Amazon Textract AnalyzeExpense vs EasyOCR

Amazon Textract AnalyzeExpense extracts financial text and data from invoices and receipts through an API or web service. Results can include grouped line items and summary fields such as purchased items, prices, receipt headers, and vendor names. The API can normalize field names and column headers to help downstream applications compare documents. It can also identify vendors from logos and extract items, quantities, and prices when those details have no labels or column headers. Supply documents as image bytes or an Amazon S3 object; AWS advises PDF, JPG, or PNG files, and invoice and receipt processing is English only. AnalyzeExpense processes synchronously. Asynchronous invoice and receipt analysis uses StartExpenseAnalysis and GetExpenseAnalysis. The listed rate is $0.01 per page for the first 1 million pages per month in US West (Oregon), then $0.008 per page; custom high-volume pricing is available. New AWS customers can use the Free Tier for three months, up to 100 pages per month. AWS says inputs may be used to improve Textract and related AI technologies, with an Organizations opt-out policy.

EasyOCR is a Python module that extracts text from images, including natural scene text and dense document text. The project says it supports more than 80 languages, and compatible languages can be processed together. Its readtext method can return recognized text with bounding-box coordinates and confidence values, or provide text alone. Inputs can be image paths, NumPy arrays, bytes, or URLs. The Reader can use a GPU when available or run in CPU-only mode. Pretrained models download automatically during use, with manual downloads available for offline environments. The API also allows custom recognition networks and settings for detection, recognition, decoding, and text-box merging. Installation options include pip, source, and Docker; Windows users may need to install PyTorch manually first. A web demo is available, and the repository says EasyOCR is integrated into Hugging Face Spaces through Gradio. The public repository identifies the project as Apache-2.0 licensed. There is no paid plan listed. Handwriting recognition is not supported; the README lists it as planned work.