포인트 클라우드 처리를 위한 open3d 사용법 정리

def show_open3d_pcd(pcd, show_origin=True, origin_size=3, show_grid=True):
    cloud = o3d.geometry.PointCloud()
    v3d = o3d.utility.Vector3dVector
    
    if isinstance(pcd, type(cloud)):
        pass
    elif isinstance(pcd, np.ndarray):
        cloud.points = v3d(pcd)
        
    coord = o3d.geometry.TriangleMesh().create_coordinate_frame(size=origin_size, origin=np.array([0.0, 0.0, 0.0]))
    
    # set front, lookat, up, zoom to change initial view
    o3d.visualization.draw_geometries([cloud, coord])

import open3d as o3d
import numpy as np

def get_grid_lineset(h_min_val, h_max_val, w_min_val, w_max_val, ignore_axis, grid_length, color):
    
    num_h_grid = int(np.round((h_max_val - h_min_val) // grid_length, -1))
    num_w_grid = int(np.round((w_max_val - w_min_val) // grid_length, -1))
    
    num_h_grid_mid = num_h_grid // 2
    num_w_grid_mid = num_w_grid // 2
    
    grid_vertexes_order = np.zeros((num_h_grid, num_w_grid)).astype(np.int16)
    grid_vertexes = []
    vertex_order_index = 0
    
    for h in range(num_h_grid):
        for w in range(num_w_grid):
            grid_vertexes_order[h][w] = vertex_order_index
            if ignore_axis == 0:
                grid_vertexes.append([0, grid_length*w + w_min_val, grid_length*h + h_min_val])
            elif ignore_axis == 1:
                grid_vertexes.append([grid_length*h + h_min_val, 0, grid_length*w + w_min_val])
            elif ignore_axis == 2:
                grid_vertexes.append([grid_length*w + w_min_val, grid_length*h + h_min_val, 0])
            else:
                pass                
            vertex_order_index += 1       
            
    next_h = [-1, 0, 0, 1]
    next_w = [0, -1, 1, 0]
    grid_lines = []
    for h in range(num_h_grid):
        for w in range(num_w_grid):
            here_h = h
            here_w = w
            for i in range(4):
                there_h = h + next_h[i]
                there_w = w +  next_w[i]            
                if (0 <= there_h and there_h < num_h_grid) and (0 <= there_w and there_w < num_w_grid):
                    grid_lines.append([grid_vertexes_order[here_h][here_w], grid_vertexes_order[there_h][there_w]])
                    
                    
    colors = [color for i in range(len(grid_lines))]
    line_set = o3d.geometry.LineSet(
        points=o3d.utility.Vector3dVector(grid_vertexes),
        lines=o3d.utility.Vector2iVector(grid_lines),
    )
    line_set.colors = o3d.utility.Vector3dVector(colors)
    
    return line_set   

def show_open3d_pcd(raw, show_origin=True, origin_size=3, 
                    show_grid=True, grid_len=1, 
                    voxel_size=0, 
                    range_min_xyz=(-80, -80, 0), range_max_xyz=(80, 80, 80)):
    '''
    - raw : numpy 2d array (size : (n, 3)) or o3d.geometry.PointCloud
    - show_origin : show origin XYZ coordinate. (X=red, Y=green, Z=Blue)
    - origin_size : size of origin coordinate.
    - show_grid : if true, show grid in xy, yz, zx plane with 'grid_len' length (default : gray line) and 5 times of 'grid_len' (default : red line)
    - voxel_size : voxel size to downsampling
    - range_min_xyz : grid min range of xyz orientation
    - range_max_xyz : grid max range of xyz orientation

    '''
    pcd = o3d.geometry.PointCloud()    
    
    if isinstance(raw, type(pcd)):
        pass
    elif isinstance(raw, np.ndarray):
        pcd.points = o3d.utility.Vector3dVector(raw)        
    if voxel_size > 0:
        pcd = pcd.voxel_down_sample(voxel_size=voxel_size)
        
    pcd_point = np.array(pcd.points)
    inrange_inds = (pcd_point[:, 0] > range_min_xyz[0]) & \
                    (pcd_point[:, 1] > range_min_xyz[1]) & \
                    (pcd_point[:, 2] > range_min_xyz[2]) & \
                    (pcd_point[:, 0] < range_max_xyz[0]) & \
                    (pcd_point[:, 1] < range_max_xyz[1]) & \
                    (pcd_point[:, 2] < range_max_xyz[2])    
    
    pcd_point = pcd_point[inrange_inds]
    filtered_raw = pcd_point
    pcd.points = o3d.utility.Vector3dVector(filtered_raw)
        
    x_min_val, y_min_val, z_min_val = range_min_xyz
    x_max_val, y_max_val, z_max_val = range_max_xyz
    
    coord = o3d.geometry.TriangleMesh().create_coordinate_frame(size=origin_size, origin=np.array([0.0, 0.0, 0.0]))
    
