Amazon Lookout for Visionで異常検出その２（Python3.6）

投稿日 2021年3月1日
著者 aws-recipe-user
カテゴリー AWS
カテゴリー Python

はじめに

Amazon AI by ナレコムアドベントカレンダー 2020の20日目の記事です。

前回のAmazon Lookout for Visionで異常検出その１では、AWSコンソール上でAmazon Lookout for Visionの異常検出プロジェクトを作成し、学習とトライアル検出を行いました。
今回は、boto3を用いて作成したモデルをホスティングし、推論を行ってみましょう。

開発環境

AWS CLI 2.1.13
boto3 1.16.40
Python 3.6
Windows PC

導入

IAMユーザーの作成、AWS CLI & SDKs の設定、AmazonLookoutVisionFullAccessのアクセス権限を与えます。AmazonLookoutVisionFullAccessポリシーが見つからなかったので、作成しました。

AWS CLIとboto3を更新しておきましょう。

Windows での AWS CLI バージョン 2 のインストール、更新、アンインストール

pip install -U boto3

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						pip install -U boto3

Start

作成したモデルを開始します。プロジェクト名（test）とモデルのバージョン（1）を指定します。

start_model.py
#Copyright 2020 Amazon.com, Inc. or its affiliates. All Rights Reserved.

import boto3

def start_model(project_name, model_version, min_inference_units):

    client=boto3.client('lookoutvision')

    try:
        # Start the model
        print('Starting model version ' + model_version  + ' for project ' + project_name )
        response=client.start_model(ProjectName=project_name,
            ModelVersion=model_version,
            MinInferenceUnits=min_inference_units)
        print('Status: ' + response['Status'])


    except Exception as e:
        print(e)

    print('Done...')

def main():
    project='test'
    model_version='1'
    min_inference_units=1 
    start_model(project, model_version, min_inference_units)

if __name__ == "__main__":
    main()    

				
					
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						start_model.py
#Copyright 2020 Amazon.com, Inc. or its affiliates. All Rights Reserved.
 
import boto3
 
def start_model(project_name, model_version, min_inference_units):
 
    client=boto3.client('lookoutvision')
 
    try:
        # Start the model
        print('Starting model version ' + model_version  + ' for project ' + project_name )
        response=client.start_model(ProjectName=project_name,
            ModelVersion=model_version,
            MinInferenceUnits=min_inference_units)
        print('Status: ' + response['Status'])
 
 
    except Exception as e:
        print(e)
 
    print('Done...')
 
def main():
    project='test'
    model_version='1'
    min_inference_units=1 
    start_model(project, model_version, min_inference_units)
 
if __name__ == "__main__":
    main()    

					

			

状態が「STARTING_HOSTING」となります。

$ python start_model.py
Starting model version 1 for project test
Status: STARTING_HOSTING
Done...

				
					
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						$ python start_model.py
Starting model version 1 for project test
Status: STARTING_HOSTING
Done...

					

			

Describe

モデルを開始したら、状態を確認しましょう。

describe_model.py
#Copyright 2020 Amazon.com, Inc. or its affiliates. All Rights Reserved.

import boto3
import json

def describe_models(project_name):

    client=boto3.client('lookoutvision')

    try:
        #list models
        response=client.list_models(ProjectName=project_name)
        print('Project: ' + project_name)
        for model in response['Models']:
            print('Version: ' + model['ModelVersion'])
            print('ARN: ' + model['ModelArn'])
            if 'Description' in model:
                print('Description: ' + model['Description'])
            print('Status: ' + model['Status'])
            print('Status Message: ' + model['StatusMessage'])

            # get model description
            model_description=client.describe_model(ProjectName=project_name,ModelVersion=model['ModelVersion'])
            print('Status: ' + model_description['ModelDescription']['Status'])
            print('Message: ' + model_description['ModelDescription']['StatusMessage'])

            if 'Performance' in model_description['ModelDescription']:
                print('Recall: ' + str(model_description['ModelDescription']['Performance']['Recall']))
                print('Precision: ' + str(model_description['ModelDescription']['Performance']['Precision']))

            if 'OutputConfig' in model_description['ModelDescription']:
                print('Output config: ' + str(model_description['ModelDescription']['OutputConfig']))
            print()

        print('Done...')

    except Exception as e:
        print(e)        

def main():
    project_name='test'
    describe_models(project_name)

if __name__ == "__main__":
    main()

				
					
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						describe_model.py
#Copyright 2020 Amazon.com, Inc. or its affiliates. All Rights Reserved.
 
