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c4492e2b
编写于
5月 19, 2021
作者:
J
Jiawei Wang
提交者:
GitHub
5月 19, 2021
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差异文件
Merge pull request #1252 from HexToString/v0.6.0
修复jiawei bug v0.6.0
上级
73df4d53
4950b25e
变更
3
隐藏空白更改
内联
并排
Showing
3 changed file
with
57 addition
and
2 deletion
+57
-2
doc/PADDLE_SERVING_ON_KUBERNETES.md
doc/PADDLE_SERVING_ON_KUBERNETES.md
+1
-1
python/examples/pipeline/PaddleClas/ResNet_V2_50/pipeline_http_client.py
.../pipeline/PaddleClas/ResNet_V2_50/pipeline_http_client.py
+17
-1
python/examples/pipeline/PaddleClas/ResNet_V2_50/pipeline_rpc_client.py
...s/pipeline/PaddleClas/ResNet_V2_50/pipeline_rpc_client.py
+39
-0
未找到文件。
doc/PADDLE_SERVING_ON_KUBERNETES.md
浏览文件 @
c4492e2b
...
@@ -25,7 +25,7 @@ kubectl apply -f https://bit.ly/kong-ingress-dbless
...
@@ -25,7 +25,7 @@ kubectl apply -f https://bit.ly/kong-ingress-dbless
在
`tools/generate_runtime_docker.sh`
文件下,它的使用方式如下
在
`tools/generate_runtime_docker.sh`
文件下,它的使用方式如下
```
bash
```
bash
bash tool/generate_runtime_docker.sh
--env
cuda10.1
--python
3.6
--serving
0.6.0
--paddle
2.0.1
--name
serving_runtime:cuda10.1-py36
bash tool
s
/generate_runtime_docker.sh
--env
cuda10.1
--python
3.6
--serving
0.6.0
--paddle
2.0.1
--name
serving_runtime:cuda10.1-py36
```
```
会生成 cuda10.1,python 3.6,serving版本0.6.0 还有 paddle版本2.0.1的运行镜像。如果有其他疑问,可以执行下列语句得到帮助信息。
会生成 cuda10.1,python 3.6,serving版本0.6.0 还有 paddle版本2.0.1的运行镜像。如果有其他疑问,可以执行下列语句得到帮助信息。
...
...
python/examples/pipeline/PaddleClas/ResNet_V2_50/pipeline_http_client.py
浏览文件 @
c4492e2b
# Copyright (c) 2021 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
numpy
as
np
import
numpy
as
np
import
requests
import
requests
import
json
import
json
...
@@ -5,11 +19,13 @@ import cv2
...
@@ -5,11 +19,13 @@ import cv2
import
base64
import
base64
import
os
import
os
def
cv2_to_base64
(
image
):
def
cv2_to_base64
(
image
):
return
base64
.
b64encode
(
image
).
decode
(
'utf8'
)
return
base64
.
b64encode
(
image
).
decode
(
'utf8'
)
if
__name__
==
"__main__"
:
if
__name__
==
"__main__"
:
url
=
"http://127.0.0.1:180
0
0/imagenet/prediction"
url
=
"http://127.0.0.1:180
8
0/imagenet/prediction"
with
open
(
os
.
path
.
join
(
"."
,
"daisy.jpg"
),
'rb'
)
as
file
:
with
open
(
os
.
path
.
join
(
"."
,
"daisy.jpg"
),
'rb'
)
as
file
:
image_data1
=
file
.
read
()
image_data1
=
file
.
read
()
image
=
cv2_to_base64
(
image_data1
)
image
=
cv2_to_base64
(
image_data1
)
...
...
python/examples/pipeline/PaddleClas/ResNet_V2_50/pipeline_rpc_client.py
0 → 100644
浏览文件 @
c4492e2b
# 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.
try
:
from
paddle_serving_server_gpu.pipeline
import
PipelineClient
except
ImportError
:
from
paddle_serving_server.pipeline
import
PipelineClient
import
numpy
as
np
import
requests
import
json
import
cv2
import
base64
import
os
client
=
PipelineClient
()
client
.
connect
([
'127.0.0.1:9993'
])
def
cv2_to_base64
(
image
):
return
base64
.
b64encode
(
image
).
decode
(
'utf8'
)
with
open
(
"daisy.jpg"
,
'rb'
)
as
file
:
image_data
=
file
.
read
()
image
=
cv2_to_base64
(
image_data
)
for
i
in
range
(
1
):
ret
=
client
.
predict
(
feed_dict
=
{
"image"
:
image
},
fetch
=
[
"label"
,
"prob"
])
print
(
ret
)
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