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Commit c98c5dd1 authored by Leif's avatar Leif
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Merge remote-tracking branch 'origin/dygraph' into dygraph

parents 063395ec 5ebf5d6e
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Showing with 686 additions and 39 deletions
ppocr/modeling/transforms/tps_spatial_transformer.py
View file @ c98c5dd1
......@@ -11,6 +11,10 @@
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
This code is refer from:
https://github.com/ayumiymk/aster.pytorch/blob/master/lib/models/tps_spatial_transformer.py
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
......
ppocr/postprocess/__init__.py
View file @ c98c5dd1
......@@ -18,7 +18,6 @@ from __future__ import print_function
from __future__ import unicode_literals
import copy
import platform
__all__ = ['build_post_process']
......@@ -26,21 +25,24 @@ from .db_postprocess import DBPostProcess, DistillationDBPostProcess
from .east_postprocess import EASTPostProcess
from .sast_postprocess import SASTPostProcess
from .rec_postprocess import CTCLabelDecode, AttnLabelDecode, SRNLabelDecode, DistillationCTCLabelDecode, \
TableLabelDecode, NRTRLabelDecode, SARLabelDecode , SEEDLabelDecode
TableLabelDecode, NRTRLabelDecode, SARLabelDecode, SEEDLabelDecode
from .cls_postprocess import ClsPostProcess
from .pg_postprocess import PGPostProcess
from .pse_postprocess import PSEPostProcess
def build_post_process(config, global_config=None):
support_dict = [
'DBPostProcess', 'PSEPostProcess', 'EASTPostProcess', 'SASTPostProcess',
'CTCLabelDecode', 'AttnLabelDecode', 'ClsPostProcess', 'SRNLabelDecode',
'PGPostProcess', 'DistillationCTCLabelDecode', 'TableLabelDecode',
'DBPostProcess', 'EASTPostProcess', 'SASTPostProcess', 'CTCLabelDecode',
'AttnLabelDecode', 'ClsPostProcess', 'SRNLabelDecode', 'PGPostProcess',
'DistillationCTCLabelDecode', 'TableLabelDecode',
'DistillationDBPostProcess', 'NRTRLabelDecode', 'SARLabelDecode',
'SEEDLabelDecode'
]
if config['name'] == 'PSEPostProcess':
from .pse_postprocess import PSEPostProcess
support_dict.append('PSEPostProcess')
config = copy.deepcopy(config)
module_name = config.pop('name')
if global_config is not None:
......
ppocr/postprocess/db_postprocess.py
View file @ c98c5dd1
......@@ -11,7 +11,10 @@
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
This code is refered from:
https://github.com/WenmuZhou/DBNet.pytorch/blob/master/post_processing/seg_detector_representer.py
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
......@@ -190,7 +193,8 @@ class DBPostProcess(object):
class DistillationDBPostProcess(object):
def __init__(self, model_name=["student"],
def __init__(self,
model_name=["student"],
key=None,
thresh=0.3,
box_thresh=0.6,
......@@ -201,12 +205,13 @@ class DistillationDBPostProcess(object):
**kwargs):
self.model_name = model_name
self.key = key
self.post_process = DBPostProcess(thresh=thresh,
box_thresh=box_thresh,
max_candidates=max_candidates,
unclip_ratio=unclip_ratio,
use_dilation=use_dilation,
score_mode=score_mode)
self.post_process = DBPostProcess(
thresh=thresh,
box_thresh=box_thresh,
max_candidates=max_candidates,
unclip_ratio=unclip_ratio,
use_dilation=use_dilation,
score_mode=score_mode)
def __call__(self, predicts, shape_list):
results = {}
......
ppocr/postprocess/locality_aware_nms.py
View file @ c98c5dd1
"""
Locality aware nms.
This code is refered from: https://github.com/songdejia/EAST/blob/master/locality_aware_nms.py
"""
import numpy as np
......
ppocr/postprocess/pse_postprocess/pse/README.md
View file @ c98c5dd1
## 编译
code from https://github.com/whai362/pan_pp.pytorch
This code is refer from:
https://github.com/whai362/PSENet/blob/python3/models/post_processing/pse
```python
python3 setup.py build_ext --inplace
```
ppocr/postprocess/pse_postprocess/pse/__init__.py
View file @ c98c5dd1
......@@ -21,8 +21,9 @@ ori_path = os.getcwd()
os.chdir('ppocr/postprocess/pse_postprocess/pse')
if subprocess.call(
'{} setup.py build_ext --inplace'.format(python_path), shell=True) != 0:
raise RuntimeError('Cannot compile pse: {}'.format(
os.path.dirname(os.path.realpath(__file__))))
raise RuntimeError(
'Cannot compile pse: {}, if your system is windows, you need to install all the default components of `desktop development using C++` in visual studio 2019+'.
