Side by side
Amazon Textract AnalyzeExpense vs docTR
Both stand on ocr api software. Which one you can start free with, which one lets you read the code, and what each costs once you pay.
AnalyzeExpense extracts and normalizes invoice and receipt details, including unlabeled fields, for applications that process financial documents. Check the English-only processing and per-page pricing; AWS lists $0.01 per page for the first million monthly pages in US West (Oregon).
Visit Amazon Textract AnalyzeExpense
docTR offers OCR, layout analysis, and custom model training in a free library, with installation and deployment options including Docker and a REST API template. Check the Python requirement and AWS Lambda guidance against your environment.
Visit docTRThe facts
| Amazon Textract AnalyzeExpense | docTR | |
|---|---|---|
| Free plan | Yes | Yes |
| Open source | No | Not published |
| Runs on | API, Self-hosted, Web | API, Linux, Mac, Self-hosted, Windows |
| Lowest paid plan | See the plans | Free or on request |
| Plans published | 5 | 1 |
| Maker | Not published | docTR |
| Website | aws.amazon.com | mindee.github.io |
| On ocr api software | #1 of 29 | #2 of 29 |
Amazon Textract AnalyzeExpense: what it does well
- Extracts line items and summary fields from receipts and invoices.
- Can identify vendors from logos and read unlabeled fields.
- Supports synchronous and asynchronous processing.
- Free Tier offers up to 100 pages monthly for three months to new AWS customers.
- Supports multiple SDK languages, including Python, Java, and JavaScript.
What to know first
- No free plan is listed.
- Invoice and receipt processing is English only.
- Supported inputs are PDF, JPG, or PNG.
- AWS says inputs may be used to improve Textract and related AI technologies.
docTR: what it does well
- Pretrained two-stage text detection and recognition
- Layout prediction identifies tables, figures, and headers
- Supports CPU and GPU inference
- Custom training for detection, recognition, layout, and tables
- Apache License 2.0
What to know first
- Installation requires Python 3.11 or higher
- AWS Lambda requires multiprocessing to be disabled
- Lambda model cache must be placed in /tmp
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