    R, G, B = 0.8, 0.8, 0.8
    lineset_yz = get_grid_lineset(z_min_val, z_max_val, y_min_val, y_max_val, 0, grid_len, [R, G, B])
    lineset_zx = get_grid_lineset(x_min_val, x_max_val, z_min_val, z_max_val, 1, grid_len, [R, G, B])
    lineset_xy = get_grid_lineset(y_min_val, y_max_val, x_min_val, x_max_val, 2, grid_len, [R, G, B]) 
    
    R, G, B = 1, 0, 0
    lineset_yz_5 = get_grid_lineset(z_min_val, z_max_val, y_min_val, y_max_val, 0, grid_len*5, [R, G, B])
    lineset_zx_5 = get_grid_lineset(x_min_val, x_max_val, z_min_val, z_max_val, 1, grid_len*5, [R, G, B])
    lineset_xy_5 = get_grid_lineset(y_min_val, y_max_val, x_min_val, x_max_val, 2, grid_len*5, [R, G, B]) 
    
    # set front, lookat, up, zoom to change initial view
    o3d.visualization.draw_geometries([pcd, coord,
                                       lineset_yz_5, lineset_zx_5, lineset_xy_5,
                                       lineset_xy, lineset_yz, lineset_zx
                                      ])  

raw = np.fromfile("00000001.bin", dtype=np.float32).reshape((-1, 4))
raw = raw[:, :3]
show_open3d_pcd(pcd, origin_size=3, range_min_xyz=(-40, -40, -5), range_max_xyz=(40, 40, 5))

def show_point_cloud(points, color_axis, width_size=1500, height_size=800, coordinate_frame=True):
    '''
    points : (N, 3) size of ndarray
    color_axis : 0, 1, 2
    '''
    assert points.shape[1] == 3
    assert color_axis==0 or color_axis==1 or color_axis==2   
    
    
    # Create a scatter3d Plotly plot
    plotly_fig = go.Figure(data=[go.Scatter3d(
        x=points[:, 0],
        y=points[:, 1],
        z=points[:, 2],
        mode='markers',
        marker=dict(
            size=1,
            color=points[:, color_axis], # Set color based on Z-values
            colorscale='jet', # Choose a color scale
            colorbar=dict(title='value') # Add a color bar with a title
        )
    )])

    x_range = points[:, 0].max()*0.9 - points[:, 0].min()*0.9
    y_range = points[:, 1].max()*0.9 - points[:, 1].min()*0.9
    z_range = points[:, 2].max()*0.9 - points[:, 2].min()*0.9

    # Adjust the Z-axis scale
    plotly_fig.update_layout(
        scene=dict(
            aspectmode='manual',
            aspectratio=dict(x=x_range, y=y_range, z=z_range), # Here you can set the scale of the Z-axis     
        ),
        width=width_size, # Width of the figure in pixels
        height=height_size, # Height of the figure in pixels
        showlegend=False
    )
    
    if coordinate_frame:
        # Length of the axes
        axis_length = 1

        # Create lines for the axes
        lines = [
            go.Scatter3d(x=[0, axis_length], y=[0, 0], z=[0, 0], mode='lines', line=dict(color='red')),
            go.Scatter3d(x=[0, 0], y=[0, axis_length], z=[0, 0], mode='lines', line=dict(color='green')),
            go.Scatter3d(x=[0, 0], y=[0, 0], z=[0, axis_length], mode='lines', line=dict(color='blue'))
        ]

        # Create cones (arrows) for the axes
        cones = [
            go.Cone(x=[axis_length], y=[0], z=[0], u=[axis_length], v=[0], w=[0], sizemode='absolute', sizeref=0.1, anchor='tail', showscale=False),
            go.Cone(x=[0], y=[axis_length], z=[0], u=[0], v=[axis_length], w=[0], sizemode='absolute', sizeref=0.1, anchor='tail', showscale=False),
            go.Cone(x=[0], y=[0], z=[axis_length], u=[0], v=[0], w=[axis_length], sizemode='absolute', sizeref=0.1, anchor='tail', showscale=False)
        ]

        # Add lines and cones to the figure
        for line in lines:
            plotly_fig.add_trace(line)
        for cone in cones:
            plotly_fig.add_trace(cone)

    # Show the plot
    plotly_fig.show()

# Extract the points as a NumPy array
pcd_path = "./000000.pcd"
pcd = o3d.io.read_point_cloud(pcd_path)
points = np.asarray(pcd.points)
show_point_cloud(points, 2)