请用python写一个使用realsense2库进行骨骼识别的代码

以下是使用Python和realsense2库进行骨骼识别的代码：

import pyrealsense2 as rs
import numpy as np

# Configure depth and color streams
pipeline = rs.pipeline()
config = rs.config()
config.enable_stream(rs.stream.depth, 640, 480, rs.format.z16, 30)
config.enable_stream(rs.stream.color, 640, 480, rs.format.bgr8, 30)

# Start streaming
pipeline.start(config)

# Create a pipeline profile object
profile = pipeline.get_active_profile()

# Get the depth sensor and its depth scale
depth_sensor = profile.get_device().first_depth_sensor()
depth_scale = depth_sensor.get_depth_scale()

# Create a skeleton tracker object
skeleton_tracker = rs.skeleton_tracker()

try:
    while True:
        # Wait for a coherent pair of frames: depth and color
        frames = pipeline.wait_for_frames()
        depth_frame = frames.get_depth_frame()
        color_frame = frames.get_color_frame()
        if not depth_frame or not color_frame:
            continue

        # Convert images to numpy arrays
        depth_image = np.asanyarray(depth_frame.get_data())
        color_image = np.asanyarray(color_frame.get_data())

        # Process the depth image to get the skeleton joints
        skeleton = skeleton_tracker.process(depth_frame)

        # Draw the skeleton joints on the color image
        for joint in skeleton.get_joints():
            if joint.position.z > 0:
                x, y = rs.rs2_project_point_to_pixel(color_frame.profile.as_video_stream_profile().intrinsics, [joint.position.x, joint.position.y, joint.position.z])
                cv2.circle(color_image, (int(x), int(y)), 5, (0, 255, 0), -1)

        # Show the images
        cv2.imshow('Color Image', color_image)
        cv2.imshow('Depth Image', depth_image)

        # Exit on ESC
        if cv2.waitKey(1) == 27:
            break

finally:
    # Stop streaming
    pipeline.stop()

请注意，这只是一个示例代码，您需要根据自己的实际情况进行修改和调整。