423A35C7/pytorch3d
1
0
Fork 0
mirror of https://github.com/facebookresearch/pytorch3d.git synced 2025-12-25 16:50:36 +08:00
Code Issues Packages Projects Releases Wiki Activity

doc rgbd point cloud

Browse Source 
Summary: docstring and shape fix

Reviewed By: shapovalov

Differential Revision: D42609661

fbshipit-source-id: fd50234872ad61b5452821eeb89d51344f70c957
This commit is contained in:
Jeremy Reizenstein
2023-01-24 15:26:52 -08:00
committed by Facebook GitHub Bot
parent d561f1913e
commit a12612a48f
2 changed files with 88 additions and 3 deletions
Download Patch File Download Diff File Expand all files Collapse all files

27
pytorch3d/implicitron/tools/point_cloud_utils.py
View File

@@ -27,13 +27,33 @@ def get_rgbd_point_cloud(
mask: Optional[torch.Tensor] = None,
mask_thr: float = 0.5,
mask_points: bool = True,
euclidean: bool = False,
) -> Pointclouds:
"""
Given a batch of images, depths, masks and cameras, generate a colored
point cloud by unprojecting depth maps to the and coloring with the source
Given a batch of images, depths, masks and cameras, generate a single colored
point cloud by unprojecting depth maps and coloring with the source
pixel colors.
Arguments:
camera: Batch of N cameras
image_rgb: Batch of N images of shape (N, C, H, W).
For RGB images C=3.
depth_map: Batch of N depth maps of shape (N, 1, H', W').
Only positive values here are used to generate points.
If euclidean=False (default) this contains perpendicular distances
from each point to the camera plane (z-values).
If euclidean=True, this contains distances from each point to
the camera center.
mask: If provided, batch of N masks of the same shape as depth_map.
If provided, values in depth_map are ignored if the corresponding
element of mask is smaller than mask_thr.
mask_thr: used in interpreting mask
euclidean: used in interpreting depth_map.
Returns:
Pointclouds object containing one point cloud.
"""
imh, imw = image_rgb.shape[2:]
imh, imw = depth_map.shape[2:]
# convert the depth maps to point clouds using the grid ray sampler
pts_3d = ray_bundle_to_ray_points(
@@ -43,6 +63,7 @@ def get_rgbd_point_cloud(
n_pts_per_ray=1,
min_depth=1.0,
max_depth=1.0,
unit_directions=euclidean,
)(camera)._replace(lengths=depth_map[:, 0, ..., None])
)