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百度智能云智能边缘 - 通过BIE部署Paddle Serving

文档简介:
1 前言: Paddle Serving依托深度学习框架PaddlePaddle,旨在帮助深度学习开发者和企业提供高性能、灵活易用的工业级在线推理服务。Paddle Serving 作为飞桨的服务化部署框架,长期目标就是为人工智能落地的最后一公里提供越来越专业、可靠、易用的服务。
*此产品及展示信息均由百度智能云官方提供。免费试用 咨询热线:400-826-7010,为您提供专业的售前咨询,让您快速了解云产品,助您轻松上云! 微信咨询
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1 前言

Paddle Serving依托深度学习框架PaddlePaddle,旨在帮助深度学习开发者和企业提供高性能、灵活易用的工业级在线推理服务。Paddle Serving 作为飞桨的服务化部署框架,长期目标就是为人工智能落地的最后一公里提供越来越专业、可靠、易用的服务。

本文重点介绍,如果借助百度智能边缘BIE,将Paddle Serving部署至边缘节点。

Paddle Serving文档可以参考github官网,本文主要参考官网文档重新组织以后撰写。

2 实验设备

本文所使用的实验设备是一台x86架构的ubuntu 18.04虚拟机,不依赖GPU。

3 模型文件准备

  1. 在宿主机上下载Paddle Serving代码
git clone https://github.com/PaddlePaddle/Serving.git
  1. 下载模型,参考文档点击此处


# 进入到yolov3实例模型目录 cd Serving/examples/Pipeline/PaddleDetection/yolov3
/ # 下载模型 wget --no-check-certificate https://paddle-serving.bj.bcebos.com
/pddet_demo/2.0/yolov3_darknet53_270e_coco.tar # 解压模型 tar xf yolov3_darkne
t53_270e_coco.tar # 解压以后删除模型压缩包 rm -r yolov3_darknet53_270e_coco.tar


  1. 制作模型压缩包


cd Serving/examples/Pipeline/PaddleDetection/yolov3/
压缩当前目录下的文件 zip -r paddle_serving_yolov3_darknet53_270e_coco.zip ./*
 # 查看md5 md5sum paddle_serving_yolov3_darknet53_270e_coco.zip 
7a2ca27f2f444c6ac169d19922ff89ab  paddle_serving_yolov3_darknet53_270e_coco.zip


  1. 将模型上传到bos

4 Paddle Serving镜像准备

  1. 下载Paddle Serving开发镜像
docker pull registry.baidubce.com/paddlepaddle/serving:0.7.0-devel
  1. 运行Paddle Serving开发镜像
docker run --rm -dit --name pipeline_serving_demo registry.baidubce.com/paddlepaddle/serving:0.7.0-devel bash
  1. Paddle Serving开发镜像当中安装依赖程序


# 进入容器 docker exec -it pipeline_serving_demo bash # 下载代码 git clone https://github.co
m/PaddlePaddle/Serving.git # 进入Paddle Serving代码目录 cd Serving # 安装依赖 pip3 install -r
 python/requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple # CPU环境安装内容如下
 # 安装Paddle Serving pip3 install paddle-serving-client==0.7.0 -i https://pypi.tuna.tsinghua.edu.cn/simple
pip3 install paddle-serving-server==0.7.0 -i https://pypi.tuna.tsinghua.edu.cn/simple 
pip3 install paddle-serving-app==0.7.0 -i https://pypi.tuna.tsinghua.edu.cn/simple
 # 安装Paddle相关Python库 pip3 install paddlepaddle==2.2.0


加上 -i https://pypi.tuna.tsinghua.edu.cn/simple 表示使用国内源,提升下载速度,非必须,可以不加。

  1. 提交镜像,固化上面的安装内容
docker commit pipeline_serving_demo paddle_serving:0.7.0-cpu-py36

