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Monte-Carlo rasterisation; arbitrary dimensionality of AlphaCompositor blending

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Summary:
Fixes required for MC rasterisation to work.
1) Wrong number of channels for background was used (derived from points dimensions, not features dimensions;
2) split of the results on the wrong dimension was done;
3) CORE CHANGE: blending in alpha compositor was assuming RGBA input.

Reviewed By: davnov134

Differential Revision: D34933673

fbshipit-source-id: a5cc9f201ea21e114639ab9e291a10888d495206
This commit is contained in:
Roman Shapovalov 2022-03-17 05:12:39 -07:00 committed by Facebook GitHub Bot
parent e64f25c255
commit 0e377c6850
1 changed files with 3 additions and 4 deletions
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7
pytorch3d/renderer/points/compositor.py
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@ -92,9 +92,8 @@ def _add_background_color_to_images(pix_idxs, images, background_color):
background_color = background_color.to(images)
# add alpha channel
if background_color.shape[0] == 3 and images.shape[1] == 4:
# special case to allow giving RGB background for RGBA
# add alpha channel if needed
if background_color.shape[0] + 1 == images.shape[1]:
alpha = images.new_ones(1)
background_color = torch.cat([background_color, alpha])
@ -107,7 +106,7 @@ def _add_background_color_to_images(pix_idxs, images, background_color):
num_background_pixels = background_mask.sum()
# permute so that features are the last dimension for masked_scatter to work
masked_images = images.permute(0, 2, 3, 1)[..., :4].masked_scatter(
masked_images = images.permute(0, 2, 3, 1).masked_scatter(
background_mask[..., None],
background_color[None, :].expand(num_background_pixels, -1),
)