Amazon Rekognition examples using SDK for Rust
The following code examples show you how to perform actions and implement common scenarios by using the AWS SDK for Rust with Amazon Rekognition.
Scenarios are code examples that show you how to accomplish specific tasks by calling multiple functions within a service or combined with other AWS services.
Each example includes a link to the complete source code, where you can find instructions on how to set up and run the code in context.
Topics
Scenarios
The following code example shows how to create a serverless application that lets users manage photos using labels.
- SDK for Rust
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Shows how to develop a photo asset management application that detects labels in images using Amazon Rekognition and stores them for later retrieval.
For complete source code and instructions on how to set up and run, see the full example on GitHub
. For a deep dive into the origin of this example see the post on AWS Community
. Services used in this example
API Gateway
DynamoDB
Lambda
Amazon Rekognition
Amazon S3
Amazon SNS
The following code example shows how to:
Save an image in an Amazon S3 bucket.
Use Amazon Rekognition to detect facial details, such as age range, gender, and emotion (such as smiling).
Display those details.
- SDK for Rust
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Save the image in an Amazon S3 bucket with an uploads prefix, use Amazon Rekognition to detect facial details, such as age range, gender, and emotion (smiling, etc.), and display those details.
For complete source code and instructions on how to set up and run, see the full example on GitHub
. Services used in this example
Amazon Rekognition
Amazon S3
The following code example shows how to:
Get EXIF information from a a JPG, JPEG, or PNG file.
Upload the image file to an Amazon S3 bucket.
Use Amazon Rekognition to identify the three top attributes (labels) in the file.
Add the EXIF and label information to an Amazon DynamoDB table in the Region.
- SDK for Rust
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Get EXIF information from a JPG, JPEG, or PNG file, upload the image file to an Amazon S3 bucket, use Amazon Rekognition to identify the three top attributes (labels in Amazon Rekognition) in the file, and add the EXIF and label information to a Amazon DynamoDB table in the Region.
For complete source code and instructions on how to set up and run, see the full example on GitHub
. Services used in this example
DynamoDB
Amazon Rekognition
Amazon S3