Sold by: AgmisÂ
Deployed on AWS
The model identifies whether required personal protection equipment (PPE) is worn by the workers.
Overview
The model recognizes PPE equipment, including high-visibility vests, hardhats of a pre-assigned area (such as a construction site, cargo loading area, factory floor etc.) The model is used to ensure complience with company safety protocol and identify safety breaches. Data provided by the model can be utilized to notify safety officer about PPE protocol breaches in real-time or used for safety procedure breaches and analysis at a later stage.
Highlights
- Maximize workplace safety with real-time monitoring of PPE policy
- Harness model data for real-time notifications about PPE policy breaches
- Utilize standard security low-resolution video monitoring cameras
Details
Sold by
Categories
Delivery method
Latest version
Deployed on AWS
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Features and programs
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Pricing
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.xlarge Inference (Batch) Recommended | Model inference on the ml.m5.xlarge instance type, batch mode | $4.00 |
ml.m5.xlarge Inference (Real-Time) Recommended | Model inference on the ml.m5.xlarge instance type, real-time mode | $4.00 |
ml.m4.4xlarge Inference (Batch) | Model inference on the ml.m4.4xlarge instance type, batch mode | $4.00 |
ml.m5.4xlarge Inference (Batch) | Model inference on the ml.m5.4xlarge instance type, batch mode | $4.00 |
ml.m4.16xlarge Inference (Batch) | Model inference on the ml.m4.16xlarge instance type, batch mode | $4.00 |
ml.m5.2xlarge Inference (Batch) | Model inference on the ml.m5.2xlarge instance type, batch mode | $4.00 |
ml.p3.16xlarge Inference (Batch) | Model inference on the ml.p3.16xlarge instance type, batch mode | $4.00 |
ml.m4.2xlarge Inference (Batch) | Model inference on the ml.m4.2xlarge instance type, batch mode | $4.00 |
ml.c5.2xlarge Inference (Batch) | Model inference on the ml.c5.2xlarge instance type, batch mode | $4.00 |
ml.p3.2xlarge Inference (Batch) | Model inference on the ml.p3.2xlarge instance type, batch mode | $4.00 |
Vendor refund policy
We do not offer refunds at this time
Legal
Vendor terms and conditions
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Content disclaimer
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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
Fixed issues with container safety.
Additional details
Inputs
- Summary
The model can analyze images that are supplied as base64 string or images that can be converted to base64 string.
- Input MIME type
- application/x-image
https://sagemaker-storage-data.s3.us-east-2.amazonaws.com/ppe/input/alex-radelich-cD7_Bs6GyeM-unsplash.jpg
https://sagemaker-storage-data.s3.us-east-2.amazonaws.com/ppe/ppe_imgs.zip
Resources
Vendor resources
Support
Vendor support
Email.: info@agmis.euÂ
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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