Calamari OCR vs EasyOCR
Calamari OCR
github.comEasyOCR
github.comSide by side
| Figure | Calamari OCR | EasyOCR |
|---|---|---|
| Price from | — | Free |
| Free plan | — | Yes |
| Free trial | — | — |
| Open source | — | — |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | Yes | Yes |
| API | Yes | — |
| Self-hosted | Yes | Yes |
| Plans published | 0 | 1 |
| Spec score · OCR API Software | 7.4 (#24) | 8.4 (#7) |
| Customization | The engine can be integrated and customized from Python scripts, and the documentation includes a Python API. | The API supports custom recognition networks and configurable detection, recognition, decoding, and text-box merging options. |
| Input formats | The documentation lists Plain files, PageXML, Abbyy, and HDF5 dataset formats. | Images can be supplied as a file path, NumPy array, bytes, or URL. |
| Installation | The README says Calamari is available on PyPI and gives `pip install calamari-ocr` as the installation command. | The maker documents installation through pip, from source, or with Docker; Windows users may need to install PyTorch manually first. |
| License | The GitHub repository identifies its license as GPL-3.0. | The public GitHub repository identifies EasyOCR as licensed under Apache-2.0. |
| Notable limitation | The command line documentation states that currently only OCR on lines is supported. | The README lists handwritten text support as planned work. |
| Purpose | Calamari is a line-based OCR engine based on OCRopy and Kraken, written in Python 3. | EasyOCR is a Python module for extracting text from images, including natural scene text and dense document text. |
| Support | The project links users to its documentation for further installation and usage instructions. | The repository directs enterprise inquiries to Jaided AI for custom OCR/AI implementation, training or fine-tuning, and deployment services. |
Plans
In their own words
Calamari OCR
Calamari OCR has no write-up on Specifiction yet; its figures are above.
EasyOCR
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.