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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
Eigen
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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