Function sample_new_points_using_pointersect

pointersect/inference/infer.py:1686–1775

Sample new points from the current point cloud. Args: num_points: number of points to sample method: method to generate querying rays model: width_px: height_px: fov: Returns: new point cloud: (b, num_poi

(
        point_cloud: PointCloud,
        num_points: int,
        model_filename: str,
        method: str = 'uniform_camera',
        model: SimplePointersect = None,
        k: int = 40,
        width_px: int = 10,
        height_px: int = 10,
        fov: float = 60.,  # degree
        max_ray_chunk_size: int = 10000,
)

def sample_new_points_using_pointersect(
        point_cloud: PointCloud,
        num_points: int,
        model_filename: str,
        method: str = 'uniform_camera',
        model: SimplePointersect = None,
        k: int = 40,
        width_px: int = 10,
        height_px: int = 10,
        fov: float = 60.,  # degree
        max_ray_chunk_size: int = 10000,
) -> PointCloud:
    """
    Sample new points from the current point cloud.

    Args:
        num_points:
            number of points to sample
        method:
            method to generate querying rays
        model:
        width_px:
        height_px:
        fov:

    Returns:
        new point cloud:  (b, num_points)
    """

    if method == 'uniform_camera':
        # adjust resolution settings
        n_imgs = max(1, num_points // (width_px * height_px))
        n_pixels_per_img = num_points / n_imgs
        width_px = max(2, math.floor(n_pixels_per_img / (width_px * height_px) * width_px))
        width_px = max(2, width_px - (width_px % 2))
        height_px = max(2, math.floor(n_pixels_per_img / width_px))
        height_px = max(2, height_px - (height_px % 2))

        # get mesh scale and center
        if not point_cloud.included_point_at_inf:
            xyz_max = point_cloud.xyz_w.max(dim=-2)[0]  # (b, 3)
            xyz_min = point_cloud.xyz_w.min(dim=-2)[0]  # (b, 3)
        else:
            xyz_max = point_cloud.xyz_w[:, 1:].max(dim=-2)[0]  # (b, 3)
            xyz_min = point_cloud.xyz_w[:, 1:].min(dim=-2)[0]  # (b, 3)
        cs = (xyz_max.mean(dim=0) + xyz_min.mean(dim=0)) / 2  # (3,)
        s = (xyz_max - xyz_min).max().detach().cpu().item() / 2

        # create uniformly placed camera
        camera = CameraTrajectory(
            mode='random',
            n_imgs=n_imgs,
            total=1,
            params=dict(
                max_angle=180,
                min_r=2 * s,
                max_r=2 * s + 1.e-9,
                origin_w=cs.detach().cpu().numpy().tolist(),