Sold by: John Snow LabsÂ
Deployed on AWS
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Specialized **Handwritten Text Extraction Model** designed to convert handwritten content from PDFs and images into accurate, searchable digital text.
Overview
Introducing a specialized Handwritten Text Extraction Model designed to convert handwritten content from PDFs and images into accurate, searchable digital text.
Leveraging cutting-edge text recognition algorithms and deep learning techniques, this model is optimized to tackle the unique challenges of handwriting - such as irregular shapes, variable stroke patterns, and inconsistent spacing. It excels in transcribing handwritten notes, medical forms, administrative documents, and historical records with high precision and minimal errors.
By automating the transcription process, it dramatically reduces manual data entry time, improves workflow efficiency, and enables seamless integration of handwritten information into digital systems.
Whether you're working in healthcare, education, legal, or archival environments, this model delivers reliable, scalable handwriting recognition for your document digitization needs.
IMPORTANT USAGE INFORMATION:
After subscribing to this product and creating a SageMaker endpoint, billing occurs on an HOURLY BASIS for as long as the endpoint is running.
-Charges apply even if the endpoint is idle and not actively processing requests.
-To stop charges, you MUST DELETE the endpoint in your SageMaker console.
-Simply stopping requests will NOT stop billing.
This ensures you are only billed for the time you actively use the service.
Highlights
- This Handwritten Text Extraction Model transforms how organizations handle handwritten content by delivering highly accurate, automated transcription of notes, forms, and scanned documents. Optimized for the irregularities of handwriting - such as varied penmanship, spacing, and alignment - it ensures reliable digitization with minimal post-processing.
- Designed for real-world applications across healthcare, education, legal, and archival sectors, this model enables smooth integration of handwritten data into digital systems. Whether digitizing patient intake forms, transcribing classroom notes, or preserving historical records, it enhances efficiency and accessibility - allowing teams to search, store, and analyze handwritten content just like typed text.
Details
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Latest version
Deployed on AWS
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Pricing
Free trial
Try this product free for 15 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.g5.2xlarge Inference (Batch) Recommended | Model inference on the ml.g5.2xlarge instance type, batch mode | $95.04 |
ml.g4dn.4xlarge Inference (Real-Time) Recommended | Model inference on the ml.g4dn.4xlarge instance type, real-time mode | $95.04 |
ml.m4.xlarge Inference (Batch) | Model inference on the ml.m4.xlarge instance type, batch mode | $47.52 |
ml.m4.2xlarge Inference (Batch) | Model inference on the ml.m4.2xlarge instance type, batch mode | $47.52 |
ml.m4.4xlarge Inference (Batch) | Model inference on the ml.m4.4xlarge instance type, batch mode | $47.52 |
ml.c5.2xlarge Inference (Batch) | Model inference on the ml.c5.2xlarge instance type, batch mode | $47.52 |
ml.c5.4xlarge Inference (Batch) | Model inference on the ml.c5.4xlarge instance type, batch mode | $47.52 |
ml.c5.9xlarge Inference (Batch) | Model inference on the ml.c5.9xlarge instance type, batch mode | $47.52 |
ml.m4.xlarge Inference (Real-Time) | Model inference on the ml.m4.xlarge instance type, real-time mode | $23.76 |
ml.m4.2xlarge Inference (Real-Time) | Model inference on the ml.m4.2xlarge instance type, real-time mode | $23.76 |
Vendor refund policy
No refunds are possible.
Legal
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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
johnsnowlabs: 6.0.0 Visual NLP: 6.0.0 Healthcare NLP: 6.0.0
Additional details
Inputs
- Summary
Input Format Image file or (Multiple and Single) PDF file are supported.
- Input MIME type
- application/octet-stream
https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/products/sagemaker/models/en.handwritten.transformer.extraction/inputs/real-time
https://github.com/JohnSnowLabs/spark-nlp-workshop/tree/master/products/sagemaker/models/en.handwritten.transformer.extraction/inputs/batch
Resources
Vendor resources
Support
Vendor support
For any assistance, please reach out to support@johnsnowlabs.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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