Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Add point reduction parameter #19

Merged
merged 1 commit into from
Jul 6, 2023
Merged

Add point reduction parameter #19

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
24 changes: 16 additions & 8 deletions chamferdist/chamfer.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -27,7 +27,8 @@ def forward(
target_cloud: torch.Tensor,
bidirectional: Optional[bool] = False,
reverse: Optional[bool] = False,
reduction: Optional[str] = "mean",
batch_reduction: Optional[str] = "mean",
point_reduction: Optional[str] = "sum",
):

if not isinstance(source_cloud, torch.Tensor):
Expand Down Expand Up @@ -71,8 +72,10 @@ def forward(
"Both bidirectional and reverse set to True. "
"bidirectional behavior takes precedence."
)
if reduction != "sum" and reduction != "mean" and reduction != None:
raise ValueError('Reduction must either be "sum" or "mean" or None.')
if point_reduction != "sum" and point_reduction != "mean" and point_reduction != None:
raise ValueError('Point reduction must either be "sum" or "mean" or None.')
if batch_reduction != "sum" and batch_reduction != "mean" and batch_reduction != None:
raise ValueError('Batch reduction must either be "sum" or "mean" or None.')

source_nn = knn_points(
source_cloud,
Expand All @@ -99,15 +102,20 @@ def forward(
# Backward Chamfer distance (batchsize_source, lengths_source)
chamfer_backward = target_nn.dists[..., 0]

chamfer_forward = chamfer_forward.sum(1) # (batchsize_source,)
if reverse or bidirectional:
chamfer_backward = chamfer_backward.sum(1) # (batchsize_target,)
if point_reduction == "sum":
chamfer_forward = chamfer_forward.sum(1) # (batchsize_source,)
if reverse or bidirectional:
chamfer_backward = chamfer_backward.sum(1) # (batchsize_target,)
elif point_reduction == "mean":
chamfer_forward = chamfer_forward.mean(1) # (batchsize_source,)
if reverse or bidirectional:
chamfer_backward = chamfer_backward.mean(1) # (batchsize_target,)

if reduction == "sum":
if batch_reduction == "sum":
chamfer_forward = chamfer_forward.sum() # (1,)
if reverse or bidirectional:
chamfer_backward = chamfer_backward.sum() # (1,)
elif reduction == "mean":
elif batch_reduction == "mean":
chamfer_forward = chamfer_forward.mean() # (1,)
if reverse or bidirectional:
chamfer_backward = chamfer_backward.mean() # (1,)
Expand Down