这里将我制作的镜像推送到了百度公有云CCR,可以直接下载使用

docker pull registry.baidubce.com/pp/paddle-serving:0.7.0-cpu-py36

5 模型应用创建

5.1 创建模型文件配置项

  1. 创建配置项paddle-yolov3-model
  2. 点击引入文件

    • 类型:HTTP
    • URL:https://bie-document.gz.bcebos.com/paddlepaddle/paddle_serving_yolov3_darknet53_270e_coco.zip
    • 文件名称:paddle_serving_yolov3_darknet53_270e_coco.zip
    • 是否解压:

5.2 创建启动脚本配置项

  1. 创建配置项paddle-yolov3-run-script
  2. 添加配置数据如下

    • 变量名:run.sh
    • 变量值:如下述代码
#! /usr/bin/env bash cd /home/work/yolov3
python3 web_service.py

5.3 创建paddle-serving应用并挂载配置

  1. 创建应用paddle-serving

  1. 配置服务

    • 基础信息:

      • 名称:paddle-serving
      • 镜像:paddle-serving:0.7.0-cpu-py36
    • 卷配置:

      • /home/work/script:运行脚本位置,与启动参数一致
      • /home/work/yolov3:模型位置,与运行脚本一致
    • 启动参数

      • /bin/bash
      • /home/work/script/run.sh,与前面的卷配置一致

5.4 使用导入方式创建配置项与应用

BIE的配置项与应用支持导入方式创建,应用依赖配置项,所以需要先导入配置项再导入应用。整体导入流程如下:

  1. 进入配置管理,点击导入配置项,依次导入以下2个配置项

    • 配置项-paddle-yolov3-model.json
    • 配置项-paddle-yolov3-run-script.json
  2. 进入应用部署菜单,点击导入应用,导入以下应用

    • 应用-paddle-serving.json

6 模型应用部署

  1. 进入到paddle-serving
  2. 定位到目标节点,点击单节点匹配,选择目标节点paddle-serving-test。等待几分钟,部署状态将变为已部署

  1. 进入边缘节点,可以查看服务在边缘测的运行状态,如下图所示:

7 测试验证

7.1使用paddle-serving-client验证

  1. ssh登录边缘节点
  2. 查看边缘节点BIE应用状态
kubectl get pod -n baetyl-edge
NAME                             READY   STATUS    RESTARTS   AGE
paddle-serving-dd6d8986c-d89k7 1/1     Running 0 3m7s
  1. 进入边缘容器


kubectl exec -it paddle-serving-dd6d8986c-d89k7 -n baetyl-edge /bin/bash # 进去以后,
工作目录为/home λ paddle-serving-dd6d8986c-d89k7 /home # 查看/home/work目录,检查云端
模型是否下发成功 λ paddle-serving-dd6d8986c-d89k7 /home/work cd /home/work/
λ paddle-serving-dd6d8986c-d89k7 /home/work ls script/  yolov3/


  1. 执行测试命令


# 进入yolov3目录 λ paddle-serving-dd6d8986c-d89k7 /home/work/yolov3 cd /home/work/yolov3
/ # 查看内容 λ paddle-serving-dd6d8986c-d89k7 /home/work/yolov3 ls -l
total 221M
-rw-rw-r-- 1 root root 136K Dec 17 09:21 000000570688.jpg
-rw-rw-r-- 1 root root 509 Dec 17 09:21 benchmark_config.yaml
-rw-rw-r-- 1 root root 4.2K Dec 17 09:21 benchmark.py
-rw-rw-r-- 1 root root 2.1K Dec 17 09:21 benchmark.sh
-rw-rw-r-- 1 root root 1.5K Dec 17 09:21 config.yml
-rw-rw-r-- 1 root root 621 Dec 17 09:21 label_list.txt
-rwxr-xr-x 1 root root 220M Dec 17 09:21 paddle_serving_yolov3_darknet53_270e_coco.zip
-rw-rw-r-- 1 root root 1.2K Dec 17 09:21 pipeline_http_client.py
drwxr-xr-x 2 root root 4.0K Dec 17 09:26 PipelineServingLogs/
-rw-r--r-- 1 root root 89 Dec 17 09:26 ProcessInfo.json
-rw-rw-r-- 1 root root 368 Dec 17 09:21 README_CN.md
-rw-rw-r-- 1 root root 374 Dec 17 09:21 README.md
drwxr-xr-x 2 root root 4.0K Dec 17 09:21 serving_client/
drwxr-xr-x 2 root root 4.0K Dec 17 09:21 serving_server/
-rw-rw-r-- 1 root root 2.8K Dec 17 09:21 web_service.py
λ paddle-serving-dd6d8986c-d89k7 /home/work/yolov3 python3 # 执行客户端测试脚本 pipeline_http_client.py


