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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Social Distancing Detector Free trial
By:
Latest Version:
0.1
Image classification model that detects violations of social distancing in public areas
Product Overview
Provectus Social Distancing Detector fits well into video analytic workloads for businesses that are to minimize disease transmission risks, gather data for decision-making processes, and ensure adequate personal space for their employees and clients. The solution performs isomorphic analysis by estimating distances between people based on their approximate height. That requires an adequate camera angle, usually placed well-above the queue or crowd so that an image frame does not look misleading.
Key Data
Version
Type
Model Package
Highlights
Ensure your public space is safe and compliant with safety and health requirements. It might be combined with a face mask detection solution from Provectus to enhance your standards and give better insights about your environment. The solution is typically integrated as a part of video processing pipelines via AWS: https://aws.amazon.com/blogs/machine-learning/video-analytics-in-the-cloud-and-at-the-edge-with-aws-deeplens-and-kinesis-video-streams/
Check it yourself with our Jupyter Notebook, that you can run hassle-free in AWS SageMaker or on your local machine: https://github.com/provectus/ai-worker-safety-notebooks/blob/master/social-distancing-usage-demo.ipynb
Need a custom-made solution for video/image analysis? Reach us at hello@provectus.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
Model Realtime Inference$0.01/hr
running on ml.t2.large
Model Batch Transform$0.01/hr
running on ml.m5.large
Infrastructure PricingWith 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
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$0.111/host/hr
running on ml.t2.large
SageMaker Batch Transform$0.115/host/hr
running on ml.m5.large
About Free trial
Try this product for 28 days. There will be no software charges, but AWS infrastructure charges still apply. Free Trials will automatically convert to a paid subscription upon expiration.
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 | $0.01 | |
ml.m5.4xlarge | $0.01 | |
ml.m5.12xlarge | $0.01 | |
ml.m4.16xlarge | $0.01 | |
ml.m5.2xlarge | $0.01 | |
ml.m5.xlarge | $0.01 | |
ml.m4.xlarge | $0.01 | |
ml.m4.2xlarge | $0.01 | |
ml.m5.large | $0.01 | |
ml.t2.xlarge | $0.01 | |
ml.m4.10xlarge | $0.01 | |
ml.m5.24xlarge | $0.01 | |
ml.m5d.xlarge | $0.01 | |
ml.m5d.large | $0.01 | |
ml.t2.large Vendor Recommended | $0.01 | |
ml.t2.medium | $0.01 | |
ml.t2.2xlarge | $0.01 |
Usage Information
Fulfillment Methods
Amazon SageMaker
Usage Instructions: Supported content types are ["image/jpeg"]
Supported response types are "application/json"
After creating an endpoint, you can use any AWS Sagemaker APIs to use the model.
The easiest way is with our supplied Jupyter Notebook: https://github.com/provectus/ai-worker-safety-notebooks/blob/master/social-distancing-demo.ipynb
But you can also use the AWS CLI:
aws sagemaker-runtime invoke-endpoint --endpoint-name "your_endpoint" --body fileb://test_image.jpeg --content-type "image/jpeg" output.json
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
Social Distancing Detector
We'd love to tailor the model for your needs and to improve prediction accuracy for your environment and use case. Reach out to us at hello@provectus.com or visit our website.
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 MoreRefund Policy
Please notify Provectus if the solution does not produce an inference or is considered to produce unsatisfactory inferences after the trial period — and we'll open a refund case for you.
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