import boto3
import json
 
def describe_models(project_name):
 
    client=boto3.client('lookoutvision')
 
    try:
        #list models
        response=client.list_models(ProjectName=project_name)
        print('Project: ' + project_name)
        for model in response['Models']:
            print('Version: ' + model['ModelVersion'])
            print('ARN: ' + model['ModelArn'])
            if 'Description' in model:
                print('Description: ' + model['Description'])
            print('Status: ' + model['Status'])
            print('Status Message: ' + model['StatusMessage'])
 
            # get model description
            model_description=client.describe_model(ProjectName=project_name,ModelVersion=model['ModelVersion'])
            print('Status: ' + model_description['ModelDescription']['Status'])
            print('Message: ' + model_description['ModelDescription']['StatusMessage'])
 
            if 'Performance' in model_description['ModelDescription']:
                print('Recall: ' + str(model_description['ModelDescription']['Performance']['Recall']))
                print('Precision: ' + str(model_description['ModelDescription']['Performance']['Precision']))
 
            if 'OutputConfig' in model_description['ModelDescription']:
                print('Output config: ' + str(model_description['ModelDescription']['OutputConfig']))
            print()
 
        print('Done...')
 
    except Exception as e:
        print(e)        
 
def main():
    project_name='test'
    describe_models(project_name)
 
if __name__ == "__main__":
    main()

					

			

状態が「STARTING_HOSTING」となっています。

$ python describe_model.py
Project: test
Version: 1
ARN: arn:aws:lookoutvision:us-east-1:xxxxxxxxxxxx:model/test/1
Status: STARTING_HOSTING
Status Message: Hosting starting.
Status: STARTING_HOSTING
Message: Hosting starting.
Recall: 0.9090909361839294
Precision: 0.9090909361839294
Output config: {'S3Location': {'Bucket': 'lookoutvision-us-east-1-xxxxxxxxxx', 'Prefix': 'project/test/model/'}}

Done...

				
					
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						$ python describe_model.py
Project: test
Version: 1
ARN: arn:aws:lookoutvision:us-east-1:xxxxxxxxxxxx:model/test/1
Status: STARTING_HOSTING
Status Message: Hosting starting.
Status: STARTING_HOSTING
Message: Hosting starting.
Recall: 0.9090909361839294
Precision: 0.9090909361839294
Output config: {'S3Location': {'Bucket': 'lookoutvision-us-east-1-xxxxxxxxxx', 'Prefix': 'project/test/model/'}}
 
Done...

					

			

「HOSTED」になれば使用可能です。

Project: test
Version: 1
ARN: arn:aws:lookoutvision:us-east-1:xxxxxxxxxxxx:model/test/1
Status: HOSTED
Status Message: The model is running
Status: HOSTED
Message: The model is running
Recall: 0.9090909361839294
Precision: 0.9090909361839294
Output config: {'S3Location': {'Bucket': 'lookoutvision-us-east-1-xxxxxxxxxx', 'Prefix': 'project/test/model/'}}

Done...

				
					
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						Project: test
Version: 1
ARN: arn:aws:lookoutvision:us-east-1:xxxxxxxxxxxx:model/test/1
Status: HOSTED
Status Message: The model is running
Status: HOSTED
Message: The model is running
Recall: 0.9090909361839294
Precision: 0.9090909361839294
Output config: {'S3Location': {'Bucket': 'lookoutvision-us-east-1-xxxxxxxxxx', 'Prefix': 'project/test/model/'}}
 
Done...

					

			

もしモデルが停止していた場合は、「TRAINED」となっています。

$ python describe_model.py
Project: test
Version: 1
ARN: arn:aws:lookoutvision:us-east-1:xxxxxxxxxxxx:model/test/1
Status: TRAINED
Status Message: The model is ready for hosting
Status: TRAINED
Message: The model is ready for hosting
Recall: 0.9090909361839294
Precision: 0.9090909361839294
Output config: {'S3Location': {'Bucket': 'lookoutvision-us-east-1-xxxxxxxxxx', 'Prefix': 'project/test/model/'}}

Done...

				
					
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						$ python describe_model.py
Project: test
Version: 1
ARN: arn:aws:lookoutvision:us-east-1:xxxxxxxxxxxx:model/test/1
Status: TRAINED
Status Message: The model is ready for hosting
Status: TRAINED
Message: The model is ready for hosting
Recall: 0.9090909361839294
Precision: 0.9090909361839294
Output config: {'S3Location': {'Bucket': 'lookoutvision-us-east-1-xxxxxxxxxx', 'Prefix': 'project/test/model/'}}
 
Done...

