Sold by: MphasisÂ
Deployed on AWS
This is a trainable algorithm which detects and recognizes faces of individuals on which the model is trained.
Overview
Mphasis DeepInsights face recognition algorithm detects the faces present in the image data and uses the concepts of transfer learning to extract high quality features from the facial data known as face embeddings. These face embedding are used to train the machine learning model for face identification.
Highlights
- Mphasis DeepInsights Face recognition algorithm is a two-step solution. First it identifies the facial features present in the data and then converts them into high quality features know as face embedding. The solution provides the mechanism to train as well as test on user specific data for face identification.
- This solution can be used in a variety of applications where facial data may be used as security measures such as access control, social distance monitoring and in location analytics for law enforcement, retail, real estate management, banking and insurance. The other uses of this solution can be unlocking phones, smarter advertising, finding missing persons.
- Mphasis DeepInsights is a cloud-based cognitive computing platform that offers data extraction & predictive analytics capabilities. Need customized Machine Learning and Deep Learning solutions? Get in touch!
Details
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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.
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.large Inference (Batch) Recommended | Model inference on the ml.m5.large instance type, batch mode | $10.00 |
ml.m5.large Inference (Real-Time) Recommended | Model inference on the ml.m5.large instance type, real-time mode | $5.00 |
ml.m5.4xlarge Training Recommended | Algorithm training on the ml.m5.4xlarge instance type | $10.00 |
ml.m4.4xlarge Inference (Batch) | Model inference on the ml.m4.4xlarge instance type, batch mode | $10.00 |
ml.m5.4xlarge Inference (Batch) | Model inference on the ml.m5.4xlarge instance type, batch mode | $10.00 |
ml.m4.16xlarge Inference (Batch) | Model inference on the ml.m4.16xlarge instance type, batch mode | $10.00 |
ml.m5.2xlarge Inference (Batch) | Model inference on the ml.m5.2xlarge instance type, batch mode | $10.00 |
ml.p3.16xlarge Inference (Batch) | Model inference on the ml.p3.16xlarge instance type, batch mode | $10.00 |
ml.m4.2xlarge Inference (Batch) | Model inference on the ml.m4.2xlarge instance type, batch mode | $10.00 |
ml.c5.2xlarge Inference (Batch) | Model inference on the ml.c5.2xlarge instance type, batch mode | $10.00 |
Vendor refund policy
Currently we do not support refunds, but you can cancel your subscription to the service at any time.
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Delivery details
Amazon SageMaker algorithm
An Amazon SageMaker algorithm is a machine learning model that requires your training data to make predictions. Use the included training algorithm to generate your unique model artifact. Then deploy the model on Amazon SageMaker for real-time inference or batch processing. Amazon SageMaker is a fully managed platform for building, training, and deploying machine learning models at scale.
Deploy the model on Amazon SageMaker AI using the following options:
Version release notes
This is the Version 1.8 of the algorithm
Additional details
Inputs
- Summary
AWS CLI Command If you are using real time inferencing, please create the endpoint first and then use the following command to invoke it:
aws sagemaker-runtime invoke-endpoint --endpoint-name "endpoint-name" --body fileb://$file_name --content-type application/json --accept application/output.json
- Input MIME type
- application/zip, text/csv, text/plain, application/json
https://github.com/Mphasis-ML-Marketplace/Face-Recognition-Algorithm/tree/main/Test%20Input
https://github.com/Mphasis-ML-Marketplace/Face-Recognition-Algorithm/tree/main/Test%20Input
Input data descriptions
The following table describes supported input data fields for real-time inference and batch transform.
Field name | Description | Constraints | Required |
|---|---|---|---|
sample_test_input.json | json form of RGB pixel array of the input image | Type: Continuous | Yes |
Resources
Vendor resources
Support
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