EasyOCR vs OCRmyPDF

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.

OCRmyPDF is free software that adds searchable text to scanned PDF files while retaining the original PDF as much as possible. It uses Tesseract to recognize text in page images and produces PDF/A-2b by default, with regular PDF output available as an alternative. Image-processing options such as deskew can adjust pages to support visual quality and OCR accuracy. When a PDF already contains text, its processing modes can stop with an error, skip affected pages, redo OCR, or force OCR across all pages. OCRmyPDF can also be used as a Python library, and plugins can customize processing steps. Installation methods are documented for Linux, macOS, Windows, FreeBSD, and Docker; Paperless-ngx and Nextcloud OCR are named as third-party integrations. Results may be poor for low-quality scans or languages not specified for processing, and handwriting is not recognized. The project also notes that accuracy may trail commercial solutions. Its documentation advises processing only PDFs users trust and warns that its example Docker web service has no security measures and is not meant for public internet deployment.