format(os.path.dirname(os.path.realpath(__file__))))
os.chdir(ori_path)
from .pse import pse
ppocr/postprocess/pse_postprocess/pse_postprocess.py
View file @ c98c5dd1
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
# copyright (c) 2021 PaddlePaddle Authors. All Rights Reserve.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
This code is refer from:
https://github.com/whai362/PSENet/blob/python3/models/head/psenet_head.py
"""
from __future__ import absolute_import
from __future__ import division
......@@ -47,7 +51,8 @@ class PSEPostProcess(object):
pred = outs_dict['maps']
if not isinstance(pred, paddle.Tensor):
pred = paddle.to_tensor(pred)
pred = F.interpolate(pred, scale_factor=4 // self.scale, mode='bilinear')
pred = F.interpolate(
pred, scale_factor=4 // self.scale, mode='bilinear')
score = F.sigmoid(pred[:, 0, :, :])
......@@ -60,7 +65,9 @@ class PSEPostProcess(object):
boxes_batch = []
for batch_index in range(pred.shape[0]):
boxes, scores = self.boxes_from_bitmap(score[batch_index], kernels[batch_index], shape_list[batch_index])
boxes, scores = self.boxes_from_bitmap(score[batch_index],
kernels[batch_index],
shape_list[batch_index])
boxes_batch.append({'points': boxes, 'scores': scores})
return boxes_batch
......@@ -98,15 +105,14 @@ class PSEPostProcess(object):
mask = np.zeros((box_height, box_width), np.uint8)
mask[points[:, 1], points[:, 0]] = 255
contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_SIMPLE)
bbox = np.squeeze(contours[0], 1)
else:
raise NotImplementedError
bbox[:, 0] = np.clip(
np.round(bbox[:, 0] / ratio_w), 0, src_w)
bbox[:, 1] = np.clip(
np.round(bbox[:, 1] / ratio_h), 0, src_h)
bbox[:, 0] = np.clip(np.round(bbox[:, 0] / ratio_w), 0, src_w)
bbox[:, 1] = np.clip(np.round(bbox[:, 1] / ratio_h), 0, src_h)
boxes.append(bbox)
scores.append(score_i)
return boxes, scores
ppocr/utils/iou.py
View file @ c98c5dd1
# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve.
# copyright (c) 2021 PaddlePaddle Authors. All Rights Reserve.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
......@@ -11,18 +11,23 @@
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
This code is refer from:
https://github.com/whai362/PSENet/blob/python3/models/loss/iou.py
"""
import paddle
EPS = 1e-6
def iou_single(a, b, mask, n_class):
valid = mask == 1
a = a.masked_select(valid)
b = b.masked_select(valid)
miou = []
for i in range(n_class):
if a.shape == [0] and a.shape==b.shape:
if a.shape == [0] and a.shape == b.shape:
inter = paddle.to_tensor(0.0)
union = paddle.to_tensor(0.0)
else:
......@@ -32,6 +37,7 @@ def iou_single(a, b, mask, n_class):
miou = sum(miou) / len(miou)
return miou
def iou(a, b, mask, n_class=2, reduce=True):
batch_size = a.shape[0]
......@@ -39,10 +45,10 @@ def iou(a, b, mask, n_class=2, reduce=True):
b = b.reshape([batch_size, -1])
mask = mask.reshape([batch_size, -1])
iou = paddle.zeros((batch_size,), dtype='float32')
iou = paddle.zeros((batch_size, ), dtype='float32')
for i in range(batch_size):
iou[i] = iou_single(a[i], b[i], mask[i], n_class)
if reduce:
iou = paddle.mean(iou)
return iou
\ No newline at end of file
return iou
ppocr/utils/logging.py
View file @ c98c5dd1
# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve.
# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
......@@ -11,6 +11,10 @@
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
This code is refer from:
https://github.com/WenmuZhou/PytorchOCR/blob/master/torchocr/utils/logging.py
"""
import os
import sys
......
test_tipc/configs/amp_ppocr_det_mobile_params.txt 0 → 100644
View file @ c98c5dd1
===========================train_params===========================
model_name:ocr_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.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|pact_train|fpgm_train
norm_train:tools/train.py -c test_tipc/configs/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/det_mv3_db.yml -o
fpgm_train:deploy/slim/prune/sensitivity_anal.py -c test_tipc/configs/det_mv3_db.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.pretrained_model:
norm_export:tools/export_model.py -c test_tipc/configs/det_mv3_db.yml -o
quant_export:deploy/slim/quantization/export_model.py -c test_tipc/configs/det_mv3_db.yml -o
fpgm_export:deploy/slim/prune/export_prune_model.py -c test_tipc/configs/det_mv3_db.yml -o
distill_export:null
export1:null
export2:null
inference_dir:null
train_model:./inference/ch_ppocr_mobile_v2.0_det_train/best_accuracy
infer_export:tools/export_model.py -c configs/det/ch_ppocr_v2.0/ch_det_mv3_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/
null:null
--benchmark:True
null:null
===========================cpp_infer_params===========================
use_opencv:True
infer_model:./inference/ch_ppocr_mobile_v2.0_det_infer/
infer_quant:False
inference:./deploy/cpp_infer/build/ppocr det
--use_gpu:True|False
--enable_mkldnn:True|False
--cpu_threads:1|6
--rec_batch_num:1
--use_tensorrt:False|True
--precision:fp32|fp16
--det_model_dir:
--image_dir:./inference/ch_det_data_50/all-sum-510/
null:null
--benchmark:True
===========================serving_params===========================
model_name:ocr_det
python:python3.7
trans_model:-m paddle_serving_client.convert
--dirname:./inference/ch_ppocr_mobile_v2.0_det_infer/
--model_filename:inference.pdmodel
--params_filename:inference.pdiparams
--serving_server:./deploy/pdserving/ppocr_det_mobile_2.0_serving/
--serving_client:./deploy/pdserving/ppocr_det_mobile_2.0_client/
serving_dir:./deploy/pdserving
web_service:web_service_det.py --config=config.yml --opt op.det.concurrency=1
op.det.local_service_conf.devices:null|0
op.det.local_service_conf.use_mkldnn:True|False
op.det.local_service_conf.thread_num:1|6
op.det.local_service_conf.use_trt:False|True
op.det.local_service_conf.precision:fp32|fp16|int8
pipline:pipeline_http_client.py --image_dir=../../doc/imgs
===========================kl_quant_params===========================
infer_model:./inference/ch_ppocr_mobile_v2.0_det_infer/
infer_export:tools/export_model.py -c configs/det/ch_ppocr_v2.0/ch_det_mv3_db_v2.0.yml -o
infer_quant:True
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:int8
--det_model_dir:
--image_dir:./inference/ch_det_data_50/all-sum-510/
null:null
--benchmark:True
null:null
null:null
===========================lite_params===========================
inference:./ocr_db_crnn det
infer_model:./models/ch_ppocr_mobile_v2.0_det_opt.nb|./models/ch_ppocr_mobile_v2.0_det_slim_opt.nb
--cpu_threads:1|4
--batch_size:1
--power_mode:LITE_POWER_HIGH|LITE_POWER_LOW
--image_dir:./test_data/icdar2015_lite/text_localization/ch4_test_images/|./test_data/icdar2015_lite/text_localization/ch4_test_images/img_233.jpg
--config_dir:./config.txt
--rec_dict_dir:./ppocr_keys_v1.txt
--benchmark:True
test_tipc/configs/fleet_ppocr_det_mobile_params.txt 0 → 100644
View file @ c98c5dd1
===========================train_params===========================
model_name:ocr_det
python:python3.7
gpu_list:xx.xx.xx.xx,xx.xx.xx.xx;0,1
Global.use_gpu:True|True
Global.auto_cast:null|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=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|pact_train|fpgm_train
