已经用cmake编译好的OpenCV与OpenCV-contrib
OpenCV（开源计算机视觉库）是一个强大的跨平台计算机视觉库，包含了众多图像处理和计算机视觉的算法。OpenCV-contrib是其扩展模块，包含了更多实验性的功能和最新的研究结果。本资源是已经使用CMake工具在Visual Studio 2019环境下编译好的OpenCV与OpenCV-contrib的版本，特别适合于在Windows系统上使用VS进行开发。
CMake是一个开源的跨平台自动化构建系统，它不直接构建项目，而是生成针对特定IDE（如Visual Studio、Xcode等）的项目文件。CMake的优点在于它可以管理不同平台和编译器下的构建过程，使得项目配置更加统一和简化。
在VS2019中使用这个预编译的OpenCV库，首先需要了解如何配置C++项目以链接到这些库。以下是一步一步的配置步骤：
1. **创建新项目**：在VS2019中，选择“创建新项目”，然后选择C++的控制台应用程序或其他类型的项目。
2. **配置CMake**：如果项目使用CMake，需要在CMakeLists.txt文件中指定OpenCV库的位置。添加如下代码：
```
find_package(OpenCV REQUIRED)
include_directories(${OpenCV_INCLUDE_DIRS})
target_link_libraries( ${OpenCV_LIBS})
```
这里的``应替换为你的项目名称。
3. **设置库路径**：在项目属性中，需要配置附加库目录，指向OpenCV的lib文件夹。同时，配置附加包含目录，指向头文件所在的include文件夹。
4. **使用OpenCV**：现在可以开始在代码中导入OpenCV头文件并使用库函数。例如：
```cpp
#include
#include
int main() {
cv::Mat img = cv::imread("image.jpg");
if (img.empty()) {
std::cout << "无法读取图片" << std::endl;
return -1;
}
cv::imshow("Image", img);
cv::waitKey(0);
return 0;
}
```
5. **运行与调试**：保存所有更改后，可以在VS2019中编译并运行项目。如果一切配置正确，程序将能够读取并显示图像。
在实际开发中，OpenCV可以应用于各种场景，如图像处理、特征检测、目标识别、视频分析等。OpenCV-contrib中的扩展模块提供了额外的功能，如深度学习模块（DNN）、XFeatures2D（特征检测与描述符）以及SIFT和SURF等经典算法。
注意，使用预编译库时，确保库版本与你的项目需求匹配，并且注意动态库与静态库的使用，这可能影响最终程序的大小和运行依赖。同时，对于OpenCV的更新版本，可能会有新的API和功能，因此定期检查官方文档和更新是很有必要的。
这个压缩包提供的预编译OpenCV与OpenCV-contrib库为开发者节省了编译时间，可以直接在VS2019项目中使用，提高了开发效率。只需正确配置项目，就可以充分利用OpenCV的强大功能进行计算机视觉相关的开发工作。
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