					

			

Detect

モデルの状態が「HOSTED」になったら、推論してみましょう。これらの画像をテストしました。

異常（capsule/test/squeeze/001.png）	正常（capsule/test/good/022.png）

detect.py
#Copyright 2020 Amazon.com, Inc. or its affiliates. All Rights Reserved.

import boto3

def detect_anomalies(project_name,model_version,photo):


    client=boto3.client('lookoutvision')

    #Call DetectAnomalies 

    with open(photo, 'rb') as image:
        response = client.detect_anomalies(ProjectName=project_name, 
        # ContentType='image/jpeg',
        ContentType='image/png',
        Body=image.read(),
        ModelVersion=model_version)
    print ('Anomalous?: ' + str(response['DetectAnomalyResult']['IsAnomalous']))
    print ('Confidence: ' + str(response['DetectAnomalyResult']['Confidence']))


def main():
    project_name='test'
    photo="capsule/test/squeeze/000.png"
    model_version='1'

    anomalous=detect_anomalies(project_name,model_version,photo)


if __name__ == "__main__":
    main()

				
					
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						detect.py
#Copyright 2020 Amazon.com, Inc. or its affiliates. All Rights Reserved.
 
import boto3
 
def detect_anomalies(project_name,model_version,photo):
 
 
    client=boto3.client('lookoutvision')
 
    #Call DetectAnomalies 
 
    with open(photo, 'rb') as image:
        response = client.detect_anomalies(ProjectName=project_name, 
        # ContentType='image/jpeg',
        ContentType='image/png',
        Body=image.read(),
        ModelVersion=model_version)
    print ('Anomalous?: ' + str(response['DetectAnomalyResult']['IsAnomalous']))
    print ('Confidence: ' + str(response['DetectAnomalyResult']['Confidence']))
 
 
def main():
    project_name='test'
    photo="capsule/test/squeeze/000.png"
    model_version='1'
 
    anomalous=detect_anomalies(project_name,model_version,photo)
 
 
if __name__ == "__main__":
    main()

					

			

正しい予測結果が出ています。

$ python detect.py
Anomalous?: True
Confidence: 0.9995505213737488

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						$ python detect.py
Anomalous?: True
Confidence: 0.9995505213737488

$ python detect.py
Anomalous?: False
Confidence: 0.9181729555130005

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						$ python detect.py
Anomalous?: False
Confidence: 0.9181729555130005

モデルが「STARTING_HOSTING」の状態のときに推論した場合、以下のようなエラーが出ます。

botocore.errorfactory.ConflictException: An error occurred (ConflictException) when calling the DetectAnomalies operation: Detect cannot be performed when the resource is in STARTING_HOSTING. The resource must be in HOSTED to perform this action

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						botocore.errorfactory.ConflictException: An error occurred (ConflictException) when calling the DetectAnomalies operation: Detect cannot be performed when the resource is in STARTING_HOSTING. The resource must be in HOSTED to perform this action

また、AWSコンソールのLookout for Visionのダッシュボードで検出結果を見ることができます。

最初に異常画像を推論した結果です。

次に正常画像を推論した結果です。ダッシュボードはすぐに更新されます。

Stop

モデルを停止します。停止するまで料金かかるので注意しましょう。

stop_model.py
#Copyright 2020 Amazon.com, Inc. or its affiliates. All Rights Reserved.

import boto3

def stop_model(project_name, model_version):

    client=boto3.client('lookoutvision')


    try:
        # Stop the model
        print('Stopping model version ' + model_version  + ' for project ' + project_name )
        response=client.stop_model(ProjectName=project_name,
            ModelVersion=model_version)
        print('Status: ' + response['Status'])


    except Exception as e:
        print(e)

    print('Done...')

def main():
    project='test'
    model_version='1'
    stop_model(project, model_version)

if __name__ == "__main__":
    main()

				
					
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						stop_model.py
#Copyright 2020 Amazon.com, Inc. or its affiliates. All Rights Reserved.
 
import boto3
 
def stop_model(project_name, model_version):
 
    client=boto3.client('lookoutvision')
 
 
    try:
        # Stop the model
        print('Stopping model version ' + model_version  + ' for project ' + project_name )
        response=client.stop_model(ProjectName=project_name,
            ModelVersion=model_version)
        print('Status: ' + response['Status'])
 
 
    except Exception as e:
        print(e)
 
    print('Done...')
 
def main():
    project='test'
    model_version='1'
    stop_model(project, model_version)
 
if __name__ == "__main__":
    main()

					

			

$ python stop_model.py
Stopping model version 1 for project test
Status: STOPPING_HOSTING
Done...

				
					
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						$ python stop_model.py
Stopping model version 1 for project test
Status: STOPPING_HOSTING
Done...

					

			

まとめ

前回作ったモデルをboto3を用いてホスティングし、推論してみました。これで運用できそうです。

参考

Amazon Lookout for Vision Developer Guide

この記事を書いた人

aws-recipe-user

記事一覧

Amazon Lookout for Visionで異常検出その２（Python3.6）

はじめに

開発環境

導入

Start

Describe

Detect

Stop

まとめ

参考

この記事を書いた人

aws-recipe-user

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