norm_train:tools/train.py -c test_tipc/configs/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/det_mv3_db.yml -o
fpgm_train:deploy/slim/prune/sensitivity_anal.py -c test_tipc/configs/det_mv3_db.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.pretrained_model:
norm_export:tools/export_model.py -c test_tipc/configs/det_mv3_db.yml -o
quant_export:deploy/slim/quantization/export_model.py -c test_tipc/configs/det_mv3_db.yml -o
fpgm_export:deploy/slim/prune/export_prune_model.py -c test_tipc/configs/det_mv3_db.yml -o
distill_export:null
export1:null
export2:null
inference_dir:null
train_model:./inference/ch_ppocr_mobile_v2.0_det_train/best_accuracy
infer_export:tools/export_model.py -c configs/det/ch_ppocr_v2.0/ch_det_mv3_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/
null:null
--benchmark:True
null:null
===========================cpp_infer_params===========================
use_opencv:True
infer_model:./inference/ch_ppocr_mobile_v2.0_det_infer/
infer_quant:False
inference:./deploy/cpp_infer/build/ppocr det
--use_gpu:True|False
--enable_mkldnn:True|False
--cpu_threads:1|6
--rec_batch_num:1
--use_tensorrt:False|True
--precision:fp32|fp16
--det_model_dir:
--image_dir:./inference/ch_det_data_50/all-sum-510/
null:null
--benchmark:True
===========================serving_params===========================
model_name:ocr_det
python:python3.7
trans_model:-m paddle_serving_client.convert
--dirname:./inference/ch_ppocr_mobile_v2.0_det_infer/
--model_filename:inference.pdmodel
--params_filename:inference.pdiparams
--serving_server:./deploy/pdserving/ppocr_det_mobile_2.0_serving/
--serving_client:./deploy/pdserving/ppocr_det_mobile_2.0_client/
serving_dir:./deploy/pdserving
web_service:web_service_det.py --config=config.yml --opt op.det.concurrency=1
op.det.local_service_conf.devices:null|0
op.det.local_service_conf.use_mkldnn:True|False
op.det.local_service_conf.thread_num:1|6
op.det.local_service_conf.use_trt:False|True
op.det.local_service_conf.precision:fp32|fp16|int8
pipline:pipeline_http_client.py --image_dir=../../doc/imgs
===========================kl_quant_params===========================
infer_model:./inference/ch_ppocr_mobile_v2.0_det_infer/
infer_export:tools/export_model.py -c configs/det/ch_ppocr_v2.0/ch_det_mv3_db_v2.0.yml -o
infer_quant:True
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:int8
--det_model_dir:
--image_dir:./inference/ch_det_data_50/all-sum-510/
null:null
--benchmark:True
null:null
null:null
===========================lite_params===========================
inference:./ocr_db_crnn det
infer_model:./models/ch_ppocr_mobile_v2.0_det_opt.nb|./models/ch_ppocr_mobile_v2.0_det_slim_opt.nb
--cpu_threads:1|4
--batch_size:1
--power_mode:LITE_POWER_HIGH|LITE_POWER_LOW
--image_dir:./test_data/icdar2015_lite/text_localization/ch4_test_images/|./test_data/icdar2015_lite/text_localization/ch4_test_images/img_233.jpg
--config_dir:./config.txt
--rec_dict_dir:./ppocr_keys_v1.txt
--benchmark:True
test_tipc/configs/jeston_ppocr_det_mobile_params.txt 0 → 100644
View file @ c98c5dd1
===========================train_params===========================
model_name:ocr_det
python:python
gpu_list:null
Global.use_gpu:null
Global.auto_cast:null
Global.epoch_num:null
Global.save_model_dir:null
Train.loader.batch_size_per_card:null
Global.pretrained_model:null
train_model_name:latest
train_infer_img_dir:null
null:null
##
trainer:null
norm_train:null
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.pretrained_model:null
norm_export:null
quant_export:null
fpgm_export:null
distill_export:null
export1:null
export2:null
inference_dir:null
train_model:./inference/ch_ppocr_mobile_v2.0_det_infer
infer_export:null
infer_quant:False
inference:tools/infer/predict_det.py
--use_gpu:True|False
--enable_mkldnn:False
--cpu_threads:1|6
--rec_batch_num:1
--use_tensorrt:False|True
--precision:fp16|fp32
--det_model_dir:
--image_dir:./inference/ch_det_data_50/all-sum-510/