返回结果如下:


{ 'err_no': 0, 'err_msg': '', 'key': ['bbox_result'], 'value': ["[{'category_id': 0, 'bbox':
 [215.16099548339844, 438.1199951171875, 43.29920959472656, 186.94189453125], 'score': 0.9860
591292381287}, {'category_id': 0, 'bbox': [404.882568359375, 463.1432800292969, 50.0075073242
1875, 174.96109008789062], 'score': 0.972165584564209}, {'category_id': 0, 'bbox': [259.8436
279296875, 458.67169189453125, 47.04876708984375, 154.5758056640625], 'score': 0.9670743346
214294}, {'category_id': 0, 'bbox': [438.247314453125, 491.875, 68.9227294921875, 145.54821
77734375], 'score': 0.9092186689376831}, {'category_id': 0, 'bbox': [156.2906951904297, 50
5.449951171875, 57.74359130859375, 55.9661865234375], 'score': 0.7775811553001404}, {'cate
gory_id': 0, 'bbox': [28.40601921081543, 451.0614318847656, 27.93486213684082, 113.3091735
8398438], 'score': 0.768792986869812}, {'category_id': 0, 'bbox': [297.4198303222656, 511.
6090087890625, 59.18255615234375, 76.463134765625], 'score': 0.7284609079360962}, {'categor
y_id': 0, 'bbox': [498.0811767578125, 504.2102966308594, 35.239501953125, 134.7639465332031
2], 'score': 0.6112859845161438}, {'category_id': 0, 'bbox': [522.001708984375, 479.5540466
308594, 63.42236328125, 156.11416625976562], 'score': 0.5191890001296997}, {'category_id':
 0, 'bbox': [139.90167236328125, 483.0037841796875, 21.444671630859375, 69.7462158203125],
 'score': 0.43779468536376953}, {'category_id': 0, 'bbox': [91.08878326416016, 494.51797485
35156, 27.569290161132812, 55.932159423828125], 'score': 0.4112253189086914}, {'category_id
: 0, 'bbox': [9.615033149719238, 462.5943908691406, 21.810187339782715, 82.98226928710938],
 'score': 0.3453913629055023}, {'category_id': 0, 'bbox': [395.7669372558594, 460.096923828
125, 13.82818603515625, 51.9017333984375], 'score': 0.30560365319252014}, {'category_id': 0
, 'bbox': [120.70891571044922, 496.8610534667969, 25.293846130371094, 54.288909912109375], 
'score': 0.21395830810070038}, {'category_id': 0, 'bbox': [595.8244018554688, 466.675811767
5781, 6.93212890625, 22.802978515625], 'score': 0.212965726852417}, {'category_id': 0, 'bb
ox': [624.6640625, 466.89288330078125, 6.6031494140625, 23.390869140625], 'score': 0.130935
4156255722}, {'category_id': 0, 'bbox': [71.72364807128906, 493.44171142578125, 23.063659667
96875, 58.178955078125], 'score': 0.11486723273992538}, {'category_id': 0, 'bbox': [93.52797
69897461, 494.7836608886719, 18.048110961914062, 29.617156982421875], 'score': 0.097386419
7731018}, {'category_id': 0, 'bbox': [633.90625, 466.93377685546875, 5.08349609375, 22.5412
59765625], 'score': 0.08928193151950836}, {'category_id': 0, 'bbox': [616.2327880859375, 4
67.5227966308594, 6.6636962890625, 22.73602294921875], 'score': 0.07480660825967789}, {'ca
tegory_id': 0, 'bbox': [330.21514892578125, 460.61785888671875, 14.3568115234375, 50.36322
021484375], 'score': 0.05391114205121994}, {'category_id': 0, 'bbox': [623.5628662109375,
 521.3399047851562, 15.6580810546875, 118.66009521484375], 'score': 0.05177609249949455},
 {'category_id': 0, 'bbox': [118.22535705566406, 493.11846923828125, 15.311538696289062, 
46.67529296875], 'score': 0.05106724426150322}, {'category_id': 0, 'bbox': [76.891639709
