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A Python wrapper for Google Tesseract
Quick Overview
UB-Mannheim/tesseract is a GitHub repository that provides Windows installer and build scripts for Tesseract OCR engine. It aims to simplify the installation process of Tesseract on Windows systems and includes pre-built binaries for various languages.
Pros
- Easy installation of Tesseract OCR on Windows systems
- Includes pre-built binaries for multiple languages
- Regular updates and maintenance
- Provides both 32-bit and 64-bit versions
Cons
- Limited to Windows operating systems
- May not always have the latest Tesseract version immediately available
- Requires manual download and installation process
- Limited customization options compared to building from source
Getting Started
- Visit the releases page of the UB-Mannheim/tesseract repository.
- Download the appropriate installer for your system (32-bit or 64-bit).
- Run the installer and follow the on-screen instructions.
- Add the Tesseract installation directory to your system's PATH environment variable.
- Open a command prompt and verify the installation by running:
tesseract --version
- To use Tesseract OCR in your project, you can now call it from the command line or use it with various programming languages that have Tesseract bindings.
Competitor Comparisons
Python-based tools for document analysis and OCR
Pros of ocropy
- Specialized for historical document OCR with better handling of degraded texts
- Includes layout analysis and text line detection capabilities
- More flexible and customizable for specific OCR tasks
Cons of ocropy
- Less actively maintained compared to Tesseract
- Smaller community and fewer resources for support
- May require more technical expertise to set up and use effectively
Code Comparison
ocropy:
from ocrolib import psegmentation, ocrolib
image = ocrolib.read_image_gray(image_path)
binary = ocrolib.binarize_sauvola(image)
segmentation = psegmentation.segment(binary)
Tesseract:
import pytesseract
from PIL import Image
image = Image.open(image_path)
text = pytesseract.image_to_string(image)
ocropy focuses on preprocessing and segmentation, while Tesseract provides a more straightforward API for text extraction. ocropy offers more granular control over the OCR process, but Tesseract is generally easier to use for basic OCR tasks.
Pure Javascript OCR for more than 100 Languages 📖🎉🖥
Pros of tesseract.js
- Runs in the browser, making it easy to integrate into web applications
- No need for server-side installation or configuration
- Supports multiple languages and can be easily customized
Cons of tesseract.js
- Generally slower performance compared to the native Tesseract implementation
- May have limitations in handling complex or large-scale OCR tasks
- Relies on WebAssembly, which might not be supported in older browsers
Code Comparison
tesseract.js:
import Tesseract from 'tesseract.js';
Tesseract.recognize('image.jpg', 'eng')
.then(({ data: { text } }) => {
console.log(text);
});
Tesseract (C++):
#include <tesseract/baseapi.h>
tesseract::TessBaseAPI *api = new tesseract::TessBaseAPI();
api->Init(NULL, "eng");
api->SetImage(image);
char* outText = api->GetUTF8Text();
printf("OCR output:\n%s", outText);
The code examples demonstrate the simplicity of using tesseract.js in a JavaScript environment compared to the more complex C++ implementation required for the native Tesseract library. However, the native version offers more fine-grained control and potentially better performance for advanced use cases.
A Python wrapper for Google Tesseract
Pros of pytesseract
- Python-specific wrapper, making it easier to integrate Tesseract OCR into Python projects
- Simplified API for common OCR tasks
- Includes additional utility functions for image processing and text extraction
Cons of pytesseract
- Limited to Python language, whereas tesseract can be used with multiple programming languages
- May have a slight performance overhead due to the Python wrapper
- Requires separate installation of Tesseract OCR engine
Code Comparison
pytesseract:
import pytesseract
from PIL import Image
text = pytesseract.image_to_string(Image.open('image.png'))
print(text)
tesseract (using command-line interface):
tesseract image.png output
cat output.txt
Summary
pytesseract is a Python-specific wrapper for Tesseract OCR, offering a more convenient API for Python developers. It simplifies integration but is limited to Python projects. tesseract, on the other hand, is the core OCR engine that can be used across multiple programming languages and platforms, providing more flexibility but requiring more setup for specific language integrations.