null:null
--benchmark:True
null:null
test_tipc/configs/mac_ppocr_det_mobile_params.txt 0 → 100644
View file @ c98c5dd1
===========================train_params===========================
model_name:ocr_det
python:python
gpu_list:-1
Global.use_gpu:False
Global.auto_cast:null
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=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|pact_train|fpgm_train
norm_train:tools/train.py -c test_tipc/configs/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/det_mv3_db.yml -o
fpgm_train:deploy/slim/prune/sensitivity_anal.py -c test_tipc/configs/det_mv3_db.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.pretrained_model:
norm_export:tools/export_model.py -c test_tipc/configs/det_mv3_db.yml -o
quant_export:deploy/slim/quantization/export_model.py -c test_tipc/configs/det_mv3_db.yml -o
fpgm_export:deploy/slim/prune/export_prune_model.py -c test_tipc/configs/det_mv3_db.yml -o
distill_export:null
export1:null
export2:null
inference_dir:null
train_model:./inference/ch_ppocr_mobile_v2.0_det_train/best_accuracy
infer_export:tools/export_model.py -c configs/det/ch_ppocr_v2.0/ch_det_mv3_db_v2.0.yml -o
infer_quant:False
inference:tools/infer/predict_det.py
--use_gpu:False
--enable_mkldnn:False
--cpu_threads:1|6
--rec_batch_num:1
--use_tensorrt:False
--precision:fp32
--det_model_dir:
--image_dir:./inference/ch_det_data_50/all-sum-510/
null:null
--benchmark:True
null:null
===========================cpp_infer_params===========================
use_opencv:True
infer_model:./inference/ch_ppocr_mobile_v2.0_det_infer/
infer_quant:False
inference:./deploy/cpp_infer/build/ppocr det
--use_gpu:False
--enable_mkldnn:False
--cpu_threads:1|6
--rec_batch_num:1
--use_tensorrt:False
--precision:fp32
--det_model_dir:
--image_dir:./inference/ch_det_data_50/all-sum-510/
null:null
--benchmark:True
===========================serving_params===========================
model_name:ocr_det
python:python3.7
trans_model:-m paddle_serving_client.convert
--dirname:./inference/ch_ppocr_mobile_v2.0_det_infer/
--model_filename:inference.pdmodel
--params_filename:inference.pdiparams
--serving_server:./deploy/pdserving/ppocr_det_mobile_2.0_serving/
--serving_client:./deploy/pdserving/ppocr_det_mobile_2.0_client/
serving_dir:./deploy/pdserving
web_service:web_service_det.py --config=config.yml --opt op.det.concurrency=1
op.det.local_service_conf.devices:null|0
op.det.local_service_conf.use_mkldnn:True|False
op.det.local_service_conf.thread_num:1|6
op.det.local_service_conf.use_trt:False|True
op.det.local_service_conf.precision:fp32|fp16|int8
pipline:pipeline_http_client.py|pipeline_rpc_client.py
--image_dir=../../doc/imgs
===========================kl_quant_params===========================
infer_model:./inference/ch_ppocr_mobile_v2.0_det_infer/
infer_export:tools/export_model.py -c configs/det/ch_ppocr_v2.0/ch_det_mv3_db_v2.0.yml -o
infer_quant:True
inference:tools/infer/predict_det.py
--use_gpu:False
--enable_mkldnn:False
--cpu_threads:1|6
--rec_batch_num:1
--use_tensorrt:False
--precision:int8
--det_model_dir:
--image_dir:./inference/ch_det_data_50/all-sum-510/
null:null
--benchmark:True
null:null
null:null
test_tipc/configs/ppocr_det_mobile_params.txt
View file @ c98c5dd1
===========================train_params===========================
model_name:ocr_det
python:python3.7
gpu_list:0|0,1|10.21.226.181,10.21.226.133;0,1
Global.use_gpu:True|True|True
Global.auto_cast:fp32|amp
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=300
Global.save_model_dir:./output/
Train.loader.batch_size_per_card:lite_train_lite_infer=2|whole_train_whole_infer=4
......@@ -80,7 +80,8 @@ op.det.local_service_conf.use_mkldnn:True|False
op.det.local_service_conf.thread_num:1|6
op.det.local_service_conf.use_trt:False|True
op.det.local_service_conf.precision:fp32|fp16|int8
pipline:pipeline_http_client.py --image_dir=../../doc/imgs
pipline:pipeline_rpc_client.py|pipeline_http_client.py