47266, 489.4934997558594, 14.865859985351562, 36.153900146484375], 'score': 0.0509687103
331089}, {'category_id': 0, 'bbox': [612.2092895507812, 466.2706604003906, 6.8411865234
375, 24.82183837890625], 'score': 0.04965047165751457}, {'category_id': 0, 'bbox': [45
9.98687744140625, 466.3093566894531, 11.68914794921875, 34.41339111328125], 'score': 0.
04907878115773201}, {'category_id': 0, 'bbox': [0.4039268493652344, 462.4938049316406, 
10.412893295288086, 61.628326416015625], 'score': 0.048166826367378235}, {'category_id
': 0, 'bbox': [163.0106201171875, 501.29864501953125, 14.077667236328125, 28.660278320
3125], 'score': 0.043710850179195404}, {'category_id': 0, 'bbox': [42.41417694091797,
 456.0679626464844, 17.12506103515625, 96.23989868164062], 'score': 0.0435817278921604
16}, {'category_id': 0, 'bbox': [124.59736633300781, 495.2655029296875, 14.957061767578
125, 29.24896240234375], 'score': 0.032280560582876205}, {'category_id': 0, 'bbox': [3
22.8830261230469, 510.5441589355469, 35.19915771484375, 58.528839111328125], 'score': 
0.032096412032842636}, {'category_id': 0, 'bbox': [499.7272644042969, 472.070159912109
4, 6.73431396484375, 23.52752685546875], 'score': 0.03191200643777847}, {'category_id'
: 0, 'bbox': [635.601318359375, 472.9556579589844, 4.2603759765625, 17.8453369140625], 
'score': 0.03138304129242897}, {'category_id': 0, 'bbox': [13.47295093536377, 509.236
5417480469, 17.922499656677246, 59.210113525390625], 'score': 0.024998517706990242},
 {'category_id': 0, 'bbox': [492.8521728515625, 474.7392883300781, 5.19732666015625,
 15.8018798828125], 'score': 0.02452804334461689}, {'category_id': 0, 'bbox': [141.
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506.34857177734375, 30.214935302734375, 69.9669189453125], 'score': 0.0141529720276594
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11.3291015625], 'score': 0.05771809071302414}, {'category_id': 2, 'bbox': [492.967529
296875, 461.03411865234375, 16.8121337890625, 11.01202392578125], 'score': 0.05025568
2319402695}, {'category_id': 2, 'bbox': [566.1650390625, 461.9089050292969, 14.287353
515625, 11.1707763671875], 'score': 0.04679763689637184}, {'category_id': 2, 'bbox': 
[582.1019287109375, 463.1806335449219, 11.535888671875, 9.76470947265625], 'score': 
0.03930026665329933}, {'category_id': 2, 'bbox': [573.3811645507812, 463.0304260253906,
 15.5157470703125, 9.6693115234375], 'score': 0.03414313867688179}, {'category_id': 
2, 'bbox': [600.5574951171875, 462.50701904296875, 7.7860107421875, 8.21221923828125],
 'score': 0.025939688086509705}, {'category_id': 2, 'bbox': [486.56951904296875, 463
.8977966308594, 12.2598876953125, 7.6630859375], 'score': 0.022135090082883835}, {'
category_id': 25, 'bbox': [437.3040466308594, 545.1283569335938, 38.20965576171875, 
87.29931640625], 'score': 0.018933355808258057}, {'category_id': 26, 'bbox': [29.908
803939819336, 486.8944396972656, 16.05537223815918, 22.83355712890625], 'score': 0.04
068344458937645}, {'category_id': 26, 'bbox': [581.0633544921875, 620.1477661132812, 3
2.0316162109375, 18.63525390625], 'score': 0.039497870951890945}, {'category_id': 26, 
'bbox': [385.1318359375, 517.0343017578125, 18.244873046875, 13.5072021484375], 'score
