Opencv 如何从ML套件人脸标志点估计人脸姿势

我正在使用iOS上的Firebase ML工具包检测人脸。虽然它提供了Euler Y和Z角度，但不提供Euler X角度（俯仰）。因此，我想尝试使用OpenCV solvePnp计算音高，如下所述：

这是我的目标C函数：

+(void) estimatePose:(FIRVisionFace *)face imgSize:(CGSize)imgSize {

    // Contour legend: https://firebase.google.com/docs/ml-kit/images/examples/face_contours.svg
    FIRVisionFaceContour* faceOval = [face contourOfType:FIRFaceContourTypeFace];
    FIRVisionFaceContour* leftEyeContour = [face contourOfType:FIRFaceContourTypeLeftEye];
    FIRVisionFaceContour* rightEyeContour = [face contourOfType:FIRFaceContourTypeRightEye];
    FIRVisionFaceContour* noseBridge = [face contourOfType:FIRFaceContourTypeNoseBridge];
    FIRVisionFaceContour* upperLipTop = [face contourOfType:FIRFaceContourTypeUpperLipTop];

    FIRVisionPoint* chin = faceOval.points[18];
    FIRVisionPoint* leftEyeLeftCorner = leftEyeContour.points[0];
    FIRVisionPoint* rightEyeRightCorner = rightEyeContour.points[8];
    FIRVisionPoint* noseTip = noseBridge.points[1];
    FIRVisionPoint* leftMouthCorner = upperLipTop.points[0];
    FIRVisionPoint* rightMouthCorner = upperLipTop.points[10];

    // 2D/3D model points using https://www.learnopencv.com/head-pose-estimation-using-opencv-and-dlib/#code
    image_points.push_back( cv::Point2d(noseTip.x.doubleValue, noseTip.y.doubleValue) );    // Nose tip
    image_points.push_back( cv::Point2d(chin.x.doubleValue, chin.y.doubleValue) );    // Chin
    image_points.push_back( cv::Point2d(leftEyeLeftCorner.x.doubleValue, leftEyeLeftCorner.y.doubleValue) );    // Left eye left corner
    image_points.push_back( cv::Point2d(rightEyeRightCorner.x.doubleValue, rightEyeRightCorner.y.doubleValue) );     // Right eye right corner
    image_points.push_back( cv::Point2d(leftMouthCorner.x.doubleValue, leftMouthCorner.y.doubleValue) );    // Left Mouth corner
    image_points.push_back( cv::Point2d(rightMouthCorner.x.doubleValue, rightMouthCorner.y.doubleValue) );    // Right mouth corner

    model_points.push_back(cv::Point3d(0.0f, 0.0f, 0.0f));               // Nose tip
    model_points.push_back(cv::Point3d(0.0f, -330.0f, -65.0f));          // Chin
    model_points.push_back(cv::Point3d(-225.0f, 170.0f, -135.0f));       // Left eye left corner
    model_points.push_back(cv::Point3d(225.0f, 170.0f, -135.0f));        // Right eye right corner
    model_points.push_back(cv::Point3d(-150.0f, -150.0f, -125.0f));      // Left Mouth corner
    model_points.push_back(cv::Point3d(150.0f, -150.0f, -125.0f));       // Right mouth corner

    double focal_length = imgSize.width; // Approximate focal length.
    cv::Point2d center = cv::Point2d(imgSize.width / 2, imgSize.height / 2);
    cv::Mat camera_matrix = (cv::Mat_<double>(3,3) << focal_length, 0, center.x, 0 , focal_length, center.y, 0, 0, 1);
    cv::Mat dist_coeffs = cv::Mat::zeros(4,1,cv::DataType<double>::type); // Assuming no lens distortion

    // Output rotation and translation
    cv::Mat rotation_vector; // Rotation in axis-angle form
    cv::Mat translation_vector;

    // Solve for pose
    cv::solvePnP(model_points, image_points, camera_matrix, dist_coeffs, rotation_vector, translation_vector);

    NSLog(@"Rotation Vector %f %f %f", rotation_vector.at<float>(0), rotation_vector.at<float>(1), rotation_vector.at<float>(2));
}

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我做错了什么？

问题在于日志语句。它需要打印双精度而不是浮动：

NSLog(@"Rotation Vector %f %f %f", rotation_vector.at<double>(0), rotation_vector.at<double>(1), rotation_vector.at<double>(2));

NSLog（@“旋转向量%f%f%f”，旋转向量在（0），旋转向量在（1），旋转向量在（2））；

此外，旋转向量不是欧拉角。它需要转换为：

---

问题在于日志语句。它需要打印双精度而不是浮动：

NSLog(@"Rotation Vector %f %f %f", rotation_vector.at<double>(0), rotation_vector.at<double>(1), rotation_vector.at<double>(2));

NSLog（@“旋转向量%f%f%f”，旋转向量在（0），旋转向量在（1），旋转向量在（2））；

此外，旋转向量不是欧拉角。它需要转换为：

嗨，Jacob——我对将EulerX检测添加到ML套件Vision的颤振库很感兴趣。您的解决方案是如何工作的？嗨，Jacob——我对将EulerX检测添加到用于ML Kit Vision的颤振库很感兴趣。你的解决方案怎么样？