IOU box3d epsilon fix

Summary: The epsilon value is important for determining whether vertices are inside/outside a plane.

Reviewed By: gkioxari

Differential Revision: D31485247

fbshipit-source-id: 5517575de7c02f1afa277d00e0190a81f44f5761
This commit is contained in:
Nikhila Ravi 2021-10-07 18:40:56 -07:00 committed by Facebook GitHub Bot
parent b26f4bc33a
commit 6dfa326922
4 changed files with 28 additions and 9 deletions

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@ -11,7 +11,8 @@
#include <thrust/device_vector.h>
#include <cstdio>
#include "utils/float_math.cuh"
#include "utils/geometry_utils.cuh"
const auto kEpsilon = 1e-4;
/*
_PLANES and _TRIS define the 4- and 3-connectivity

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@ -16,9 +16,9 @@
#include <queue>
#include <tuple>
#include <type_traits>
#include "utils/geometry_utils.h"
#include "utils/vec3.h"
const auto kEpsilon = 1e-4;
/*
_PLANES and _TRIS define the 4- and 3-connectivity
of the 8 box corners.

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tests/data/real_boxes.pkl Normal file

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@ -4,6 +4,7 @@
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import pickle
import random
import unittest
from typing import List, Tuple, Union
@ -15,7 +16,6 @@ from pytorch3d.io import save_obj
from pytorch3d.ops.iou_box3d import _box_planes, _box_triangles, box3d_overlap
from pytorch3d.transforms.rotation_conversions import random_rotation
OBJECTRON_TO_PYTORCH3D_FACE_IDX = [0, 4, 6, 2, 1, 5, 7, 3]
DATA_DIR = get_tests_dir() / "data"
DEBUG = False
@ -167,6 +167,7 @@ class TestIoU3D(TestCaseMixin, unittest.TestCase):
device=vol.device,
dtype=vol.dtype,
),
atol=1e-7,
)
# 7th test: hand coded example and test with meshlab output
@ -283,20 +284,36 @@ class TestIoU3D(TestCaseMixin, unittest.TestCase):
self.assertClose(vols, torch.tensor([[vol_inters]], device=device), atol=1e-1)
self.assertClose(ious, torch.tensor([[iou]], device=device), atol=1e-1)
def _test_real_boxes(self, overlap_fn, device):
data_filename = "./real_boxes.pkl"
with open(DATA_DIR / data_filename, "rb") as f:
example = pickle.load(f)
verts1 = torch.FloatTensor(example["verts1"])
verts2 = torch.FloatTensor(example["verts2"])
boxes = torch.stack((verts1, verts2)).to(device)
iou_expected = torch.eye(2).to(device)
vol, iou = overlap_fn(boxes, boxes)
self.assertClose(iou, iou_expected)
def test_iou_naive(self):
device = get_random_cuda_device()
self._test_iou(self._box3d_overlap_naive_batched, device)
self._test_compare_objectron(self._box3d_overlap_naive_batched, device)
self._test_real_boxes(self._box3d_overlap_naive_batched, device)
def test_iou_cpu(self):
device = torch.device("cpu")
self._test_iou(box3d_overlap, device)
self._test_compare_objectron(box3d_overlap, device)
self._test_real_boxes(box3d_overlap, device)
def test_iou_cuda(self):
device = torch.device("cuda:0")
self._test_iou(box3d_overlap, device)
self._test_compare_objectron(box3d_overlap, device)
self._test_real_boxes(box3d_overlap, device)
def _test_compare_objectron(self, overlap_fn, device):
# Load saved objectron data
@ -656,7 +673,7 @@ def is_inside(
n: torch.Tensor,
points: torch.Tensor,
return_proj: bool = True,
eps: float = 1e-6,
eps: float = 1e-4,
):
"""
Computes whether point is "inside" the plane.
@ -778,17 +795,17 @@ def clip_tri_by_plane_oneout(
vout is "outside" the plane and vin1, vin2 are "inside"
Returns:
verts: tensor of shape (4, 3) containing the new vertices formed after clipping the
original intersectiong triangle (vout, vin1, vin2)
original intersecting triangle (vout, vin1, vin2)
faces: tensor of shape (2, 3) defining the vertex indices forming the two new triangles
which are "inside" the plane formed after clipping
"""
device = plane.device
# point of intersection between plane and (vin1, vout)
pint1, a1 = plane_edge_point_of_intersection(plane, n, vin1, vout)
assert a1 >= eps and a1 <= 1.0, a1
assert a1 >= -eps and a1 <= 1.0 + eps, a1
# point of intersection between plane and (vin2, vout)
pint2, a2 = plane_edge_point_of_intersection(plane, n, vin2, vout)
assert a2 >= 0.0 and a2 <= 1.0, a2
assert a2 >= -eps and a2 <= 1.0 + eps, a2
verts = torch.stack((vin1, pint1, pint2, vin2), dim=0) # 4x3
faces = torch.tensor(
@ -823,10 +840,10 @@ def clip_tri_by_plane_twoout(
device = plane.device
# point of intersection between plane and (vin, vout1)
pint1, a1 = plane_edge_point_of_intersection(plane, n, vin, vout1)
assert a1 >= eps and a1 <= 1.0, a1
assert a1 >= -eps and a1 <= 1.0 + eps, a1
# point of intersection between plane and (vin, vout2)
pint2, a2 = plane_edge_point_of_intersection(plane, n, vin, vout2)
assert a2 >= eps and a2 <= 1.0, a2
assert a2 >= -eps and a2 <= 1.0 + eps, a2
verts = torch.stack((vin, pint1, pint2), dim=0) # 3x3
faces = torch.tensor(
@ -917,6 +934,7 @@ def box3d_overlap_naive(box1: torch.Tensor, box2: torch.Tensor):
`iou = vol / (vol1 + vol2 - vol)`
"""
device = box1.device
# For boxes1 we compute the unit directions n1 corresponding to quad_faces
n1 = box_planar_dir(box1) # (6, 3)
# For boxes2 we compute the unit directions n2 corresponding to quad_faces