cv::Mat img1 = cv::imread("img1.png"); cv::Mat img2 = cv::imread("img2.png"); cv::Mat fft_img1, fft_img2; cv::dft(img1, fft_img1, cv::DFT_COMPLEX_OUTPUT); cv::dft(img2, fft_img2, cv::DFT_COMPLEX_OUTPUT); cv::Mat conj_img1; cv::magnitude(fft_img1, conj_img1, fft_img1); cv::phase(fft_img1, fft_img1); cv::Mat conj_img2; cv::magnitude(fft_img2, conj_img2, fft_img2); cv::phase(fft_img2, fft_img2); cv::Mat correlation; cv::mulSpectrums(fft_img1, fft_img2, correlation, cv::DFT_COMPLEX_OUTPUT); cv::idft(correlation, correlation, cv::DFT_SCALE); cv::normalize(correlation, correlation, 0, 1, cv::NORM_MINMAX); AnalysisResultPtr result(new AnalysisResult()); result->phase = correlation; return result;
tensorflow::Scope scope = tensorflow::Scope::NewRootScope(); tensorflow::Output tensor = /* some complex tensor */; tensorflow::Output magnitude = tensorflow::complex_abs(tensor); tensorflow::Output phase = tensorflow::angle(tensor); AnalysisResultPtr result(new AnalysisResult()); result->phase = phase; return result;Package/library: The package/library that provides the `getPhase` function cannot be determined solely from the function name. However, based on the examples provided, it can be inferred that the library is likely a C++ data analysis library that supports complex-valued data and Fourier transforms. Possible candidates include OpenCV, FFTW, and Eigen.