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.
Passport Data Page Detection Free trial
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Passport Data Page Detection allows you to detect if a passport data page photo is a valid photo for identity use.
Product Overview
With GTRIIP's Passport Data Page Detection API, you can now have automated Know Your Customer (KYC) capabilities at your fingertips. GTRIIP's Passport Page Detection API uses machine learning and AI to verify the photograph and personal particulars on the passport page and can extract these personal particulars to automate cumbersome form-filling processes. This robust API can be easily integrated to web applications and perform verification checks at scale.
Key Data
By
Type
Model Package
Highlights
-Machine Learning - our API is powered by our proprietary machine learning engine to detect passport fraud and validity and our accuracy is continuously improved as our model is trained with more input
-Smooth User Experience - easy-to-use API which can be integrated to any web application like chatbots or onboarding screens for instant access to our service
-Trusted by Leading Brands - GTRIIP's digital identity products are used by leading hospitality brands all over the world such as the Sands China Group and Amara Hotel
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Usage Information
Model input and output details
Input
Summary
Provide a form-data or application/json file to the endpoint. Parameters you can tune:
- image or image_bytes: Field for your image, either as a file or base64-encoded bytestring. An error will be thrown if neither is provided.
- auto_rotate: Optional. Set to True if uploading your passport at 90/180/270 degrees. A suggested rotation degree will be returned.
- skip_face_detect: Optional. Set to True to skip face detection for the passport. Refer to the sample notebook for more details.
Limitations for input type
10 MegaBytes
Input MIME type
application/jsonSample input data
Output
Summary
Output Summary:
- Face Location: Coordinates of detected face.
- Document Details:
- Type and MRZ type, Country, Nationality
- Name, Date of Birth, Sex
- Expiration Date, Document Number, Personal Number
- Expiry Status
- Validation Scores:
- Composite, Date of Birth, Expiration Date, Number, Personal Number scores
- Overall validity and score
- Raw Text: Extracted MRZ text
- Rotate Angle: Suggested rotation angle
- Success: Scan success status
- Error Message: Error details.
Limitations for output type
No limitation.
Output MIME type
application/jsonSample output data
Sample notebook
Additional Resources
End User License Agreement
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Support Information
Passport Data Page Detection
Input format: application/json
Output format: application/json
Blog: https://aws.amazon.com/blogs/awsmarketplace/automating-know-your-customer-workflow-using-a-ready-to-use-model-package-from-aws-marketplace-for-machine-learning/
Sample notebook for deployment and inference:
http://download.gtriip.com/document/AWS%20SageMaker%20Deploy%20and%20Invoke.ipynb
AWS Infrastructure
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Learn MoreRefund Policy
The product is not refundable.
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