Sold by: Seamfix
Deployed on AWS
Authenticate customers with ease and level up your onboarding with Face Match for Customer Authentication by Seamfix.
Overview
Face Match for Customer Authentication by Seamfix uses advanced facial recognition technology to match faces against a database of registered faces. It is highly reliable and accurate, even in low-light conditions, reducing the risk of fraud and improving security.
Highlights
- Level Up Your Facial Recognition: Face Match by Seamfix accurately compares and matches human faces within seconds.
- Enjoy Accuracy: Face Match by Seamfix relies on advanced AI technology to ensure accuracy of results.
- Ensure Improved Image Quality: Face Match by Seamfix recognizes faces from various angles and lighting conditions, so only accurate images are approved.
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 |
|---|---|---|
ml.m4.xlarge Inference (Batch) Recommended | Model inference on the ml.m4.xlarge instance type, batch mode | $0.95/host/hour |
inference.count.m.i.c Inference Pricing | inference.count.m.i.c Inference Pricing | $0.95/request |
Dimensions summary
This product uses usage-based pricing with two separate dimensions. You pay by the hour for model inference run on the ml.m4.xlarge instance type in batch mode. This dimension charges per host hour, so cost scales with how long the instance runs. The second dimension charges per inference request, so cost scales with how many face match requests you process. The two dimensions are independent and reflect different ways of running the face match capability. Pick based on whether you process work in batches or handle individual requests.
Top-of-mind questions for buyers
Each request charges for one face match operation processed by the model. The system compares biometric faces to confirm a person matches their claimed identity. One submitted match call counts as one billable request, so your cost tracks the number of authentication checks you run.
The host-hour dimension meters time the instance runs. Charges accrue per hour while the ml.m4.xlarge instance is active in batch mode. A fully stopped instance does not accrue software host-hour charges. Underlying AWS infrastructure fees may still apply depending on instance state.
The two dimensions bill independently. The batch host-hour charge tracks how long the ml.m4.xlarge instance runs. The per-request charge tracks how many face match requests you process. Batch workloads lean on host hours; individual real-time checks lean on request volume. You pay for whichever modes you use.
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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
Detects face i pair of images and returns the similairty score between faces
Additional details
Inputs
- Summary
{"source_image": source_img_base64,"target_image": target_img_base64}
- Limitations for input type
- 10MB for each image
- Input MIME type
- application/json
https://github.com/seamfix/seamfix-AWSmarketplace/blob/main/data/input/real-time/image.jpg
https://github.com/seamfix/seamfix-AWSmarketplace/blob/main/data/input/real-time/image.jpg
Input data descriptions
The following table describes supported input data fields for real-time inference and batch transform.
Field name | Description | Constraints | Required |
|---|---|---|---|
source_image | source_image: source image to be matched with 2nd. image target_image: target image to be matched with source image | Type: FreeText
Limitations: 20MB | Yes |
target_image | source_image: source image to be matched with 2nd. image target_image: target image to be matched with source image | Type: FreeText
Limitations: 20MB | Yes |
Support
Vendor support
Face Match for Customer Authentication Arena Business Centre, 100 Berkshire Place, Wharfedale Road, Winnersh, RG41 5RD Phone: 44 7756 238056 Support@seamfix.com support@seamfix.com
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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