基于深度学习和计算机视觉的实时人体姿态估计技术应用于医疗服务场景.zip

// // This file is auto-generated. Please don't modify it! // package org.opencv.calib3d; import java.util.ArrayList; import java.util.List; import org.opencv.calib3d.UsacParams; import org.opencv.core.Mat; import org.opencv.core.MatOfDouble; import org.opencv.core.MatOfPoint2f; import org.opencv.core.MatOfPoint3f; import org.opencv.core.Point; import org.opencv.core.Rect; import org.opencv.core.Scalar; import org.opencv.core.Size; import org.opencv.core.TermCriteria; import org.opencv.utils.Converters; // C++: class Calib3d public class Calib3d { // C++: enum <unnamed> public static final int CV_ITERATIVE = 0, CV_EPNP = 1, CV_P3P = 2, CV_DLS = 3, CvLevMarq_DONE = 0, CvLevMarq_STARTED = 1, CvLevMarq_CALC_J = 2, CvLevMarq_CHECK_ERR = 3, LMEDS = 4, RANSAC = 8, RHO = 16, USAC_DEFAULT = 32, USAC_PARALLEL = 33, USAC_FM_8PTS = 34, USAC_FAST = 35, USAC_ACCURATE = 36, USAC_PROSAC = 37, USAC_MAGSAC = 38, CALIB_CB_ADAPTIVE_THRESH = 1, CALIB_CB_NORMALIZE_IMAGE = 2, CALIB_CB_FILTER_QUADS = 4, CALIB_CB_FAST_CHECK = 8, CALIB_CB_EXHAUSTIVE = 16, CALIB_CB_ACCURACY = 32, CALIB_CB_LARGER = 64, CALIB_CB_MARKER = 128, CALIB_CB_SYMMETRIC_GRID = 1, CALIB_CB_ASYMMETRIC_GRID = 2, CALIB_CB_CLUSTERING = 4, CALIB_NINTRINSIC = 18, CALIB_USE_INTRINSIC_GUESS = 0x00001, CALIB_FIX_ASPECT_RATIO = 0x00002, CALIB_FIX_PRINCIPAL_POINT = 0x00004, CALIB_ZERO_TANGENT_DIST = 0x00008, CALIB_FIX_FOCAL_LENGTH = 0x00010, CALIB_FIX_K1 = 0x00020, CALIB_FIX_K2 = 0x00040, CALIB_FIX_K3 = 0x00080, CALIB_FIX_K4 = 0x00800, CALIB_FIX_K5 = 0x01000, CALIB_FIX_K6 = 0x02000, CALIB_RATIONAL_MODEL = 0x04000, CALIB_THIN_PRISM_MODEL = 0x08000, CALIB_FIX_S1_S2_S3_S4 = 0x10000, CALIB_TILTED_MODEL = 0x40000, CALIB_FIX_TAUX_TAUY = 0x80000, CALIB_USE_QR = 0x100000, CALIB_FIX_TANGENT_DIST = 0x200000, CALIB_FIX_INTRINSIC = 0x00100, CALIB_SAME_FOCAL_LENGTH = 0x00200, CALIB_ZERO_DISPARITY = 0x00400, CALIB_USE_LU = (1 << 17), CALIB_USE_EXTRINSIC_GUESS = (1 << 22), FM_7POINT = 1, FM_8POINT = 2, FM_LMEDS = 4, FM_RANSAC = 8, fisheye_CALIB_USE_INTRINSIC_GUESS = 1 << 0, fisheye_CALIB_RECOMPUTE_EXTRINSIC = 1 << 1, fisheye_CALIB_CHECK_COND = 1 << 2, fisheye_CALIB_FIX_SKEW = 1 << 3, fisheye_CALIB_FIX_K1 = 1 << 4, fisheye_CALIB_FIX_K2 = 1 << 5, fisheye_CALIB_FIX_K3 = 1 << 6, fisheye_CALIB_FIX_K4 = 1 << 7, fisheye_CALIB_FIX_INTRINSIC = 1 << 8, fisheye_CALIB_FIX_PRINCIPAL_POINT = 1 << 9, fisheye_CALIB_ZERO_DISPARITY = 1 << 10, fisheye_CALIB_FIX_FOCAL_LENGTH = 1 << 11; // C++: enum GridType (cv.CirclesGridFinderParameters.GridType) public static final int CirclesGridFinderParameters_SYMMETRIC_GRID = 0, CirclesGridFinderParameters_ASYMMETRIC_GRID = 1; // C++: enum HandEyeCalibrationMethod (cv.HandEyeCalibrationMethod) public static final int CALIB_HAND_EYE_TSAI = 0, CALIB_HAND_EYE_PARK = 1, CALIB_HAND_EYE_HORAUD = 2, CALIB_HAND_EYE_ANDREFF = 3, CALIB_HAND_EYE_DANIILIDIS = 4; // C++: enum LocalOptimMethod (cv.LocalOptimMethod) public static final int LOCAL_OPTIM_NULL = 0, LOCAL_OPTIM_INNER_LO = 1, LOCAL_OPTIM_INNER_AND_ITER_LO = 2, LOCAL_OPTIM_GC = 3, LOCAL_OPTIM_SIGMA = 4; // C++: enum NeighborSearchMethod (cv.NeighborSearchMethod) public static final int