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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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Automatic Video/Image Recognition Free trial

By:
Sensifai
Latest Version:
v1
Automatic image/video recognition and tagging
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    Product Overview

    Sensifai offers automatic video/image recognition and tagging. For example, our basic software recognizes thousands and thousands of objects/scenes and concepts in videos and images such as cars, foods, and animals. In Sagemaker platform, you can easily fine-tune this software to recognize a new set of concepts and tags by providing the required training dataset.

    Key Data

    Version
    v1
    Usage Instructions
    Release Notes
    By
    Sensifai
    Categories
    Classification-Video
    Classification-Image
    Computer Vision
    Type
    Algorithm
    Fulfillment Methods
    Amazon SageMaker

    Highlights

    • Sensifai's basic video/image recognition system covers thousands of concepts (this software is accessible through AWS marketplace). However, customers and users often deal with a new set of concepts and objects. Therefore, we have designed an easy-to-use interface which automates the process of training a video/image recognition system.

    • You can use Sensifai's interface through Sagemaker to develop a video/image recognition system that covers your set of concepts for your own specific use-case. Provide a training dataset and create your own video recognition system immediately.

    • If you do not have dataset for training or looking for pre-trained models for image/video recognition or other domains of video/image analysis, you can check our ready to use API or contact us directly (sales@sensifai.com).

    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

    Algorithm Training$2/hr

    running on ml.p3.16xlarge

    Model Realtime Inference$3.60/hr

    running on ml.p3.2xlarge

    Model Batch Transform$3.60/hr

    running on ml.p3.8xlarge

    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 Algorithm Training$28.152/host/hr

    running on ml.p3.16xlarge

    SageMaker Realtime Inference$3.825/host/hr

    running on ml.p3.2xlarge

    SageMaker Batch Transform$14.688/host/hr

    running on ml.p3.8xlarge

    About Free trial

    Try this product for 2 days. There will be no software charges, but AWS infrastructure charges still apply. Free Trials will automatically convert to a paid subscription upon expiration.

    Algorithm Training

    For algorithm training 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
    Algorithm/hr
    ml.p2.xlarge
    $0.10
    ml.p2.8xlarge
    $0.70
    ml.p2.16xlarge
    $1.00
    ml.p3.2xlarge
    $0.40
    ml.p3.8xlarge
    $1.00
    ml.p3.16xlarge
    Vendor Recommended
    $2.00

    Usage Information

    Fulfillment Methods

    Amazon SageMaker

    See example notebook for example usage.

    Metrics

    Name
    Regex
    f1-measure
    .*\\[[0-9]+\\].*#011f1-measure:(\\S+)
    train-loss
    .*\\[[0-9]+\\].*#011train-loss:(\\S+)

    Channel specification

    Fields marked with * are required

    train

    *
    Input modes: File
    Content types: image/*
    Compression types: None

    validation

    Input modes: File
    Content types: image/*
    Compression types: None

    Hyperparameters

    Fields marked with * are required

    min_val_samples

    minimum number of validation samples for each tag (if no val label file exists!)
    Type: Integer
    Tunable: No

    learning_rate

    Initial learning rate
    Type: Continuous
    Tunable: No

    momentum

    Momentum
    Type: Continuous
    Tunable: No

    model_depth

    Number of layers for model
    Type: Categorical
    Tunable: No

    settings

    *
    select Training Setting
    Type: Categorical
    Tunable: No

    batch_size

    batch size(if set to 0, will automatically set batch size considering GPU memories)
    Type: Integer
    Tunable: No

    lr_decay

    Factor by which the learning rate will be reduced. new_lr = lr * factor
    Type: Continuous
    Tunable: No

    lr_patience

    Patience of LR scheduler
    Type: Integer
    Tunable: No

    max_patience

    Terminate training after validation loss become greater than train loss for this number of epochs
    Type: Integer
    Tunable: No

    n_epochs

    Total number of training epochs
    Type: Integer
    Tunable: No

    result_second_interval

    return results for tags in this second Intervals
    Type: Integer
    Tunable: No

    thresholdValue

    Critical Parameter for Selecting Class Labels
    Type: Continuous
    Tunable: No

    score_result_threshold

    the threshold on results
    Type: Continuous
    Tunable: No

    num_result_tags

    number of tags on results
    Type: Integer
    Tunable: No

    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

    Automatic Video/Image Recognition

    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.

    Learn More

    Refund Policy

    You may cancel your subscription at any time; However, we will not refund payments made by you under the agreement for any reason whatsoever.

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