tink/nerfstudio
4
0
Fork 0
mirror of https://github.com/nerfstudio-project/nerfstudio.git synced 2026-11-11 10:34:29 +08:00
Code

Metadata for cameras (#1623)

Browse Source 
Adding metadata field to cameras explicitly, will be broadcast to rays generated
This commit is contained in:
Jake Austin 2023-04-14 20:56:25 -07:00 committed by GitHub
parent a9eea19880
commit db03d5792e
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
1 changed files with 18 additions and 6 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

24
nerfstudio/cameras/cameras.py
View File

@ -62,11 +62,7 @@ CAMERA_MODEL_TO_TYPE = {
class Cameras(TensorDataclass):
"""Dataparser outputs for the image dataset and the ray generator.
Note: currently only supports cameras with the same principal points and types. The reason we type
the focal lengths, principal points, and image sizes as tensors is to allow for batched cameras
down the line in cases where your batches of camera data don't come from the same cameras.
If a single value is provided, it is broadcasted to all cameras.
If a single value is provided, it is broadcasted to all cameras.
Args:
camera_to_worlds: Camera to world matrices. Tensor of per-image c2w matrices, in [R | t] format
@ -79,6 +75,8 @@ class Cameras(TensorDataclass):
distortion_params: OpenCV 6 radial distortion coefficients
camera_type: Type of camera model. This will be an int corresponding to the CameraType enum.
times: Timestamps for each camera
metadata: Additional metadata or data needed for interpolation, will mimic shape of the cameras
and will be broadcasted to the rays generated from any derivative RaySamples we create with this
"""
camera_to_worlds: TensorType["num_cameras":..., 3, 4]
@ -91,6 +89,7 @@ class Cameras(TensorDataclass):
distortion_params: Optional[TensorType["num_cameras":..., 6]]
camera_type: TensorType["num_cameras":..., 1]
times: Optional[TensorType["num_cameras", 1]]
metadata: Optional[Dict]
def __init__(
self,
@ -111,6 +110,7 @@ class Cameras(TensorDataclass):
]
] = CameraType.PERSPECTIVE,
times: Optional[TensorType["num_cameras"]] = None,
metadata: Optional[Dict] = None,
) -> None:
"""Initializes the Cameras object.
@ -146,6 +146,8 @@ class Cameras(TensorDataclass):
self.camera_type = self._init_get_camera_type(camera_type)
self.times = self._init_get_times(times)
self.metadata = metadata
self.__post_init__() # This will do the dataclass post_init and broadcast all the tensors
self._use_nerfacc = strtobool(os.environ.get("INTERSECT_WITH_NERFACC", "TRUE"))
@ -716,13 +718,23 @@ class Cameras(TensorDataclass):
times = self.times[camera_indices, 0] if self.times is not None else None
metadata = (
self._apply_fn_to_dict(self.metadata, lambda x: x[true_indices]) if self.metadata is not None else None
)
if metadata is not None:
metadata["directions_norm"] = directions_norm[0].detach()
else:
metadata = {"directions_norm": directions_norm[0].detach()}
times = self.times[camera_indices, 0] if self.times is not None else None
return RayBundle(
origins=origins,
directions=directions,
pixel_area=pixel_area,
camera_indices=camera_indices,
times=times,
metadata={"directions_norm": directions_norm[0].detach()},
metadata=metadata,
)
def to_json(