Sold by: ProvectusÂ
Deployed on AWS
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Image classification model to accurately identify PPE items that prevent disease transmission.
Overview
The Worker Health Safety solution enables businesses to minimize disease transmission risks in various environments. Through ML-driven proactive monitoring, it makes it easier to enforce and comply with safety standards, to keep customers and employees safe from viruses and bacteria. The ML model is trained on public datasets of crowd footage featuring individuals wearing a wide range of masks, scarfs, and respirators on the face. It can be reinforced with a social distancing monitoring solution by Provectus to further enhance safety standards.
Highlights
- Classification of a correct/incorrect use of facial masks, respirators, or scarves by individuals caught in the image.
- Can be used with a social distance monitoring solution to provide you details on groups of people who can potentially violate the set distance parameter.
- Need a custom-made solution for video/image analysis? Reach us at hello@provectus.com
Details
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Delivery method
Latest version
Deployed on AWS
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Pricing
Free trial
Try this product free for 28 days according to the free trial terms set by the vendor.
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.
Dimension | Description | Cost/host/hour |
|---|---|---|
ml.m5.large Inference (Batch) Recommended | Model inference on the ml.m5.large instance type, batch mode | $0.01 |
ml.t2.medium Inference (Real-Time) Recommended | Model inference on the ml.t2.medium instance type, real-time mode | $0.01 |
ml.m4.4xlarge Inference (Batch) | Model inference on the ml.m4.4xlarge instance type, batch mode | $0.01 |
ml.m5.4xlarge Inference (Batch) | Model inference on the ml.m5.4xlarge instance type, batch mode | $0.01 |
ml.m5.12xlarge Inference (Batch) | Model inference on the ml.m5.12xlarge instance type, batch mode | $0.01 |
ml.m4.16xlarge Inference (Batch) | Model inference on the ml.m4.16xlarge instance type, batch mode | $0.01 |
ml.m5.2xlarge Inference (Batch) | Model inference on the ml.m5.2xlarge instance type, batch mode | $0.01 |
ml.m5.xlarge Inference (Batch) | Model inference on the ml.m5.xlarge instance type, batch mode | $0.01 |
ml.m4.xlarge Inference (Batch) | Model inference on the ml.m4.xlarge instance type, batch mode | $0.01 |
ml.c5.4xlarge Inference (Batch) | Model inference on the ml.c5.4xlarge instance type, batch mode | $0.01 |
Vendor refund 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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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:
Version release notes
Added more classes:
- face_no_mask,
- face_with_mask,
- face_with_mask_incorrect,
- mask_surgical,
- face_other_covering,
- mask_colorful
Additional details
Inputs
- Summary
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: Â https://github.com/provectus/ai-worker-safety-notebooks/blob/master/worker_health_safety_usage_demo.ipynbÂ
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
See Input Summary
See Input Summary
Resources
Vendor resources
Support
Vendor support
Check out the JSON inference sample: https://bit.ly/whs-inferenceÂ
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 support
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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