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5dbd1b6e
编写于
12月 09, 2020
作者:
J
Jiawei Wang
提交者:
wangjiawei04
12月 10, 2020
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Merge pull request #917 from wangjiawei04/ocr_remove
rm ocr_detection dir
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python/examples/ocr_detection/7.jpg
python/examples/ocr_detection/7.jpg
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python/examples/ocr_detection/text_det_client.py
python/examples/ocr_detection/text_det_client.py
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# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
#
# 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
#
# 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.
import
os
from
paddle_serving_client
import
Client
from
paddle_serving_app.reader
import
Sequential
,
File2Image
,
ResizeByFactor
from
paddle_serving_app.reader
import
Div
,
Normalize
,
Transpose
from
paddle_serving_app.reader
import
DBPostProcess
,
FilterBoxes
client
=
Client
()
client
.
load_client_config
(
"ocr_det_client/serving_client_conf.prototxt"
)
client
.
connect
([
"127.0.0.1:9494"
])
read_image_file
=
File2Image
()
preprocess
=
Sequential
([
ResizeByFactor
(
32
,
960
),
Div
(
255
),
Normalize
([
0.485
,
0.456
,
0.406
],
[
0.229
,
0.224
,
0.225
]),
Transpose
(
(
2
,
0
,
1
))
])
post_func
=
DBPostProcess
({
"thresh"
:
0.3
,
"box_thresh"
:
0.5
,
"max_candidates"
:
1000
,
"unclip_ratio"
:
1.5
,
"min_size"
:
3
})
filter_func
=
FilterBoxes
(
10
,
10
)
img
=
read_image_file
(
name
)
ori_h
,
ori_w
,
_
=
img
.
shape
img
=
preprocess
(
img
)
new_h
,
new_w
,
_
=
img
.
shape
ratio_list
=
[
float
(
new_h
)
/
ori_h
,
float
(
new_w
)
/
ori_w
]
outputs
=
client
.
predict
(
feed
=
{
"image"
:
img
},
fetch
=
[
"concat_1.tmp_0"
])
dt_boxes_list
=
post_func
(
outputs
[
"concat_1.tmp_0"
],
[
ratio_list
])
dt_boxes
=
filter_func
(
dt_boxes_list
[
0
],
[
ori_h
,
ori_w
])
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