[
"SRN"
,
"NRTR"
,
"SAR"
,
"SEED"
,
"SVTR"
]
extra_input
=
False
if
config
[
'Architecture'
][
'algorithm'
]
==
'Distillation'
:
extra_input
=
config
[
'Architecture'
][
'Models'
][
'Teacher'
][
for
key
in
config
[
'Architecture'
][
"Models"
]:
extra_input
=
extra_input
or
config
[
'Architecture'
][
'Models'
][
key
][
'algorithm'
]
in
extra_input_models
else
:
extra_input
=
config
[
'Architecture'
][
'algorithm'
]
in
extra_input_models
...
...
tools/infer/utility.py
浏览文件 @
0b4106a6
...
...
@@ -271,9 +271,10 @@ def create_predictor(args, mode, logger):
elif
mode
==
"rec"
:
if
args
.
rec_algorithm
!=
"CRNN"
:
use_dynamic_shape
=
False
min_input_shape
=
{
"x"
:
[
1
,
3
,
32
,
10
]}
max_input_shape
=
{
"x"
:
[
args
.
rec_batch_num
,
3
,
32
,
1536
]}
opt_input_shape
=
{
"x"
:
[
args
.
rec_batch_num
,
3
,
32
,
320
]}
imgH
=
int
(
args
.
rec_image_shape
.
split
(
','
)[
-
2
])
min_input_shape
=
{
"x"
:
[
1
,
3
,
imgH
,
10
]}
max_input_shape
=
{
"x"
:
[
args
.
rec_batch_num
,
3
,
imgH
,
1536
]}
opt_input_shape
=
{
"x"
:
[
args
.
rec_batch_num
,
3
,
imgH
,
320
]}
elif
mode
==
"cls"
:
min_input_shape
=
{
"x"
:
[
1
,
3
,
48
,
10
]}
max_input_shape
=
{
"x"
:
[
args
.
rec_batch_num
,
3
,
48
,
1024
]}
...
...
tools/program.py
浏览文件 @
0b4106a6
...
...
@@ -202,8 +202,10 @@ def train(config,
use_srn
=
config
[
'Architecture'
][
'algorithm'
]
==
"SRN"
extra_input_models
=
[
"SRN"
,
"NRTR"
,
"SAR"
,
"SEED"
,
"SVTR"
]
extra_input
=
False
if
config
[
'Architecture'
][
'algorithm'
]
==
'Distillation'
:
extra_input
=
config
[
'Architecture'
][
'Models'
][
'Teacher'
][
for
key
in
config
[
'Architecture'
][
"Models"
]:
extra_input
=
extra_input
or
config
[
'Architecture'
][
'Models'
][
key
][
'algorithm'
]
in
extra_input_models
else
:
extra_input
=
config
[
'Architecture'
][
'algorithm'
]
in
extra_input_models
...
...
编辑
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