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Tesseract OCR
Table of Contents
About
This package contains an OCR engine - libtesseract and a command line program - tesseract.
Tesseract 4 adds a new neural net (LSTM) based OCR engine which is focused on line recognition, but also still supports the legacy Tesseract OCR engine of Tesseract 3 which works by recognizing character patterns. Compatibility with Tesseract 3 is enabled by using the Legacy OCR Engine mode (--oem 0). It also needs traineddata files which support the legacy engine, for example those from the tessdata repository.
Stefan Weil is the current lead developer. Ray Smith was the lead developer until 2018. The maintainer is Zdenko Podobny. For a list of contributors see AUTHORS and GitHub's log of contributors.
Tesseract has unicode (UTF-8) support, and can recognize more than 100 languages "out of the box".
Tesseract supports various image formats including PNG, JPEG and TIFF.
Tesseract supports various output formats: plain text, hOCR (HTML), PDF, invisible-text-only PDF, TSV, ALTO and PAGE.
You should note that in many cases, in order to get better OCR results, you'll need to improve the quality of the image you are giving Tesseract.
This project does not include a GUI application. If you need one, please see the 3rdParty documentation.
Tesseract can be trained to recognize other languages. See Tesseract Training for more information.
Brief history
Tesseract was originally developed at Hewlett-Packard Laboratories Bristol UK and at Hewlett-Packard Co, Greeley Colorado USA between 1985 and 1994, with some more changes made in 1996 to port to Windows, and some C++izing in 1998. In 2005 Tesseract was open sourced by HP. From 2006 until November 2018 it was developed by Google.
Major version 5 is the current stable version and started with release 5.0.0 on November 30, 2021. Newer minor versions and bugfix versions are available from GitHub.
Latest source code is available from main branch on GitHub. Open issues can be found in issue tracker, and planning documentation.
See Release Notes and Change Log for more details of the releases.
Installing Tesseract
You can either Install Tesseract via pre-built binary package or build it from source.
Before building Tesseract from source, please check that your system has a compiler which is one of the supported compilers.
Running Tesseract
Basic command line usage:
tesseract imagename outputbase [-l lang] [--oem ocrenginemode] [--psm pagesegmode] [configfiles...]
For more information about the various command line options use tesseract --help or man tesseract.
Examples can be found in the documentation.
For developers
Developers can use libtesseract C or
C++ API to build their own application. If you need bindings to libtesseract for other programming languages, please see the
wrapper section in the AddOns documentation.
Documentation of Tesseract generated from source code by doxygen can be found on tesseract-ocr.github.io.
Support
Before you submit an issue, please review the guidelines for this repository.
For support, first read the documentation, particularly the FAQ to see if your problem is addressed there. If not, search the Tesseract user forum, the Tesseract developer forum and past issues, and if you still can't find what you need, ask for support in the mailing-lists.
Mailing-lists:
- tesseract-ocr - For tesseract users.
- tesseract-dev - For tesseract developers.
Please report an issue only for a bug, not for asking questions.
License
The code in this repository is licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
NOTE: This software depends on other packages that may be licensed under different open source licenses.
Tesseract uses Leptonica library which essentially uses a BSD 2-clause license.
Dependencies
Tesseract uses Leptonica library for opening input images (e.g. not documents like pdf). It is suggested to use leptonica with built-in support for zlib, png and tiff (for multipage tiff).
Latest Version of README
For the latest online version of the README.md see:
https://github.com/tesseract-ocr/tesseract/blob/main/README.md
Top Related Projects
Python-based tools for document analysis and OCR
Pure Javascript OCR for more than 100 Languages 📖🎉🖥
A Python wrapper for Google Tesseract
Convert designs to code with AI
Introducing Visual Copilot: A new AI model to turn Figma designs to high quality code using your components.
Try Visual Copilot