--image_dir:../../doc/imgs
===========================kl_quant_params===========================
infer_model:./inference/ch_ppocr_mobile_v2.0_det_infer/
infer_export:tools/export_model.py -c configs/det/ch_ppocr_v2.0/ch_det_mv3_db_v2.0.yml -o
......@@ -108,3 +109,15 @@ infer_model:./models/ch_ppocr_mobile_v2.0_det_opt.nb|./models/ch_ppocr_mobile_v2
--config_dir:./config.txt
--rec_dict_dir:./ppocr_keys_v1.txt
--benchmark:True
===========================paddle2onnx_params===========================
2onnx: paddle2onnx
--model_dir:./inference/ch_ppocr_mobile_v2.0_det_infer/
--model_filename:inference.pdmodel
--params_filename:inference.pdiparams
--save_file:./inference/det_mobile_onnx/model.onnx
--opset_version:10
--enable_onnx_checker:True
inference:tools/infer/predict_det.py
--use_gpu:False
--det_model_dir:
--image_dir:./inference/ch_det_data_50/all-sum-510/
\ No newline at end of file
test_tipc/configs/ppocr_det_server_params.txt
View file @ c98c5dd1
......@@ -80,4 +80,5 @@ op.det.local_service_conf.use_mkldnn:True|False
op.det.local_service_conf.thread_num:1|6
op.det.local_service_conf.use_trt:False|True
op.det.local_service_conf.precision:fp32|fp16|int8
pipline:pipeline_http_client.py --image_dir=../../doc/imgs
pipline:pipeline_http_client.py|pipeline_rpc_client.py
--image_dir=../../doc/imgs
test_tipc/configs/ppocr_rec_mobile_params.txt
View file @ c98c5dd1
......@@ -80,4 +80,5 @@ op.rec.local_service_conf.use_mkldnn:True|False
op.rec.local_service_conf.thread_num:1|6
op.rec.local_service_conf.use_trt:False|True
op.rec.local_service_conf.precision:fp32|fp16|int8
pipline:pipeline_http_client.py --image_dir=../../doc/imgs_words_en
pipline:pipeline_http_client.py|pipeline_rpc_client.py
--image_dir=../../doc/imgs_words_en
test_tipc/configs/ppocr_rec_server_params.txt
View file @ c98c5dd1
......@@ -80,4 +80,5 @@ op.rec.local_service_conf.use_mkldnn:True|False
op.rec.local_service_conf.thread_num:1|6
op.rec.local_service_conf.use_trt:False|True
op.rec.local_service_conf.precision:fp32|fp16|int8
pipline:pipeline_http_client.py --image_dir=../../doc/imgs_words_en
pipline:pipeline_http_client.py|pipeline_rpc_client.py
--image_dir=../../doc/imgs_words_en
test_tipc/configs/win_ppocr_det_mobile_params.txt 0 → 100644
View file @ c98c5dd1
===========================train_params===========================
model_name:ocr_det
python:python
gpu_list:0
Global.use_gpu:True
Global.auto_cast:fp32|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=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|pact_train|fpgm_train
norm_train:tools/train.py -c test_tipc/configs/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/det_mv3_db.yml -o
fpgm_train:deploy/slim/prune/sensitivity_anal.py -c test_tipc/configs/det_mv3_db.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.pretrained_model:
norm_export:tools/export_model.py -c test_tipc/configs/det_mv3_db.yml -o
quant_export:deploy/slim/quantization/export_model.py -c test_tipc/configs/det_mv3_db.yml -o
fpgm_export:deploy/slim/prune/export_prune_model.py -c test_tipc/configs/det_mv3_db.yml -o
distill_export:null
export1:null
export2:null
inference_dir:null
train_model:./inference/ch_ppocr_mobile_v2.0_det_train/best_accuracy
infer_export:tools/export_model.py -c configs/det/ch_ppocr_v2.0/ch_det_mv3_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/
null:null
--benchmark:True
null:null
===========================cpp_infer_params===========================
use_opencv:True
infer_model:./inference/ch_ppocr_mobile_v2.0_det_infer/
infer_quant:False
inference:./deploy/cpp_infer/build/ppocr det
--use_gpu:True|False
--enable_mkldnn:True|False
--cpu_threads:1|6
--rec_batch_num:1
--use_tensorrt:False|True
--precision:fp32|fp16
--det_model_dir:
--image_dir:./inference/ch_det_data_50/all-sum-510/
null:null
--benchmark:True
===========================serving_params===========================
model_name:ocr_det
python:python3.7
