Sold by: Upstage
Overview
Upstage Document OCR (Optical Character Recognition) is designed to efficiently detect and recognize text from a wide range of document images, ensuring high accuracy and versatility across various languages and image qualities.
Highlights
- ### Key Features - **Word-Level Coordinate/Transcription Results:** Provides word-level bounding box and transcription for easy text processing. - **Robustness on Rotated Documents:** Detects and corrects text orientation in rotated documents. - **Multilingual Text Detection:** Recognizes texts in multiple languages.(English, Chinese, Japanese, and Korean) - **Confidence Scores:** Outputs word-level confidence scores to assess reliability of extracted text for further verification.
- ### Key Applications - **Automated Data Entry:** Converts printed or handwritten documents into digital text, streamlining data entry and reducing manual effort. - **Archival and Digitization:** Digitizes documents, books, and records, preserving information and making it searchable and accessible. - **Multilingual Document Processing:** Handles documents in English and CJK (Chinese, Japanese, Korean), enabling effective international document processing.
- ### Key Tasks - Text Extraction - Document Digitization - Multilingual Document Handling - Automated Data Entry - Information Retrieval
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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.m5.12xlarge Inference (Batch) Recommended | Model inference on the ml.m5.12xlarge instance type, batch mode | $0.00 |
ml.g5.xlarge Inference (Real-Time) Recommended | Model inference on the ml.g5.xlarge instance type, real-time mode | $1.50 |
ml.p3.2xlarge Inference (Real-Time) | Model inference on the ml.p3.2xlarge instance type, real-time mode | $1.50 |
ml.g6.2xlarge Inference (Real-Time) | Model inference on the ml.g6.2xlarge instance type, real-time mode | $1.50 |
ml.g5.2xlarge Inference (Real-Time) | Model inference on the ml.g5.2xlarge instance type, real-time mode | $1.50 |
ml.g4dn.xlarge Inference (Real-Time) | Model inference on the ml.g4dn.xlarge instance type, real-time mode | $1.50 |
ml.g6.xlarge Inference (Real-Time) | Model inference on the ml.g6.xlarge instance type, real-time mode | $1.50 |
Vendor refund policy
We do not support any refunds currently.
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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
The patchify feature has been added.
Patchify processes large images (2560 pixels or more) by dividing them into smaller patches for inference. This enhances the accuracy of inference for large images.
Additional details
Inputs
- Summary
Provide an image file in binary format to the request body.
- Input MIME type
- multipart/form-data
https://developers.upstage.ai/_next/image?url=%2Fimages%2Fhello.png&w=384&q=75
https://developers.upstage.ai/_next/image?url=%2Fimages%2Fhello.png&w=384&q=75
Input data descriptions
The following table describes supported input data fields for real-time inference and batch transform.
Field name | Description | Constraints | Required |
|---|---|---|---|
use_patchify | Patchify processes large images (2560 pixels or more) by dividing them into smaller patches for inference. This enhances the accuracy of inference for large images. | Default value: false
Type: Categorical
Allowed values: true, false | No |
Resources
Vendor resources
Support
Vendor support
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AWS infrastructure support
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This product has charges associated with it for seller support. DocAI OCR Pro extracts, processes, and digitizes text from documents and images with high accuracy, running seamlessly on Ubuntu.
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