mirror of
https://github.com/nerfstudio-project/nerfstudio.git
synced 2026-11-13 19:33:46 +08:00
Ethan Weber
676beebb14
* some initial cuda code as I learn. using git to save progress. * first cuda kernel for ray sampling that mostly works * cleaning up code. working on lr. structs for scene bounds aabb * added scene bounds collider code * updated setup * setup * setup * black * including some files * exporting env variable * new file * git workflows * github actions * github actions * github actions * removing env var
64 lines
2.2 KiB
Python
64 lines
2.2 KiB
Python
"""
|
|
For loading the blender dataset format.
|
|
"""
|
|
|
|
from typing import Optional, Union
|
|
|
|
from omegaconf import ListConfig
|
|
|
|
from mattport.nerf.dataset.format.blender import load_blender_data
|
|
from mattport.nerf.dataset.format.friends import load_friends_data
|
|
from mattport.nerf.dataset.structs import DatasetInputs
|
|
from mattport.structures.colors import get_color
|
|
from mattport.utils.io import get_absolute_path
|
|
|
|
|
|
def get_dataset_inputs(
|
|
data_directory: str,
|
|
dataset_format: str,
|
|
split: str,
|
|
downscale_factor: int = 1,
|
|
alpha_color: Optional[Union[str, list, ListConfig]] = None,
|
|
load_dataset_inputs_from_cache: bool = False,
|
|
) -> DatasetInputs:
|
|
"""Returns the dataset inputs, which will be used with an ImageDataset and RayGenerator.
|
|
# TODO: implement the `test` split, which will have depths and normals, etc.
|
|
|
|
Args:
|
|
data_directory (str): Location of data
|
|
dataset_format (str): Name of dataset type
|
|
downscale_factor (int, optional): How much to downscale images. Defaults to 1.0.
|
|
alpha_color (str, list, optional): Sets transparent regions to specified color, otherwise black.
|
|
load_from_cache (bool)
|
|
Returns:
|
|
DatasetInputs: The inputs needed for generating rays.
|
|
"""
|
|
|
|
if load_dataset_inputs_from_cache:
|
|
print("Loading from cache.")
|
|
return None
|
|
|
|
if alpha_color is not None:
|
|
alpha_color = get_color(alpha_color)
|
|
|
|
if dataset_format == "blender":
|
|
dataset_inputs = load_blender_data(
|
|
get_absolute_path(data_directory),
|
|
downscale_factor=downscale_factor,
|
|
split=split,
|
|
alpha_color=alpha_color,
|
|
)
|
|
elif dataset_format == "friends":
|
|
# TODO(ethan): change this hack, and do proper splits for the friends dataset
|
|
# currently we assume that there is only the training set of images
|
|
dataset_inputs = load_friends_data(
|
|
get_absolute_path(data_directory),
|
|
downscale_factor=downscale_factor,
|
|
split="train",
|
|
include_point_cloud=False,
|
|
)
|
|
else:
|
|
raise NotImplementedError(f"{dataset_format} is not a valid dataset type")
|
|
|
|
return dataset_inputs
|