trans_model:-m paddle_serving_client.convert
--dirname:./inference/ch_ppocr_mobile_v2.0_det_infer/
--model_filename:inference.pdmodel
--params_filename:inference.pdiparams
--serving_server:./deploy/pdserving/ppocr_det_mobile_2.0_serving/
--serving_client:./deploy/pdserving/ppocr_det_mobile_2.0_client/
serving_dir:./deploy/pdserving
web_service:web_service_det.py --config=config.yml --opt op.det.concurrency=1
op.det.local_service_conf.devices:null|0
op.det.local_service_conf.use_mkldnn:True|False
op.det.local_service_conf.thread_num:1|6
op.det.local_service_conf.use_trt:False|True
op.det.local_service_conf.precision:fp32|fp16|int8
pipline:pipeline_http_client.py|pipeline_rpc_client.py
--image_dir=../../doc/imgs
===========================kl_quant_params===========================
infer_model:./inference/ch_ppocr_mobile_v2.0_det_infer/
infer_export:tools/export_model.py -c configs/det/ch_ppocr_v2.0/ch_det_mv3_db_v2.0.yml -o
infer_quant:True
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:int8
--det_model_dir:
--image_dir:./inference/ch_det_data_50/all-sum-510/
null:null
--benchmark:True
null:null
null:null
===========================lite_params===========================
inference:./ocr_db_crnn det
infer_model:./models/ch_ppocr_mobile_v2.0_det_opt.nb|./models/ch_ppocr_mobile_v2.0_det_slim_opt.nb
--cpu_threads:1|4
--batch_size:1
--power_mode:LITE_POWER_HIGH|LITE_POWER_LOW
--image_dir:./test_data/icdar2015_lite/text_localization/ch4_test_images/|./test_data/icdar2015_lite/text_localization/ch4_test_images/img_233.jpg
--config_dir:./config.txt
--rec_dict_dir:./ppocr_keys_v1.txt
--benchmark:True
test_tipc/docs/jeston_test_train_inference_python.md 0 → 100644
View file @ c98c5dd1
# Jeston端基础训练预测功能测试
Jeston端基础训练预测功能测试的主程序为`test_train_inference_python.sh`，由于Jeston端CPU较差，Jeston只需要测试TIPC关于GPU和TensorRT预测推理的部分即可。
## 1. 测试结论汇总
- 预测相关：基于训练是否使用量化，可以将训练产出的模型可以分为`正常模型`和`量化模型`，这两类模型对应的预测功能汇总如下：
| 模型类型 |device | batchsize | tensorrt | mkldnn | cpu多线程 |
| ---- | ---- | ---- | :----: | :----: | :----: |
| 正常模型 | GPU | 1/6 | fp32/fp16 | - | - |
| 量化模型 | GPU | 1/6 | int8 | - | - |
## 2. 测试流程
环境准备只需要Python环境即可，安装PaddlePaddle等依赖参考下述文档。
### 2.1 安装依赖
- 安装PaddlePaddle >= 2.0
- 安装PaddleOCR依赖
```
pip install -r ../requirements.txt
```
- 安装autolog（规范化日志输出工具）
```
git clone https://github.com/LDOUBLEV/AutoLog
cd AutoLog
pip install -r requirements.txt
python setup.py bdist_wheel
pip install ./dist/auto_log-1.0.0-py3-none-any.whl
cd ../
```
- 安装PaddleSlim (可选)
```
# 如果要测试量化、裁剪等功能，需要安装PaddleSlim
pip install paddleslim
```
### 2.2 功能测试
先运行`prepare.sh`准备数据和模型，然后运行`test_train_inference_python.sh`进行测试，最终在```test_tipc/output```目录下生成`python_infer_*.log`格式的日志文件。
`test_train_inference_python.sh`包含5种[运行模式](./test_train_inference_python.md)，在Jeston端，仅需要测试预测推理的模式即可：
```
- 模式3：whole_infer，不训练，全量数据预测，走通开源模型评估、动转静，检查inference model预测时间和精度;
```shell
bash test_tipc/prepare.sh ./test_tipc/configs/mac_ppocr_det_mobile_params.txt 'whole_infer'
# 用法1:
bash test_tipc/test_train_inference_python.sh ./test_tipc/configs/jeston_ppocr_det_mobile_params.txt 'whole_infer'
# 用法2: 指定GPU卡预测，第三个传入参数为GPU卡号
bash test_tipc/test_train_inference_python.sh ./test_tipc/configs/jeston_ppocr_det_mobile_params.txt 'whole_infer' '1'
```
运行相应指令后，在`test_tipc/output`文件夹下自动会保存运行日志。如`lite_train_lite_infer`模式下，会运行训练+inference的链条，因此，在`test_tipc/output`文件夹有以下文件：
```
test_tipc/output/
|- results_python.log # 运行指令状态的日志
|- python_infer_gpu_usetensorrt_True_precision_fp32_batchsize_1.log # GPU上开启TensorRT，batch_size=1条件下的预测运行日志
......
```
其中`results_python.log`中包含了每条指令的运行状态，如果运行成功会输出：
```
Run successfully with command - python tools/infer/predict_det.py --use_gpu=True --use_tensorrt=False --precision=fp32 --det_model_dir=./inference/ch_ppocr_mobile_v2.0_det_infer/ --rec_batch_num=1 --image_dir=./inference/ch_det_data_50/all-sum-510/ --benchmark=True > ./test_tipc/output/python_infer_gpu_usetrt_False_precision_fp32_batchsize_1.log 2>&1 !
