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Amazon Sagemaker

Amazon SageMaker is a fully-managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. With Amazon SageMaker, all the barriers and complexity that typically slow down developers who want to use machine learning are removed. The service includes models that can be used together or independently to build, train, and deploy your machine learning models.

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GluonCV ResNet50 Classifier

Latest Version:
1.0
Image feature extraction and ImageNet category prediction using ResNet50-v1d network, provided by GluonCV

    Product Overview

    This model provides intermediate image feature extraction functionality for image classification. It can also provide top-5 category predictions out of 1000 classes on ImageNet. This network is one of the best models that are both highly efficient and accurate. As a result, it also provides high-quality features for various tasks.

    Key Data

    Type
    Model Package
    Fulfillment Methods
    Amazon SageMaker

    Highlights

    • This model can extract high-quality image features efficiently.

    • This model can predict top-5 predictions on ImageNet.

    • The state-of-the-art performance with accuracy of 79.15 vs. 75.3 in the original paper (https://arxiv.org/abs/1512.03385 )

    Not quite sure what you’re looking for? AWS Marketplace can help you find the right solution for your use case. Contact us

    Pricing Information

    Use this tool to estimate the software and infrastructure costs based your configuration choices. Your usage and costs might be different from this estimate. They will be reflected on your monthly AWS billing reports.


    Estimating your costs

    Choose your region and launch option to see the pricing details. Then, modify the estimated price by choosing different instance types.

    Version
    Region

    Software Pricing

    Model Realtime Inference$0.00/hr

    running on ml.c4.xlarge

    Model Batch Transform$0.00/hr

    running on ml.c4.xlarge

    Infrastructure Pricing

    With Amazon SageMaker, you pay only for what you use. Training and inference is billed by the second, with no minimum fees and no upfront commitments. Pricing within Amazon SageMaker is broken down by on-demand ML instances, ML storage, and fees for data processing in notebooks and inference instances.
    Learn more about SageMaker pricing

    SageMaker Realtime Inference$0.239/host/hr

    running on ml.c4.xlarge

    SageMaker Batch Transform$0.239/host/hr

    running on ml.c4.xlarge

    Model Realtime Inference

    For model deployment as Real-time endpoint in Amazon SageMaker, the software is priced based on hourly pricing that can vary by instance type. Additional infrastructure cost, taxes or fees may apply.
    InstanceType
    Realtime Inference/hr
    ml.m4.4xlarge
    $0.00
    ml.m5.4xlarge
    $0.00
    ml.m5.12xlarge
    $0.00
    ml.m4.16xlarge
    $0.00
    ml.m5.2xlarge
    $0.00
    ml.c4.4xlarge
    $0.00
    ml.m5.xlarge
    $0.00
    ml.c5.9xlarge
    $0.00
    ml.m4.xlarge
    $0.00
    ml.c5.4xlarge
    $0.00
    ml.m4.2xlarge
    $0.00
    ml.c5.2xlarge
    $0.00
    ml.m5.large
    $0.00
    ml.c4.2xlarge
    $0.00
    ml.c4.8xlarge
    $0.00
    ml.m4.10xlarge
    $0.00
    ml.c4.xlarge
    Vendor Recommended
    $0.00
    ml.m5.24xlarge
    $0.00
    ml.c5.18xlarge
    $0.00
    ml.c5.xlarge
    $0.00

    Usage Information

    Fulfillment Methods

    Amazon SageMaker

    Supported content types are image/jpeg, image/png and image/bmp.

    AWS APIs can be used to invoke the model after endpoint creation, e.g., using aws-cli:

    aws sagemaker-runtime invoke-endpoint --endpoint-name your_endpoint_name --body fileb://img.jpg --accept image/jpeg --custom-attributes '{"feature": "flat"}' feat.out

    This command will extract 2048-dim feature prior to fully-connected layer.

    Supported layers: ('conv1', 'bn1', 'relu', 'maxpool', 'layer1', 'layer2', 'layer3', 'layer4', 'avgpool', 'flat', 'fc'), if you don't speficy custom-attributes, this model will return top-5 predictions.

    Additional Resources

    End User License Agreement

    By subscribing to this product you agree to terms and conditions outlined in the product End user License Agreement (EULA)

    Support Information

    GluonCV ResNet50 Classifier

    Model supported is available from GluonCV. Search for questions and open new issues to ask questions.

    AWS Infrastructure

    AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.

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    Refund Policy

    None

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