nerfbaselines

class nerfbaselines.CameraModel(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)

Bases: Enum

FULL_OPENCV = 3

OPENCV = 1

OPENCV_FISHEYE = 2

PINHOLE = 0

class nerfbaselines.Cameras(poses: numpy.ndarray, normalized_intrinsics: numpy.ndarray, camera_types: numpy.ndarray, distortion_parameters: numpy.ndarray, image_sizes: numpy.ndarray | None, nears_fars: numpy.ndarray | None, metadata: numpy.ndarray | None = None)

Bases: object

camera_types: ndarray

classmethod cat(values: Sequence[Cameras]) → Cameras

clone() → Cameras

distortion_parameters: ndarray

get_rays(xy: ~numpy.ndarray, xnp=<module 'numpy' from '/opt/hostedtoolcache/Python/3.12.6/x64/lib/python3.12/site-packages/numpy/__init__.py'>) → Tuple[ndarray, ndarray]

image_sizes: ndarray | None

item()

metadata: ndarray | None = None

nears_fars: ndarray | None

normalized_intrinsics: ndarray

poses: ndarray

project(xyz: ~numpy.ndarray, xnp=<module 'numpy' from '/opt/hostedtoolcache/Python/3.12.6/x64/lib/python3.12/site-packages/numpy/__init__.py'>) → ndarray

unproject(xy: ~numpy.ndarray, xnp=<module 'numpy' from '/opt/hostedtoolcache/Python/3.12.6/x64/lib/python3.12/site-packages/numpy/__init__.py'>) → Tuple[ndarray, ndarray]

with_image_sizes(image_sizes: ndarray) → Cameras

with_metadata(metadata: ndarray) → Cameras

class nerfbaselines.CurrentProgress(i: int, total: int, image_i: int, image_total: int)

Bases: object

i: int

image_i: int

image_total: int

total: int

class nerfbaselines.Indices(steps)

Bases: object

classmethod every_iters(iters: int, zero: bool = False)

class nerfbaselines.Method(*args, **kwargs)

Bases: Protocol

abstract get_info() → MethodInfo

Get method defaults for the trainer.

Returns:

Method info.

classmethod install()

Install the method.

abstract render(cameras: Cameras, progress_callback: Callable[[CurrentProgress], None] | None = None) → Iterable[Dict]

Render images.

Parameters:

• cameras – Cameras.

• progress_callback – Callback for progress.

abstract save(path: Path)

Save model.

Parameters:

path – Path to save.

abstract setup_train(train_dataset: Dataset, *, num_iterations: int | None = None, config_overrides: Dict[str, Any] | None = None)

Setup training data, model, optimizer, etc.

Parameters:

• train_dataset – Training dataset.

• num_iterations – Optional number of iterations to train.

• config_overrides – Optional set of config overrides.

abstract train_iteration(step: int)

Train one iteration.

Parameters:

step – Current step.

class nerfbaselines.MethodInfo(loaded_step: Optional[int] = None, num_iterations: Optional[int] = None, batch_size: Optional[int] = None, eval_batch_size: Optional[int] = None, required_features: FrozenSet[Literal['color', 'points3D_xyz', 'points3D_rgb']] = <factory>, supported_camera_models: FrozenSet = <factory>)

Bases: object

batch_size: int | None = None

eval_batch_size: int | None = None

loaded_step: int | None = None

num_iterations: int | None = None

required_features: FrozenSet[Literal['color', 'points3D_xyz', 'points3D_rgb']]

supported_camera_models: FrozenSet

class nerfbaselines.RayMethod(batch_size, seed: int = 42, config_overrides: ~typing.Dict[str, ~typing.Any] | None = None, xnp=<module 'numpy' from '/opt/hostedtoolcache/Python/3.12.6/x64/lib/python3.12/site-packages/numpy/__init__.py'>)

Bases: Method

render(cameras: Cameras, progress_callback: Callable[[CurrentProgress], None] | None = None) → Iterable[Dict]

Render images.

Parameters:

• cameras – Cameras.

• progress_callback – Callback for progress.

abstract render_rays(origins: ndarray, directions: ndarray, nears_fars: ndarray | None) → Dict

Render rays.

Parameters:

• origins – Ray origins.

• directions – Ray directions.

• nears_fars – Near and far planes.

setup_train(train_dataset: Dataset, *, num_iterations: int | None = None, config_overrides: Dict[str, Any] | None = None)

Setup training data, model, optimizer, etc.

Parameters:

• train_dataset – Training dataset.

• num_iterations – Optional number of iterations to train.

• config_overrides – Optional set of config overrides.

train_iteration(step: int)

Train one iteration.

Parameters:

step – Current step.

abstract train_iteration_rays(step: int, origins: ndarray, directions: ndarray, nears_fars: ndarray | None, colors: ndarray)

Train one iteration.

Parameters:

• step – Current step.

• origins – Ray origins.

• directions – Ray directions.

• nears_fars – Near and far planes.

• colors – Colors.