EasyOCR vs Surya

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.

Surya is a 650M-parameter OCR model for extracting text and analyzing document structure. It handles layout, reading order and tables, and supports OCR in 91 languages. Surya 2 returns page content as structured blocks that can include HTML, polygons, bounding boxes, confidence values and reading order. Table recognition can provide row and column geometry; full mode can also return HTML with spanning cells and header rows. Equations found in page OCR are represented as KaTeX-compatible LaTeX within math tags. Users can work with a Python package, command-line tools or an interactive Streamlit app for images and PDFs. Layout, OCR and table recognition require an inference backend: vLLM on NVIDIA GPUs or llama.cpp on CPU and Apple Silicon, or a connection to an existing server. Surya is free and open source. The code uses Apache 2.0, while the model weights have a separate modified AI Pubs Open Rail-M license with commercial-use conditions. It is specialized for documents, not photos or natural scenes.