tfg.geometry.representation.ray.sample_1d

Sample points on a ray using a sampling strategy (ray wrapper for sampling functions).

tfg.geometry.representation.ray.sample_1d(
    ray_org: TensorLike,
    ray_dir: TensorLike,
    near: Union[float, TensorLike],
    far: Union[float, TensorLike],
    n_samples: int,
    strategy: str = &#x27;stratified',
    name: str = &#x27;sample_1d'
) -> Tuple[tf.Tensor, tf.Tensor]

Args
`ray_org`	A tensor of shape `[A1, ..., An, 3]`, where the last dimension represents the 3D position of the ray origin.
`ray_dir`	A tensor of shape `[A1, ..., An, 3]`, where the last dimension represents the 3D direction of the ray.
`near`	The smallest distance from the ray origin that a sample can have. It can be a scalar (float) or a tensor of shape `[A1, ..., An]`.
`far`	The largest distance from the ray origin that a sample can have. It can be a scalar (float) or a tensor of shape `[A1, ..., An]`.
`n_samples`	A number M to sample on the ray.
`strategy`	The sampling strategy.
`name`	A name for this op that defaults to "sample_1d".

Returns
A tensor of shape `[A1, ..., An, M, 3]` indicating the M points on the ray and a tensor of shape `[A1, ..., An, M]` for the Z values on the points.

tfg.geometry.representation.ray.sample_1d

Args

Returns