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What are the commonly used frameworks in C++?

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The C framework includes: cross-platform GUI component Qt, tool library collection Boost, general data structure STL, computer vision OpenCV, linear algebra Eigen, unit test Google Test and optimization library Ceres Solver.

What are the commonly used frameworks in C++?

C Commonly used frameworks

C As a powerful programming language, it has a large number of excellent frameworks that can be used Simplify the development process and improve code quality. Here are a few commonly used C frameworks:

1. Qt

#Qt is a cross-platform C framework that provides a rich set of GUI component libraries. For building desktop, mobile and embedded applications. It is known for its powerful graphics engine and cross-platform capabilities.

2. Boost

Boost is a large collection of C libraries that provide a wide range of tools and components, from algorithms and data structures to threading and unit testing. It is known for its high performance and portability.

3. C Standard Template Library (STL)

STL is a standard C library that provides common data structures and operations such as containers, algorithms, and iterators. It is widely used in C programming to provide support for code readability, maintainability, and performance.

4. OpenCV

OpenCV is a C framework focusing on computer vision. It provides a series of visual processing algorithms and optimization functions for image processing, video analysis, machine learning and other fields.

5. Eigen

Eigen is a templated linear algebra library. It provides an efficient set of matrix and vector operations and supports a variety of compilers and platforms. It is widely used in scientific computing, image processing and machine learning.

6. Google Test

Google Test is a C framework for unit testing. It provides a flexible set of assertion macros and testing tools that simplify the writing and maintenance of unit tests.

7. Ceres Solver

Ceres Solver is a C optimization library. It provides a variety of optimization algorithms and linear algebra tools for large-scale numerical optimization problems. It is widely used in fields such as robotics, computer vision, and machine learning.

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