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The code is this:

// Compare two images by getting the L2 error (square-root of sum of squared error). double getSimilarity(const Mat A, const Mat B) { if (A.rows > 0 && A.rows == B.rows && A.cols > 0 && A.cols == B.cols) { // Calculate the L2 relative error between the 2 images. double errorL2 = norm(A, B, CV_L2); // Convert to a reasonable scale, since L2 error is summed across all pixels of the image. double similarity = errorL2 / (double)(A.rows * A.cols); return similarity; } else { //cout << "WARNING: Images have a different size in 'getSimilarity()'." << endl; return 100000000.0; // Return a bad value } }

If L2 relative error is a Euclidean Distance, what is this "Predict" and "Confidence" in opencv FaceRecognizer class?

Regards, Marcelo

The code is this:

// Compare two images by getting the the L2 error (square-root of sum of of squared error). double error). double getSimilarity(const Mat A, const Mat B) Mat B) { if (A.rows > 0 && A.rows == B.rows && A.cols > 0 && A.cols == B.cols) { // Calculate the L2 relative error between the 2 images. double errorL2 = norm(A, B, CV_L2); // Convert to a reasonable scale, since L2 error is summed across across all pixels of the image. double similarity = errorL2 / (double)(A.rows * A.cols); return similarity; } else { //cout << "WARNING: Images have a different size in in 'getSimilarity()'." << endl; return 100000000.0; // Return a bad value } }

}
}

If L2 relative error is a Euclidean Distance, what is this "Predict" and "Confidence" in opencv FaceRecognizer class?

Regards, Marcelo