': 0.02217845804989338}, {'category_id': 26, 'bbox': [590.1017456054688, 559.3590698242
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d': 26, 'bbox': [582.7347412109375, 560.3289184570312, 26.631103515625, 76.627319335937
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61548}, {'category_id': 33, 'bbox': [175.90914916992188, 314.95672607421875, 79.74258422
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2533874511719, 261.376708984375, 18.829742431640625, 24.36407470703125], 'score': 0.81371
03915214539}, {'category_id': 33, 'bbox': [328.5792236328125, 86.0416030883789, 61.033752
44140625, 27.46881103515625], 'score': 0.8071057796478271}, {'category_id': 33, 'bbox': [3
63.2680358886719, 161.7618865966797, 12.36090087890625, 10.89990234375], 'score': 0.804425
1203536987}, {'category_id': 33, 'bbox': [222.79953002929688, 350.03302001953125, 162.1348
2666015625, 79.5477294921875], 'score': 0.7996627688407898}, {'category_id': 33, 'bbox': 
[279.99066162109375, 124.66069030761719, 45.8681640625, 16.145660400390625], 'score': 0.
7842240333557129}, {'category_id': 33, 'bbox': [98.05622100830078, 419.7298889160156, 65.
67034149169922, 62.50732421875], 'score': 0.7424381971359253}, {'category_id': 33, 'bbox':
 [242.89645385742188, 166.64027404785156, 20.291900634765625, 14.35076904296875], 'score': 
0.6263655424118042}, {'category_id': 33, 'bbox': [430.3121643066406, 40.18694305419922, 18.
87353515625, 19.074172973632812], 'score': 0.5938690304756165}, {'category_id': 33, 'bbox':
 [86.46560668945312, 137.0863800048828, 48.230865478515625, 19.82879638671875], 'score': 
0.5937690734863281}, {'category_id': 33, 'bbox': [392.02850341796875, 394.45611572265625, 
26.37896728515625, 23.63372802734375], 'score': 0.5023226141929626}, {'category_id': 33, 
'bbox': [271.4128112792969, 299.25018310546875, 149.4326171875, 59.794921875], 'score':
 0.422481894493103}, {'category_id': 33, 'bbox': [282.4754638671875, 281.77496337890625,
 164.82354736328125, 56.41583251953125], 'score': 0.4141545295715332}, {'category_id': 33,
 'bbox': [114.94490051269531, 237.0370330810547, 22.510589599609375, 17.687591552734375], 
'score': 0.40582510828971863}, {'category_id': 33, 'bbox': [160.378173828125, 257.062255
859375, 10.08685302734375, 8.29095458984375], 'score': 0.3285631537437439}, {'category_id'
: 33, 'bbox': [260.0093994140625, 44.60060501098633, 4.9671630859375, 5.313697814941406],
 'score': 0.28955695033073425}, {'category_id': 33, 'bbox': [216.726318359375, 238.367248
53515625, 180.0245361328125, 60.68719482421875], 'score': 0.25094327330589294}, {'category
_id': 33, 'bbox': [58.31337356567383, 340.7672424316406, 7.575717926025391, 5.219543457031
25], 'score': 0.2317829728126526}, {'category_id': 33, 'bbox': [2.293954849243164, 424.198
5778808594, 17.95143699645996, 10.4171142578125], 'score': 0.21052710711956024}, {'category
_id': 33, 'bbox': [281.1366271972656, 130.51866149902344, 8.10662841796875, 9.6792907714843
75], 'score': 0.13495559990406036}, {'category_id': 33, 'bbox': [170.76100158691406, 425.66
9677734375, 60.928955078125, 52.55987548828125], 'score': 0.11672469973564148}, {'category_
id': 33, 'bbox': [218.16445922851562, 236.66871643066406, 86.7357177734375, 36.82264709472
