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    High Resolution Image Enhancer

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    Sold by: Mphasis 
    Deployed on AWS
    This solution helps improve the resolution and detail of images with advanced AI-based image super resolution techniques.

    Overview

    This solution utilizes GAN based techniques that reconstructs the image at a pixel level to generate a high-resolution version that preserves the original details and sharpness. The result is an image that is ready for printing, editing, or use in any application where high quality is a must. This solution takes a zip file of low resolution image/images as input and returns a zip file of transformed hi-res image/images as output.This solution supports jpg,jpeg and png file formats. Limit the number of images to 20 and image size of around 250KB is recommended for optimal use in low end machines.

    Highlights

    • An easy to use solution for generating high resolution images from low resolution.This solution will aid in improving image resolution for low resolution images of scans and documents by using advance machine learning techniques
    • The resolution of medical photos, satellite images, insurance documents, and many other types of images can be improved with the help of this solution, which also makes images more visually appealing and immersive.
    • Mphasis Synth Studio is an Enterprise Synthetic Data Platform for generating high-quality synthetic data that can help derive and monetize trustworthy business insights, while preserving privacy and protecting data subjects. Build reliable and high accuracy models when no or low data is available.

    Details

    Delivery method

    Latest version

    Deployed on AWS

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    Features and programs

    Financing for AWS Marketplace purchases

    AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
    Financing for AWS Marketplace purchases

    Pricing

    High Resolution Image Enhancer

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    Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
    Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator  to estimate your infrastructure costs.

    Usage costs (27)

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    Dimension
    Description
    Cost
    ml.m5.xlarge Inference (Batch)
    Recommended
    Model inference on the ml.m5.xlarge instance type, batch mode
    $10.00/host/hour
    ml.m4.4xlarge Inference (Batch)
    Model inference on the ml.m4.4xlarge instance type, batch mode
    $10.00/host/hour
    ml.m5.4xlarge Inference (Batch)
    Model inference on the ml.m5.4xlarge instance type, batch mode
    $10.00/host/hour
    ml.m4.16xlarge Inference (Batch)
    Model inference on the ml.m4.16xlarge instance type, batch mode
    $10.00/host/hour
    ml.m5.2xlarge Inference (Batch)
    Model inference on the ml.m5.2xlarge instance type, batch mode
    $10.00/host/hour
    ml.p3.16xlarge Inference (Batch)
    Model inference on the ml.p3.16xlarge instance type, batch mode
    $10.00/host/hour
    ml.m4.2xlarge Inference (Batch)
    Model inference on the ml.m4.2xlarge instance type, batch mode
    $10.00/host/hour
    ml.c5.2xlarge Inference (Batch)
    Model inference on the ml.c5.2xlarge instance type, batch mode
    $10.00/host/hour
    ml.p3.2xlarge Inference (Batch)
    Model inference on the ml.p3.2xlarge instance type, batch mode
    $10.00/host/hour
    ml.c4.2xlarge Inference (Batch)
    Model inference on the ml.c4.2xlarge instance type, batch mode
    $10.00/host/hour

    Vendor refund policy

    Currently we do not support refunds, but you can cancel your subscription to the service at any time.

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    Legal

    Vendor terms and conditions

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    Usage information

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    Delivery details

    Amazon SageMaker model

    An Amazon SageMaker model package is a pre-trained machine learning model ready to use without additional training. Use the model package to create a model on Amazon SageMaker for real-time inference or batch processing. Amazon SageMaker is a fully managed platform for building, training, and deploying machine learning models at scale.

    Deploy the model on Amazon SageMaker AI using the following options:
    Deploy the model as an API endpoint for your applications. When you send data to the endpoint, SageMaker processes it and returns results by API response. The endpoint runs continuously until you delete it. You're billed for software and SageMaker infrastructure costs while the endpoint runs. AWS Marketplace models don't support Amazon SageMaker Asynchronous Inference. For more information, see Deploy models for real-time inference  .
    Deploy the model to process batches of data stored in Amazon Simple Storage Service (Amazon S3). SageMaker runs the job, processes your data, and returns results to Amazon S3. When complete, SageMaker stops the model. You're billed for software and SageMaker infrastructure costs only during the batch job. Duration depends on your model, instance type, and dataset size. AWS Marketplace models don't support Amazon SageMaker Asynchronous Inference. For more information, see Batch transform for inference with Amazon SageMaker AI  .
    Version release notes

    Latest Version:

    Additional details

    Inputs

    Summary

    A zip file with low resolution images is required as input. Please refer sample images

    Limitations for input type
    Limit each image size to around 250 KB
    Input MIME type
    application/zip
    https://github.com/Mphasis-ML-Marketplace/High-Resolution-Image-Enhancer
    https://github.com/Mphasis-ML-Marketplace/High-Resolution-Image-Enhancer

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