Use cases for popular libraries and frameworks in the C++ ecosystem

Popular C libraries/frameworks and their application scenarios: Boost: strings, concurrency, mathematics, regular expressions Eigen: linear algebra, matrix operations OpenCV: image/video processing, computer vision Qt: cross-platform GUI development CUDA: parallelism Programming, GPU-accelerated TensorFlow: Machine Learning/Deep Learning Practical Case: Using OpenCV to process images

Application scenarios of popular libraries and frameworks in the C ecosystem

In the C ecosystem, there are a large number of libraries and frameworks to choose from, each with its specific use cases. The following are some popular libraries and frameworks and their common application scenarios:

Boost

• ##Use cases: String operations, concurrency, mathematics Functions, regular expressions

Eigen

##Use examples:
• Linear algebra and matrix operations

Use cases:
• Image and video processing, computer vision

Use case:
• Cross-platform graphical user interface development

Use cases:
• Parallel programming, using GPU to accelerate computing

Use cases:
• Machine learning and deep learning

The following is a practical case of using OpenCV to process images:

#include <opencv2/opencv.hpp>

int main() {
  // 从文件加载图像
  cv::Mat image = cv::imread("image.jpg");

  // 转换图像为灰度图
  cv::cvtColor(image, image, cv::COLOR_BGR2GRAY);

  // 使用阈值化二值化图像
  cv::threshold(image, image, 127, 255, cv::THRESH_BINARY);

  // 保存输出图像
  cv::imwrite("output.jpg", image);

  return 0;
}

In this example , we used the OpenCV library to load an image, convert it to grayscale, and binarize it using thresholding. Finally, we save the processed image to a file.

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