656], 'score': 0.09928663074970245}, {'category_id': 33, 'bbox': [57.59531021118164, 340.6
3653564453125, 11.535961151123047, 10.2398681640625], 'score': 0.09524064511060715}, {'cat
egory_id': 33, 'bbox': [83.4229736328125, 300.5054626464844, 4.1660614013671875, 3.5161132
8125], 'score': 0.05346690118312836}, {'category_id': 33, 'bbox': [85.83900451660156, 137.
0255584716797, 7.1644134521484375, 8.851104736328125], 'score': 0.044692330062389374}, {'ca
tegory_id': 33, 'bbox': [412.9825744628906, 38.167327880859375, 32.94921875, 45.05966949462
8906], 'score': 0.04101773351430893}, {'category_id': 33, 'bbox': [596.8782958984375, 1.069
2591667175293, 35.0404052734375, 10.813299655914307], 'score': 0.03720707818865776}, {'cate
gory_id': 33, 'bbox': [218.40847778320312, 239.14697265625, 37.585540771484375, 23.4786682
12890625], 'score': 0.03472490981221199}, {'category_id': 33, 'bbox': [22.163543701171875,
 430.1997985839844, 15.829334259033203, 46.72674560546875], 'score': 0.03383627161383629},
 {'category_id': 33, 'bbox': [51.58473205566406, 443.5025939941406, 30.812210083007812, 35.
05010986328125], 'score': 0.028524775058031082}, {'category_id': 33, 'bbox': [436.84979248
046875, 541.2200927734375, 41.42523193359375, 93.6231689453125], 'score': 0.0165852420032
0244}, {'category_id': 33, 'bbox': [577.9300537109375, 0.0, 54.505859375, 48.9048156738281
25], 'score': 0.016126543283462524}, {'category_id': 33, 'bbox': [3.094654083251953, 438.2
5445556640625, 20.415660858154297, 28.048095703125], 'score': 0.014082299545407295}, {'ca
tegory_id': 56, 'bbox': [567.2755126953125, 559.4602661132812, 37.1573486328125, 77.500488
28125], 'score': 0.3802623450756073}, {'category_id': 56, 'bbox': [72.8006820678711, 514.7
3583984375, 21.915634155273438, 37.716796875], 'score': 0.08133123815059662}, {'category_i
d': 56, 'bbox': [508.6803283691406, 559.0682373046875, 93.95669555664062, 78.7860107421875
], 'score': 0.06216099485754967}, {'category_id': 56, 'bbox': [174.71974182128906, 497.6105
95703125, 17.5482177734375, 22.37078857421875], 'score': 0.04738868027925491}, {'category_
id': 56, 'bbox': [90.97509002685547, 507.92376708984375, 28.04888916015625, 45.368041992187
5], 'score': 0.03899860754609108}, {'category_id': 56, 'bbox': [377.0034484863281, 491.5137
023925781, 20.13714599609375, 34.996185302734375], 'score': 0.0388840027153492}, {'categor
y_id': 56, 'bbox': [503.78839111328125, 566.7881469726562, 28.494873046875, 72.01782226562
5], 'score': 0.036751069128513336}, {'category_id': 56, 'bbox': [119.07683563232422, 507.2
21923828125, 28.098655700683594, 46.0355224609375], 'score': 0.029802320525050163}, {'cate
gory_id': 56, 'bbox': [70.57160186767578, 499.4393310546875, 15.87109375, 51.1988525390625
], 'score': 0.024599188938736916}, {'category_id': 56, 'bbox': [389.9160461425781, 493.023
2849121094, 14.80902099609375, 33.048980712890625], 'score': 0.019945451989769936}, {'cate
gory_id': 56, 'bbox': [60.86790466308594, 502.6175537109375, 12.643905639648438, 27.787963
8671875], 'score': 0.018364958465099335}, {'category_id': 56, 'bbox': [529.2908935546875, 5
66.8236694335938, 40.3153076171875, 71.20458984375], 'score': 0.01757989637553692}]"], 'tensors': [] }


