infer_dit result in V100

[arasika]

I ran the infer_dit.py script with the arguments -d DIT_CARLA and --best_vae, which generated many .npy files. When I attempted to visualize these .npy files, the resulting images were not as expected. It looks like BEV not occ. Could you help me understand what might have gone wrong or how I can improve the visualization?

` # 1.load 16 .npy files and get voxel size (16,128, 128, 8)===========
for file_name in npy_files:
file_path = os.path.join(folder_path, file_name)
data = np.fromfile(file_path, dtype=np.int8).reshape((128, 128, 8))
data_list.append(data)

voxels = np.stack(data_list, axis=0)

# save (16,128, 128) point with color to .ply ===========
x = torch.arange(voxels.shape[0])  # 16
y = torch.arange(voxels.shape[1])  # 128
z = torch.arange(voxels.shape[2])  # 128
xx, yy, zz = torch.meshgrid(x, y, z, indexing='ij')
voxel_color = voxels[...,0].flatten()
indices = np.where(voxel_color == 6)
voxel_color = np.delete(voxel_color, indices, axis=0)
colors = np.array([
    [1.0, 0.0, 0.0],    # 红色
    [0.0, 1.0, 0.0],    # 绿色
    [0.0, 0.0, 1.0],    # 蓝色
    [1.0, 1.0, 0.0],    # 黄色
    [1.0, 0.0, 1.0],    # 粉红色
    [0.0, 1.0, 1.0],    # 青色
    [0.5, 0.5, 0.5],    # 灰色
    [1.0, 0.5, 0.0],    # 橙色
    [0.5, 1.0, 0.0],    # 浅绿色
    [0.0, 0.5, 1.0]     # 浅蓝色
])
mapped_colors = colors[voxel_color % 10] 
points = np.vstack([xx.flatten(), yy.flatten(), zz.flatten()]).T 
points = np.delete(points, indices, axis=0)
point_cloud = o3d.geometry.PointCloud()
point_cloud.points = o3d.utility.Vector3dVector(points)
point_cloud.colors = o3d.utility.Vector3dVector(mapped_colors)
o3d.io.write_point_cloud(base_path+"ply/"+str(path_id)+".ply", point_cloud)`

[bian-hengwei]

Hi, you may try the following method for visualization:

def get_mesh_open3d(voxel_map, shape, ignore, color_map, voxel_size, ignores=None):
    x, y, z = np.meshgrid(np.arange(shape[0]), np.arange(shape[1]), np.arange(shape[2]))
    positions = np.stack([y, x, z], axis=-1).reshape(-1, 3)

    mask = voxel_map.reshape(-1) != ignore

    if ignores is not None:
        for val in ignores:
            mask &= voxel_map.reshape(-1) != val

    positions = positions[mask]
    colors = np.array([color_map[voxel_map.reshape(-1)[i]] for i in np.where(mask)[0]]) / 255.0

    pcd = o3d.geometry.PointCloud()
    pcd.points = o3d.utility.Vector3dVector(positions * voxel_size)
    pcd.colors = o3d.utility.Vector3dVector(colors[:, ::-1])  # RGB to BGR

    voxel_grid = o3d.geometry.VoxelGrid.create_from_point_cloud(pcd, voxel_size=voxel_size)

    mesh = o3d.geometry.TriangleMesh()
    voxels = voxel_grid.get_voxels()
    for voxel in voxels:
        cube = o3d.geometry.TriangleMesh.create_box(width=voxel_size, height=voxel_size, depth=voxel_size)
        cube.paint_uniform_color(voxel.color)
        cube.translate(voxel.grid_index * voxel_size)
        mesh += cube

    vertices = np.asarray(mesh.vertices)
    faces = np.asarray(mesh.triangles)
    colors = np.asarray(mesh.vertex_colors)

    trimesh_mesh = trimesh.Trimesh(vertices=vertices, faces=faces, vertex_colors=colors)
    return trimesh_mesh, pyrender.Mesh.from_trimesh(trimesh_mesh, smooth=False)

[arasika]

Thank you! I've successfully obtained the result.