Run successfully with command - python tools/infer/predict_det.py --use_gpu=True --use_tensorrt=True --precision=fp32 --det_model_dir=./inference/ch_ppocr_mobile_v2.0_det_infer/ --rec_batch_num=1 --image_dir=./inference/ch_det_data_50/all-sum-510/ --benchmark=True > ./test_tipc/output/python_infer_gpu_usetrt_True_precision_fp32_batchsize_1.log 2>&1 !
Run successfully with command - python tools/infer/predict_det.py --use_gpu=True --use_tensorrt=True --precision=fp16 --det_model_dir=./inference/ch_ppocr_mobile_v2.0_det_infer/ --rec_batch_num=1 --image_dir=./inference/ch_det_data_50/all-sum-510/ --benchmark=True > ./test_tipc/output/python_infer_gpu_usetrt_True_precision_fp16_batchsize_1.log 2>&1 !
```
如果运行失败，会输出：
```
Run failed with command - python tools/infer/predict_det.py --use_gpu=True --use_tensorrt=False --precision=fp32 --det_model_dir=./inference/ch_ppocr_mobile_v2.0_det_infer/ --rec_batch_num=1 --image_dir=./inference/ch_det_data_50/all-sum-510/ --benchmark=True > ./test_tipc/output/python_infer_gpu_usetrt_False_precision_fp32_batchsize_1.log 2>&1 !
Run failed with command - python tools/infer/predict_det.py --use_gpu=True --use_tensorrt=True --precision=fp32 --det_model_dir=./inference/ch_ppocr_mobile_v2.0_det_infer/ --rec_batch_num=1 --image_dir=./inference/ch_det_data_50/all-sum-510/ --benchmark=True > ./test_tipc/output/python_infer_gpu_usetrt_True_precision_fp32_batchsize_1.log 2>&1 !
Run failed with command - python tools/infer/predict_det.py --use_gpu=True --use_tensorrt=True --precision=fp16 --det_model_dir=./inference/ch_ppocr_mobile_v2.0_det_infer/ --rec_batch_num=1 --image_dir=./inference/ch_det_data_50/all-sum-510/ --benchmark=True > ./test_tipc/output/python_infer_gpu_usetrt_True_precision_fp16_batchsize_1.log 2>&1 !
```
可以很方便的根据`results_python.log`中的内容判定哪一个指令运行错误。
### 2.3 精度测试
使用compare_results.py脚本比较模型预测的结果是否符合预期，主要步骤包括：
- 提取日志中的预测坐标；
- 从本地文件中提取保存好的坐标结果；
- 比较上述两个结果是否符合精度预期，误差大于设置阈值时会报错。
#### 使用方式
运行命令：
```shell
python test_tipc/compare_results.py --gt_file=./test_tipc/results/python_*.txt --log_file=./test_tipc/output/python_*.log --atol=1e-3 --rtol=1e-3
```
参数介绍：
- gt_file： 指向事先保存好的预测结果路径，支持*.txt 结尾，会自动索引*.txt格式的文件，文件默认保存在test_tipc/result/ 文件夹下
- log_file: 指向运行test_tipc/test_train_inference_python.sh 脚本的infer模式保存的预测日志，预测日志中打印的有预测结果，比如：文本框，预测文本，类别等等，同样支持python_infer_*.log格式传入
- atol: 设置的绝对误差
- rtol: 设置的相对误差
#### 运行结果
正常运行效果如下：
```
Assert allclose passed! The results of python_infer_gpu_usetrt_True_precision_fp32_batchsize_1.log and ./test_tipc/results/python_ppocr_det_mobile_results_fp32.txt are consistent!
```
出现不一致结果时的运行输出：
```
......
Traceback (most recent call last):
File "test_tipc/compare_results.py", line 140, in <module>
format(filename, gt_filename))
ValueError: The results of python_infer_gpu_usetrt_True_precision_fp32_batchsize_1.log and the results of ./test_tipc/results/python_ppocr_det_mobile_results_fp32.txt are inconsistent!
```
## 3. 更多教程
本文档为功能测试用，更丰富的训练预测使用教程请参考：
[模型训练](https://github.com/PaddlePaddle/PaddleOCR/blob/dygraph/doc/doc_ch/training.md)
[基于Python预测引擎推理](https://github.com/PaddlePaddle/PaddleOCR/blob/dygraph/doc/doc_ch/inference.md)
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