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Code

Local camera coordinate directions

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This commit is contained in:
Kevin Chen 2022-11-08 19:35:56 +00:00
parent a32b254254
commit b3efcb9bfd
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3 changed files with 16 additions and 23 deletions
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23
nerfstudio/cameras/cameras.py
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@ -46,7 +46,7 @@ CAMERA_MODEL_TO_TYPE = {
"RADIAL": CameraType.PERSPECTIVE,
"OPENCV": CameraType.PERSPECTIVE,
"OPENCV_FISHEYE": CameraType.FISHEYE,
"EQUIRECTANGULAR": CameraType.EQUIRECTANGULAR
"EQUIRECTANGULAR": CameraType.EQUIRECTANGULAR,
}
@ -315,20 +315,13 @@ class Cameras:
dim=-1,
)
elif self.camera_type[0] == CameraType.EQUIRECTANGULAR.value:
coord = torch.stack([x,y ], -1)
coord_x_offset = torch.stack([x+1, y], -1)
coord_y_offset = torch.stack([x, y+1], -1)
coord_stack = torch.stack([coord, coord_x_offset, coord_y_offset], dim=0)
phi = coord_stack[..., 1] / self.image_height[camera_indices] * torch.pi
theta = coord_stack[..., 0] / self.image_width[camera_indices] * 2 * torch.pi
# u goes from -w/2 to w/2
# v goes from -h/2 to h/2
phi = torch.pi * (0.5 - coord_stack[..., 1] / self.image_height[camera_indices])
theta = -2 * torch.pi * coord_stack[..., 0] / self.image_width[camera_indices]
# use spherical in local camera coordinates (+y up, x=0 and z<0 is theta=0)
directions_stack = torch.stack(
[
torch.cos(theta) * torch.sin(phi),
torch.sin(theta) * torch.sin(phi),
torch.cos(phi)
],
[-torch.sin(theta) * torch.sin(phi), torch.cos(phi), -torch.cos(theta) * torch.sin(phi)],
dim=-1,
)
else:
@ -354,7 +347,7 @@ class Cameras:
if not isinstance(camera_indices, torch.Tensor):
ray_bundle_camera_indices = torch.Tensor([camera_indices]).broadcast_to(pixel_area.shape).to(self.device)
else:
ray_bundle_camera_indices = camera_indices.view(pixel_area.shape)
ray_bundle_camera_indices = camera_indices.view(pixel_area.shape)
return RayBundle(
origins=origins,

4
nerfstudio/data/datamanagers.py
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@ -38,7 +38,7 @@ from nerfstudio.data.dataparsers.instant_ngp_dataparser import (
)
from nerfstudio.data.dataparsers.nerfstudio_dataparser import NerfstudioDataParserConfig
from nerfstudio.data.dataparsers.record3d_dataparser import Record3DDataParserConfig
from nerfstudio.data.pixel_samplers import PixelSampler, EquirectangularSampler
from nerfstudio.data.pixel_samplers import EquirectangularSampler, PixelSampler
from nerfstudio.data.utils.dataloaders import (
CacheDataloader,
FixedIndicesEvalDataloader,
@ -302,7 +302,7 @@ class VanillaDataManager(DataManager): # pylint: disable=abstract-method
pin_memory=True,
)
self.iter_train_image_dataloader = iter(self.train_image_dataloader)
self.train_pixel_sampler = EquirectangularSampler(self.config.train_num_rays_per_batch)
self.train_pixel_sampler = PixelSampler(self.config.train_num_rays_per_batch)
self.train_camera_optimizer = self.config.camera_optimizer.setup(
num_cameras=self.train_dataset.dataparser_outputs.cameras.size, device=self.device
)

12
scripts/process_data.py
View File

@ -605,12 +605,12 @@ def opensfm_to_json(reconstruction_path: Path, output_dir: Path, camera_model: C
# For now just assume it's all the same camera
cam = cams[list(cams.keys())[0]]
out = {
"fl_x": float(cam["focal_x"]) * max(cam["height"], cam["width"]) if "focal_x" in cam else 1.0,
"fl_y": float(cam["focal_y"]) * max(cam["height"], cam["width"]) if "focal_y" in cam else 1.0,
"cx": cam["width"] / 2.0 + float(cam["c_x"]) * cam["width"] if "c_x" in cam else 1.0,
"cy": cam["height"] / 2.0 + float(cam["c_y"]) * cam["height"] if "c_y" in cam else 1.0,
"w": cam["width"],
"h": cam["height"],
"fl_x": float(cam["focal_x"]) if "focal_x" in cam else 1.0,
"fl_y": float(cam["focal_y"]) if "focal_y" in cam else 1.0,
"cx": float(cam["c_x"]) if "c_x" in cam else 0.5 * cam["width"],
"cy": float(cam["c_y"]) if "c_y" in cam else 0.5 * cam["height"],
"w": int(cam["width"]),
"h": int(cam["height"]),
"camera_model": camera_model.value,
}
if camera_model == CameraModel.OPENCV: