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Bug fix for case where aspect ratio is a float

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Summary:
- Fix the calculation of the non square NDC range when the H and W are not integer multiples.
- Add test for this case

Reviewed By: gkioxari

Differential Revision: D26613213

fbshipit-source-id: df6763cac602e9f1d516b41b432c4d2cfbaa356d
This commit is contained in:
Nikhila Ravi
2021-02-24 10:05:07 -08:00
committed by Facebook GitHub Bot
parent 0345f860d4
commit 13429640d3
4 changed files with 15 additions and 18 deletions
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4
pytorch3d/csrc/rasterize_points/rasterization_utils.cuh
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@@ -10,7 +10,9 @@
__device__ inline float NonSquareNdcRange(int S1, int S2) {
float range = 2.0f;
if (S1 > S2) {
range = ((S1 / S2) * range);
// First multiply S1 by float range so that division results
// in a float value.
range = (S1 * range) / S2;
}
return range;
}

2
pytorch3d/csrc/rasterize_points/rasterization_utils.h
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@@ -10,7 +10,7 @@
inline float NonSquareNdcRange(int S1, int S2) {
float range = 2.0f;
if (S1 > S2) {
range = ((S1 / S2) * range);
range = (S1 * range) / S2;
}
return range;
}

11
pytorch3d/renderer/points/rasterize_points.py
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@@ -2,6 +2,7 @@
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
# pyre-fixme[21]: Could not find name `_C` in `pytorch3d`.
@@ -120,15 +121,7 @@ def rasterize_points(
# Binned CPU rasterization not fully implemented
bin_size = 0
else:
# TODO: These heuristics are not well-thought out!
if max_image_size <= 64:
bin_size = 8
elif max_image_size <= 256:
bin_size = 16
elif max_image_size <= 512:
bin_size = 32
elif max_image_size <= 1024:
bin_size = 64
bin_size = int(2 ** max(np.ceil(np.log2(max_image_size)) - 4, 4))
if bin_size != 0:
# There is a limit on the number of points per bin in the cuda kernel.