Sold by: MLism Inc.
Deployed on AWS
YomiToku is a proprietary document analysis engine specialized for Japanese. It integrates AI OCR plus layout and table parsing models, accurately structuring vertical text, multi column documents, and complex business forms. It supports a wide range of use cases, including generating data for RAG / search, creating searchable PDFs, and extracting information from table data.
We provide **yomitoku-client** as a client SDK to help you use this product more conveniently.For more details, please refer to the link below:
https://github.com/MLism-Inc/yomitoku-client
For long-term or large-scale use, this product is also available through private offers.Please contact our support team for pricing information.
Overview
YomiToku is a proprietary document analysis engine specialized for Japanese. It integrates AI OCR plus layout and table parsing models, accurately structuring vertical text, multi column documents, and complex business forms. It supports a wide range of use cases, including generating data for RAG / search, creating searchable PDFs, and extracting information from table data.
** This product is intended to be offered through a private offer, so please contact us for pricing.**
Highlights
- Each model is specifically trained for Japanese document images, supporting the recognition of over 7,000 Japanese characters, including vertical text and other layout structures unique to Japanese documents. (It also supports English documents.)
- Equipped with four AI models trained on Japanese datasets: text detection, text recognition, layout analysis, and table structure recognition. All models are independently trained and optimized for Japanese documents, delivering high-precision inference.
- By leveraging layout analysis, table structure parsing, and reading order estimation, it extracts information while preserving the semantic structure of the document layout.
Details
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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.g4dn.xlarge Inference (Batch) Recommended | Model inference on the ml.g4dn.xlarge instance type, batch mode | $10.00 |
ml.g4dn.xlarge Inference (Real-Time) Recommended | Model inference on the ml.g4dn.xlarge instance type, real-time mode | $10.00 |
ml.g5.xlarge Inference (Batch) | Model inference on the ml.g5.xlarge instance type, batch mode | $10.00 |
ml.g5.xlarge Inference (Real-Time) | Model inference on the ml.g5.xlarge instance type, real-time mode | $10.00 |
ml.g6.xlarge Inference (Real-Time) | Model inference on the ml.g6.xlarge instance type, real-time mode | $10.00 |
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
- Minor bug fixes
- Improved efficiency in text recognition model processing
- Hyperparameter tuning of the text detection model
Additional details
Inputs
- Summary
Supported Content Types:
- application/pdf - PDF documents (multi-page supported)
- image/jpeg - JPEG images
- image/png - PNG images
- image/tiff - TIFF images
Request Body: Send the binary file data directly in the request body with appropriate Content-Type header.
Example Usage: bash aws sagemaker-runtime invoke-endpoint \ --endpoint-name ${ENDPOINT_NAME} \ --content-type "application/pdf" \ --body fileb://demo/sample.pdf \ --region ${AWS_REGION} \ output.json
Sample Image Source: The sample images used in this documentation are from 「広報誌 令和 6 年 11 月号」 published by 総務省.
- Input MIME type
- application/pdf, image/jpeg, image/png, image/tiff
https://mlism-marketplace-documents.s3.ap-northeast-1.amazonaws.com/samples/gallery1.jpg
https://mlism-marketplace-documents.s3.ap-northeast-1.amazonaws.com/samples/gallery1.jpg
Support
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