1. 深度圖Image和點(diǎn)云

關(guān)鍵代碼：

(1) 深度圖轉(zhuǎn)點(diǎn)云

pcd = o3d.t.geometry.PointCloud.create_from_depth_image(depth=depth,
                                                        intrinsics=intrinsic,
                                                        depth_scale=5000.0,
                                                        depth_max=10.0)

需要知道相機(jī)內(nèi)外參數(shù)。?

(2) 點(diǎn)云轉(zhuǎn)深度圖

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

?需要知道相機(jī)內(nèi)外參數(shù)。?

point_cloud_to_depth.py

import open3d as o3d
import numpy as np
import matplotlib.pyplot as plt

if __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. 相機(jī)內(nèi)參
    extrinsics (open3d.core.Tensor, optional): Extrinsic parameters of the camera. 相機(jī)外參
    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和點(diǎn)云

深度圖-》RGBD-》點(diǎn)云

需要知道相機(jī)內(nèi)外參數(shù)。

point_cloud_to_rgbd.py

import open3d as o3d
import numpy as np
import matplotlib.pyplot as plt

if __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()

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