1. 深度图Image和点云

关键代码：

(1) 深度图转点云

pcd = o3D.t.geometry.PointCloud.create_from_depth_image(depth=depth,intrinsics=intrinsic,depth_scale=5000.0,depth_max=10.0)

需要知道相机内外参数。 

(2) 点云转深度图

depth_reproj = pcd.project_to_depth_image(width=640,              height=480,              intrinsics=intrinsic,              depth_scale=5000.0,              depth_max=10.0)

 需要知道相机内外参数。 

point_cloud_to_depth.py

import open3d as o3dimport numpy as npimport matplotlib.pyplot as pltif __name__ == '__main__':    # 1. read    tum_data = o3d.data.SampleTUMRGBDImage()    depth = o3d.t.io.read_image(tum_data.depth_path)  # Image    # 2. depth Image生成PointCloud    """    create PointCloud from a depth image and a camera model.        depth (open3d.t.geometry.Image): The input depth image should be a uint16_t image.    intrinsics (open3d.core.Tensor): Intrinsic parameters of the camera. 相机内参    extrinsics (open3d.core.Tensor, optional): Extrinsic parameters of the camera. 相机外参    depth_scale (float, optional, default=1000.0): The depth is scaled by 1 / depth_scale.    depth_max (float, optional, default=3.0): Truncated at depth_max distance.    ...params.        """    intrinsic = o3d.core.Tensor([[535.4, 0, 320.1], [0, 539.2, 247.6],     [0, 0, 1]])    pcd = o3d.t.geometry.PointCloud.create_from_depth_image(depth=depth,    intrinsics=intrinsic,    depth_scale=5000.0,    depth_max=10.0)    o3d.visualization.draw([pcd])    # 3. PointCloud生成depth Image    depth_reproj = pcd.project_to_depth_image(width=640,                  height=480,                  intrinsics=intrinsic,                  depth_scale=5000.0,                  depth_max=10.0)    fig, axs = plt.subplots(1, 2)    axs[0].imshow(np.asarray(depth.to_legacy()))  # 原始depth    axs[1].imshow(np.asarray(depth_reproj.to_legacy()))  # depth->ointCloud->depth    plt.show()

2. RGBD和点云

深度图-》RGBD-》点云

需要知道相机内外参数。

point_cloud_to_rgbd.py

import open3d as o3dimport numpy as npimport matplotlib.pyplot as pltif __name__ == '__main__':        # 1. read depth and color image    device = o3d.core.Device('CPU:0')    tum_data = o3d.data.SampleTUMRGBDImage()    depth = o3d.t.io.read_image(tum_data.depth_path).to(device)    color = o3d.t.io.read_image(tum_data.color_path).to(device)    # 2. depth and color 生成rgbd    rgbd = o3d.t.geometry.RGBDImage(color, depth)        # 3. rgbd生成pcd    intrinsic = o3d.core.Tensor([[535.4, 0, 320.1], [0, 539.2, 247.6], [0, 0, 1]])    pcd = o3d.t.geometry.PointCloud.create_from_rgbd_image(rgbd,   intrinsic,   depth_scale=5000.0,   depth_max=10.0)    o3d.visualization.draw([pcd])        # 4. pcd生成rgbd    rgbd_reproj = pcd.project_to_rgbd_image(640,                480,                intrinsic,                depth_scale=5000.0,                depth_max=10.0)    # 5. view    fig, axs = plt.subplots(1, 2)    axs[0].imshow(np.asarray(rgbd_reproj.color.to_legacy()))  # 原始rgbd    axs[1].imshow(np.asarray(rgbd_reproj.depth.to_legacy()))  # rgbd->pcd->rgbd    plt.show()

来源地址：https://blog.csdn.net/jizhidexiaoming/article/details/130578591