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remove unused params + cubify note

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Summary:
This diff
* removes the unused compositing params
* adds a note describing cubify

Reviewed By: nikhilaravi

Differential Revision: D22426191

fbshipit-source-id: e8aa32040bb594e1dfd7d6d98e29264feefcec7c
This commit is contained in:
Georgia Gkioxari
2020-07-09 18:02:50 -07:00
committed by Facebook GitHub Bot
parent 38eadb75e2
commit 3d7dea58e1
3 changed files with 15 additions and 20 deletions
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11
pytorch3d/renderer/compositing.py
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@@ -14,11 +14,6 @@ from pytorch3d import _C
# This can be an image (C=3) or a set of features.
# Data class to store blending params with defaults
class CompositeParams(NamedTuple):
radius: float = 4.0 / 256.0
class _CompositeAlphaPoints(torch.autograd.Function):
"""
Composite features within a z-buffer using alpha compositing. Given a z-buffer
@@ -67,7 +62,7 @@ class _CompositeAlphaPoints(torch.autograd.Function):
return grad_features, grad_alphas, grad_points_idx, None
def alpha_composite(pointsidx, alphas, pt_clds, blend_params=None) -> torch.Tensor:
def alpha_composite(pointsidx, alphas, pt_clds) -> torch.Tensor:
"""
Composite features within a z-buffer using alpha compositing. Given a z-buffer
with corresponding features and weights, these values are accumulated according
@@ -147,7 +142,7 @@ class _CompositeNormWeightedSumPoints(torch.autograd.Function):
return grad_features, grad_alphas, grad_points_idx, None
def norm_weighted_sum(pointsidx, alphas, pt_clds, blend_params=None) -> torch.Tensor:
def norm_weighted_sum(pointsidx, alphas, pt_clds) -> torch.Tensor:
"""
Composite features within a z-buffer using normalized weighted sum. Given a z-buffer
with corresponding features and weights, these values are accumulated
@@ -226,7 +221,7 @@ class _CompositeWeightedSumPoints(torch.autograd.Function):
return grad_features, grad_alphas, grad_points_idx, None
def weighted_sum(pointsidx, alphas, pt_clds, blend_params=None) -> torch.Tensor:
def weighted_sum(pointsidx, alphas, pt_clds) -> torch.Tensor:
"""
Composite features within a z-buffer using normalized weighted sum.

17
pytorch3d/renderer/points/compositor.py
View File

@@ -3,7 +3,7 @@
import torch
import torch.nn as nn
from ..compositing import CompositeParams, alpha_composite, norm_weighted_sum
from ..compositing import alpha_composite, norm_weighted_sum
# A compositor should take as input 3D points and some corresponding information.
@@ -16,15 +16,11 @@ class AlphaCompositor(nn.Module):
Accumulate points using alpha compositing.
"""
def __init__(self, composite_params=None):
def __init__(self):
super().__init__()
self.composite_params = (
composite_params if composite_params is not None else CompositeParams()
)
def forward(self, fragments, alphas, ptclds, **kwargs) -> torch.Tensor:
images = alpha_composite(fragments, alphas, ptclds, self.composite_params)
images = alpha_composite(fragments, alphas, ptclds)
return images
@@ -33,12 +29,9 @@ class NormWeightedCompositor(nn.Module):
Accumulate points using a normalized weighted sum.
"""
def __init__(self, composite_params=None):
def __init__(self):
super().__init__()
self.composite_params = (
composite_params if composite_params is not None else CompositeParams()
)
def forward(self, fragments, alphas, ptclds, **kwargs) -> torch.Tensor:
images = norm_weighted_sum(fragments, alphas, ptclds, self.composite_params)
images = norm_weighted_sum(fragments, alphas, ptclds)
return images