7.2 使用Postman验证

  1. 我们知道上述yolov3模型服务的容器内端口是18082,当前我们需要在单独的一台测试机器上使用postman去调用yolov3服务接口,那么就需要将容器内的18082端口映射到宿主机上,我们在云端BIE控制台配置paddle-serving这个服务,添加端口映射,如下图所示:

  1. 下载测试图片dog.jpeg
  2. 执行一下命令,将这张图片的base64编码输出到dog.base64文件当中
base64 -i dog.jpeg -o dog.base64
  1. 组装postman输出参数,如下所示:


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tbBFeUyPFFc24jDcCWHjUEeeqbu38GZ6ZFVbDaFbXIXYtrW7uLiaKPhLKqEelRuq18tXFqqWhisrCl
qFLzvjEKxwoY53UNRd/lk/PQWnaxqxUqlsewx3UjpLIrxNKhE8dKxgjoaDwOr0SM+W1p8h5Hay3VjP
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bcxSchzukjJNTt08dIzZFCsmbMOJXTq+gehssnYZz2LJzFNHzjSYKQrVFCGGhvevDUxvDdWfRfqCG
H02UjjnW5v5r1jE/EEhHG5YHwppjc000gTjx2beh//Z" ] }
  1. postman调用url为http://[ip]:18082/yolov3/prediction,如下图所示:

  1. 查看postman返回结果如下,如下图所示:


{ "err_no":0, "err_msg":"", "key":[ "bbox_result" ], "value":[ "[{'category_id': 16, 'bbox': 
[138.06399536132812, 54.169952392578125, 464.1486511230469, 552.6064147949219], 'score':
0.9826956987380981}, {'category_id': 57, 'bbox': [142.67298889160156, 29.47320556640625, 
401.58738708496094, 564.1134033203125], 'score': 0.02150958590209484}]" ], "tensors":[ ] }


  1. 我们看到category_id为16,查看该模型的label_list.txt,我们看到16刚好对应dog

说明:label_list当中的id,从0开始。

7.3 使用云端远程调用测试

BIE云端提供了远程调用功能。可以使用远程调用在云端直接调用边缘api,并查看返回结果。

整体测试流程如下:

  1. 进入边缘节点,找到部署的边缘应用实例paddle-serving,如下图所示:

  1. 在弹窗界面当中输入请求信息,与postman一致,如下图所示:

  1. 点击测试,云端可以查看返回结果。此处返回的结果,与前面使用postman返回的结果一致。

8 总结

  1. 上述的paddle-serving应用和运行脚本是通用的,如果想要运行不同的模型,只需要替换下发的模型文件即可。
  2. GPU镜像构建的逻辑跟CPU镜像是一致的,可以参考[制作GPU版本Paddle Serving推理镜像](BIE/典型实践/与PaddlePaddle集成/制作GPU版本Paddle Serving推理镜像.md)
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