pykinect azure 手眼标定程序

以下是使用PyKinect和Azure Kinect进行手眼标定的示例程序：

import numpy as np
import cv2
import open3d as o3d
from pykinect2 import PyKinectRuntime, PyKinectV2
from pyk4a import Config, PyK4A
from pyk4a import PyK4APlayback

# 这里使用PyK4A库，也可以使用Azure Kinect SDK
def get_kinect_intrinsics():
    kinect = PyKinectRuntime.PyKinectRuntime(PyKinectV2.FrameSourceTypes_Color | PyKinectV2.FrameSourceTypes_Depth)
    color_intrinsics = kinect.color_frame_desc
    depth_intrinsics = kinect.depth_frame_desc
    kinect.close()
    return color_intrinsics, depth_intrinsics

def get_azure_intrinsics():
    k4a = PyK4A(Config())
    k4a.start()
    color_intrinsics = k4a.calibration.get_camera_matrix(PyK4A.CalibrationType.COLOR)
    depth_intrinsics = k4a.calibration.get_camera_matrix(PyK4A.CalibrationType.DEPTH)
    k4a.stop()
    return color_intrinsics, depth_intrinsics

def depth_to_color(kinect_intrinsics, depth_intrinsics, depth_image):
    R = np.eye(3)
    t = np.zeros((3, 1))
    fx = depth_intrinsics.intrinsic_matrix[0][0]
    fy = depth_intrinsics.intrinsic_matrix[1][1]
    cx = depth_intrinsics.intrinsic_matrix[0][2]
    cy = depth_intrinsics.intrinsic_matrix[1][2]
    k4a_fx = kinect_intrinsics.intrinsic_matrix[0][0]
    k4a_fy = kinect_intrinsics.intrinsic_matrix[1][1]
    k4a_cx = kinect_intrinsics.intrinsic_matrix[0][2]
    k4a_cy = kinect_intrinsics.intrinsic_matrix[1][2]
    depth_scale = 0.001
    point_cloud = o3d.geometry.PointCloud()
    depth_image = depth_image * depth_scale
    rows, cols = depth_image.shape
    for i in range(rows):
        for j in range(cols):
            z = depth_image[i, j]
            if z == 0:
                continue
            x = (j - cx) * z / fx
            y = (i - cy) * z / fy
            point_cloud.points.append([x, y, z])
            point_cloud.colors.append([0, 0, 0])
    extrinsics = np.eye(4)
    k4a_extrinsics = np.array([[-1, 0, 0, 0],
                               [0, 1, 0, 0],
                               [0, 0, -1, 0],
                               [0, 0, 0, 1]])
    extrinsics[:3, :3] = R
    extrinsics[:3, 3] = t.reshape(-1)
    k4a_extrinsics[:3, :3] = R
    k4a_extrinsics[:3, 3] = t.reshape(-1)
    point_cloud.transform(extrinsics)
    return point_cloud, k4a_extrinsics

def main():
    # 获取Kinect/ Azure Kinect intrinsics
    kinect_intrinsics, depth_intrinsics = get_kinect_intrinsics()
    azure_intrinsics = get_azure_intrinsics()

    # 获取深度图和彩色图
    k4a = PyK4APlayback("path/to/recording.mkv")
    k4a.open()
    while True:
        capture = k4a.get_next_capture()
        if capture.depth is None:
            break
        depth_image = np.asarray(capture.depth)
        color_image = np.asarray(capture.color)

        # 将深度图转换为点云
        point_cloud, k4a_extrinsics = depth_to_color(kinect_intrinsics, depth_intrinsics, depth_image)

        # 显示点云
        vis = o3d.visualization.Visualizer()
        vis.create_window()
        vis.add_geometry(point_cloud)
        vis.run()
        vis.destroy_window()

        # 进行手眼标定
        # ...

    k4a.close()

if __name__ == '__main__':
    main()

在这个示例程序中，我们首先获取Kinect/ Azure Kinect的intrinsics，然后使用PyK4A获取深度图和彩色图。接着，我们将深度图转换为点云，并使用Open3D显示点云。最后，我们可以使用手眼标定算法对点云和机器人的位姿进行估计。

需要注意的是，这个示例程序仅仅是一个框架，具体的手眼标定算法需要根据实际情况进行选择和实现。