EasyOCR vs Kraken
EasyOCR
github.comKraken
kraken.reSide by side
| Figure | EasyOCR | Kraken |
|---|---|---|
| Price from | Free | — |
| Free plan | Yes | — |
| Free trial | — | — |
| Open source | — | — |
| Windows | Yes | — |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| API | — | Yes |
| Self-hosted | Yes | — |
| Plans published | 1 | 0 |
| Spec score · OCR API Software | 8.4 (#7) | 7.5 (#22) |
| Spec score · OCR software | 8.4 (#13) | 7.3 (#36) |
| Free plan | Yes | Yes |
| Handwriting OCR | No | Yes |
| Supported inputs | image | both |
| Installation | The maker documents installation through pip, from source, or with Docker; Windows users may need to install PyTorch manually first. | The documentation says Kraken can be installed on Linux or Mac OS X, on x64 and ARM, using pip or Anaconda. |
| Integrations | The repository says EasyOCR is integrated into Hugging Face Spaces using Gradio and provides a web demo. | The documentation lists eScriptorium, OCR4all, the OCR-D suite, and arkindex by Teklia as applications or suites integrated with Kraken. |
| Primary platform | desktop | desktop |
| Purpose | EasyOCR is a Python module for extracting text from images, including natural scene text and dense document text. | Kraken is an open-source automatic text recognition system optimized for historical documents and non-Latin scripts. |
| Support | The repository directs enterprise inquiries to Jaided AI for custom OCR/AI implementation, training or fine-tuning, and deployment services. | The project welcomes feedback, pull requests, bug reports, and feature suggestions through its GitHub repository. |
Plans
In their own words
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.