Skip to content

Assign image tensors to data_device immediately on creation. #667

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

Open
wants to merge 1 commit into
base: main
Choose a base branch
from
Open

Assign image tensors to data_device immediately on creation. #667

Show file tree
Hide file tree
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
2 changes: 1 addition & 1 deletion utils/camera_utils.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -38,7 +38,7 @@ def loadCam(args, id, cam_info, resolution_scale):
scale = float(global_down) * float(resolution_scale)
resolution = (int(orig_w / scale), int(orig_h / scale))

resized_image_rgb = PILtoTorch(cam_info.image, resolution)
resized_image_rgb = PILtoTorch(cam_info.image, resolution, args.data_device)

gt_image = resized_image_rgb[:3, ...]
loaded_mask = None
Expand Down
4 changes: 2 additions & 2 deletions utils/general_utils.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -18,9 +18,9 @@
def inverse_sigmoid(x):
return torch.log(x/(1-x))

def PILtoTorch(pil_image, resolution):
def PILtoTorch(pil_image, resolution, data_device="cuda"):
resized_image_PIL = pil_image.resize(resolution)
resized_image = torch.from_numpy(np.array(resized_image_PIL)) / 255.0
resized_image = torch.from_numpy(np.array(resized_image_PIL)).to(data_device) / 255.0
if len(resized_image.shape) == 3:
return resized_image.permute(2, 0, 1)
else:
Expand Down