The aws-ai module contains classes that make it easy for DJL to access AWS services.
With this module, you can easily load model from AWS S3 bucket. As long as you include this module in your project, ModelZoo class can load models from your s3 bucket.
The following pseudocode demonstrates how to load model from S3:
Criteria<Image, Classifications> criteria =
Criteria.builder()
.optApplication(Application.CV.IMAGE_CLASSIFICATION)
.setTypes(Image.class, Classifications.class)
.optModelUrls("s3://djl-misc/test/models/resnet18")
.optModelName("resent18_v1")
.optProgress(new ProgressBar())
.build();
ZooModel<Image, Classifications> model = criteria.loadModel();
See How to load a model for more detail.
If you want to customize your AWS credentials and region, you can manually register a customized
S3RepositoryFactory:
S3Client client = S3Client.builder()
.credentialsProvider(provider)
.region(Region.US_EAST_1)
.build();
Repository.registerRepositoryFactory(new S3RepositoryFactory(client));
The latest javadocs can be found on here.
You can also build the latest javadocs locally using the following command:
./gradlew javadoc
The javadocs output is built in the build/doc/javadoc folder.
You can pull the module from the central Maven repository by including the following dependency in your pom.xml file:
<dependency>
<groupId>ai.djl.aws</groupId>
<artifactId>aws-ai</artifactId>
<version>0.30.0</version>
</dependency>