Dlib VS tesseract-ocr

Compare Dlib vs tesseract-ocr and see what are their differences.

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Dlib tesseract-ocr
33 121
13,031 58,182
- 1.4%
8.2 8.9
6 days ago 8 days ago
C++ C++
Boost Software License 1.0 Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

Dlib

Posts with mentions or reviews of Dlib. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-06-06.

tesseract-ocr

Posts with mentions or reviews of tesseract-ocr. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-12-27.

What are some alternatives?

When comparing Dlib and tesseract-ocr you can also consider the following projects:

mlpack - mlpack: a fast, header-only C++ machine learning library

PaddleOCR - Awesome multilingual OCR toolkits based on PaddlePaddle (practical ultra lightweight OCR system, support 80+ languages recognition, provide data annotation and synthesis tools, support training and deployment among server, mobile, embedded and IoT devices)

Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration

pytesseract - A Python wrapper for Google Tesseract

Boost - Super-project for modularized Boost

EasyOCR - Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.

Face Recognition - The world's simplest facial recognition api for Python and the command line

OpenCV - Open Source Computer Vision Library

Caffe - Caffe: a fast open framework for deep learning.