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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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Face Anonymizer (CPU)

By:
Appen (fka Figure Eight)
Latest Version:
Version 1
This model blurs the faces of people in an image to preserve privacy
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    Product Overview

    This model blurs the faces of people in an image to preserve privacy. It was trained on the “Labeled Faces in the Wild” dataset and tested on small and medium sized images. This is a great tool to mitigate privacy concerns when showing images which contain people in a public setting. Please note: though this model currently is optimized for caucasian men based solely on the training data set coverage, it will also work for other ethnicities and genders. A deep dive on the training data set to better understand the limitations is recommended.

    Key Data

    Version
    Version 1
    Usage Instructions
    Release Notes
    By
    Appen (fka Figure Eight)
    Categories
    Computer Vision
    Human/Faces
    Type
    Model Package
    Fulfillment Methods
    Amazon SageMaker

    Highlights

    • This model blurs the faces of people in an image to preserve privacy.

    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.

    Contact us to request contract pricing for this product.


    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$0.45/hr

    running on ml.c5.xlarge

    Model Batch Transform$0.45/hr

    running on ml.c5.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$0.204/host/hr

    running on ml.c5.xlarge

    SageMaker Batch Transform$0.204/host/hr

    running on ml.c5.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.c5.xlarge
    Vendor Recommended
    $0.45

    Usage Information

    Fulfillment Methods

    Amazon SageMaker

    Example for the /invocations endpoint:

    Input (application/json): Image with peoples faces that needs to be blurred [base64 encoded] Payload: {"instances": [{"image": {"b64": "BASE_64_ENCODED_IMAGE_CONTENTS"}}]}

    Output (application/json): Image with the predicted faces blurred.

    Content: {"predictions": [ { "image": {"b64", "a35..."}}]}

    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

    Face Anonymizer (CPU)

    If you need any support, have questions, or suggestions, please email ml-support@figure-eight.com

    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

    We do not currently support refunds, but you can cancel at any time.

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