NEIGH_FLANN_KNN = 0, NEIGH_GRID = 1, NEIGH_FLANN_RADIUS = 2; // C++: enum PolishingMethod (cv.PolishingMethod) public static final int NONE_POLISHER = 0, LSQ_POLISHER = 1, MAGSAC = 2, COV_POLISHER = 3; // C++: enum RobotWorldHandEyeCalibrationMethod (cv.RobotWorldHandEyeCalibrationMethod) public static final int CALIB_ROBOT_WORLD_HAND_EYE_SHAH = 0, CALIB_ROBOT_WORLD_HAND_EYE_LI = 1; // C++: enum SamplingMethod (cv.SamplingMethod) public static final int SAMPLING_UNIFORM = 0, SAMPLING_PROGRESSIVE_NAPSAC = 1, SAMPLING_NAPSAC = 2, SAMPLING_PROSAC = 3; // C++: enum ScoreMethod (cv.ScoreMethod) public static final int SCORE_METHOD_RANSAC = 0, SCORE_METHOD_MSAC = 1, SCORE_METHOD_MAGSAC = 2, SCORE_METHOD_LMEDS = 3; // C++: enum SolvePnPMethod (cv.SolvePnPMethod) public static final int SOLVEPNP_ITERATIVE = 0, SOLVEPNP_EPNP = 1, SOLVEPNP_P3P = 2, SOLVEPNP_DLS = 3, SOLVEPNP_UPNP = 4, SOLVEPNP_AP3P = 5, SOLVEPNP_IPPE = 6, SOLVEPNP_IPPE_SQUARE = 7, SOLVEPNP_SQPNP = 8, SOLVEPNP_MAX_COUNT = 8+1; // C++: enum UndistortTypes (cv.UndistortTypes) public static final int PROJ_SPHERICAL_ORTHO = 0, PROJ_SPHERICAL_EQRECT = 1; // // C++: void cv::Rodrigues(Mat src, Mat& dst, Mat& jacobian = Mat()) // /** * Converts a rotation matrix to a rotation vector or vice versa. * * @param src Input rotation vector (3x1 or 1x3) or rotation matrix (3x3). * @param dst Output rotation matrix (3x3) or rotation vector (3x1 or 1x3), respectively. * @param jacobian Optional output Jacobian matrix, 3x9 or 9x3, which is a matrix of partial * derivatives of the output array components with respect to the input array components. * * \(\begin{array}{l} \theta \leftarrow norm(r) \\ r \leftarrow r/ \theta \\ R = \cos(\theta) I + (1- \cos{\theta} ) r r^T + \sin(\theta) \vecthreethree{0}{-r_z}{r_y}{r_z}{0}{-r_x}{-r_y}{r_x}{0} \end{array}\) * * Inverse transformation can be also done easily, since * * \(\sin ( \theta ) \vecthreethree{0}{-r_z}{r_y}{r_z}{0}{-r_x}{-r_y}{r_x}{0} = \frac{R - R^T}{2}\) * * A rotation vector is a convenient and most compact representation of a rotation matrix (since any * rotation matrix has just 3 degrees of freedom). The representation is used in the global 3D geometry * optimization procedures like REF: calibrateCamera, REF: stereoCalibrate, or REF: solvePnP . * * <b>Note:</b> More information about the computation of the derivative of a 3D rotation matrix with respect to its exponential coordinate * can be found in: * <ul> * <li> * A Compact Formula for the Derivative of a 3-D Rotation in Exponential Coordinates, Guillermo Gallego, Anthony J. Yezzi CITE: Gallego2014ACF * </li> * </ul> * * <b>Note:</b> Useful information on SE(3) and Lie Groups can be found in: * <ul> * <li> * A tutorial on SE(3) transformation parameterizations and on-manifold optimization, Jose-Luis Blanco CITE: blanco2010tutorial * </li> * <li> * Lie Groups for 2D and 3D Transformation, Ethan Eade CITE: Eade17 * </li> * <li> * A micro Lie theory for state estimation in robotics, Joan Solà, Jérémie Deray, Dinesh Atchuthan CITE: Sol2018AML * </li> * </ul> */ public static void Rodrigues(Mat src, Mat dst, Mat jacobian) { Rodrigues_0(src.nativeObj, dst.nativeObj, jacobian.