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https://github.com/facebookresearch/pytorch3d.git
synced 2025-08-02 03:42:50 +08:00
small fix for iou3d
Summary: A small numerical fix for IoU for 3D boxes, fixes GH #992 * Adds a check for boxes with zero side areas (invalid boxes) * Fixes numerical issue when two boxes have coplanar sides Reviewed By: nikhilaravi Differential Revision: D33195691 fbshipit-source-id: 8a34b4d1f1e5ec2edb6d54143930da44bdde0906
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@ -90,7 +90,8 @@ __global__ void IoUBox3DKernel(
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for (int b2 = 0; b2 < box2_count; ++b2) {
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const bool is_coplanar =
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IsCoplanarFace(box1_intersect[b1], box2_intersect[b2]);
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if (is_coplanar) {
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const float area = FaceArea(box1_intersect[b1]);
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if ((is_coplanar) && (area > kEpsilon)) {
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tri2_keep[b2].keep = false;
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}
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}
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@ -81,7 +81,8 @@ std::tuple<at::Tensor, at::Tensor> IoUBox3DCpu(
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for (int b2 = 0; b2 < box2_intersect.size(); ++b2) {
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const bool is_coplanar =
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IsCoplanarFace(box1_intersect[b1], box2_intersect[b2]);
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if (is_coplanar) {
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const float area = FaceArea(box1_intersect[b1]);
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if ((is_coplanar) && (area > kEpsilon)) {
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tri2_keep[b2] = 0;
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}
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}
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@ -138,6 +138,26 @@ FaceNormal(const float3 v0, const float3 v1, const float3 v2) {
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return n;
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}
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// The area of the face defined by vertices (v0, v1, v2)
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// Define e0 to be the edge connecting (v1, v0)
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// Define e1 to be the edge connecting (v2, v0)
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// Area is the norm of the cross product of e0, e1 divided by 2.0
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//
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// Args
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// tri: FaceVerts of float3 coordinates of the vertices of the face
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//
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// Returns
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// float: area for the face
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//
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__device__ inline float FaceArea(const FaceVerts& tri) {
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// Get verts for face 1
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const float3 v0 = tri.v0;
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const float3 v1 = tri.v1;
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const float3 v2 = tri.v2;
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const float3 n = cross(v1 - v0, v2 - v0);
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return norm(n) / 2.0;
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}
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// The normal of a box plane defined by the verts in `plane` with
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// the centroid of the box given by `center`.
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// Args
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@ -145,6 +145,26 @@ inline vec3<float> FaceNormal(vec3<float> v0, vec3<float> v1, vec3<float> v2) {
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return n;
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}
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// The area of the face defined by vertices (v0, v1, v2)
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// Define e0 to be the edge connecting (v1, v0)
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// Define e1 to be the edge connecting (v2, v0)
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// Area is the norm of the cross product of e0, e1 divided by 2.0
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//
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// Args
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// tri: vec3 coordinates of the vertices of the face
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//
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// Returns
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// float: area for the face
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//
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inline float FaceArea(const std::vector<vec3<float>>& tri) {
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// Get verts for face
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const vec3<float> v0 = tri[0];
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const vec3<float> v1 = tri[1];
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const vec3<float> v2 = tri[2];
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const vec3<float> n = cross(v1 - v0, v2 - v0);
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return norm(n) / 2.0;
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}
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// The normal of a box plane defined by the verts in `plane` with
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// the centroid of the box given by `center`.
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// Args
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@ -69,6 +69,28 @@ def _check_coplanar(boxes: torch.Tensor, eps: float = 1e-4) -> None:
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return
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def _check_nonzero(boxes: torch.Tensor, eps: float = 1e-4) -> None:
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"""
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Checks that the sides of the box have a non zero area
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"""
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faces = torch.tensor(_box_triangles, dtype=torch.int64, device=boxes.device)
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# pyre-fixme[16]: `boxes` has no attribute `index_select`.
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verts = boxes.index_select(index=faces.view(-1), dim=1)
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B = boxes.shape[0]
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T, V = faces.shape
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# (B, T, 3, 3) -> (B, T, 3)
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v0, v1, v2 = verts.reshape(B, T, V, 3).unbind(2)
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normals = torch.cross(v1 - v0, v2 - v0, dim=-1) # (B, T, 3)
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face_areas = normals.norm(dim=-1) / 2
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if (face_areas < eps).any().item():
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msg = "Planes have zero areas"
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raise ValueError(msg)
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return
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class _box3d_overlap(Function):
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"""
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Torch autograd Function wrapper for box3d_overlap C++/CUDA implementations.
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@ -138,6 +160,8 @@ def box3d_overlap(
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_check_coplanar(boxes1, eps)
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_check_coplanar(boxes2, eps)
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_check_nonzero(boxes1, eps)
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_check_nonzero(boxes2, eps)
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# pyre-fixme[16]: `_box3d_overlap` has no attribute `apply`.
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vol, iou = _box3d_overlap.apply(boxes1, boxes2)
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@ -111,6 +111,11 @@ class TestIoU3D(TestCaseMixin, unittest.TestCase):
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self.assertClose(
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vol, torch.tensor([[1 - dd]], device=vol.device, dtype=vol.dtype)
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)
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# symmetry
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vol, iou = overlap_fn(box2[None], box1[None])
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self.assertClose(
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vol, torch.tensor([[1 - dd]], device=vol.device, dtype=vol.dtype)
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)
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# 3rd test
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dd = random.random()
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@ -119,6 +124,11 @@ class TestIoU3D(TestCaseMixin, unittest.TestCase):
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self.assertClose(
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vol, torch.tensor([[1 - dd]], device=vol.device, dtype=vol.dtype)
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)
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# symmetry
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vol, _ = overlap_fn(box2[None], box1[None])
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self.assertClose(
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vol, torch.tensor([[1 - dd]], device=vol.device, dtype=vol.dtype)
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)
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# 4th test
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ddx, ddy, ddz = random.random(), random.random(), random.random()
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@ -132,6 +142,16 @@ class TestIoU3D(TestCaseMixin, unittest.TestCase):
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dtype=vol.dtype,
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),
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)
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# symmetry
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vol, _ = overlap_fn(box2[None], box1[None])
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self.assertClose(
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vol,
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torch.tensor(
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[[(1 - ddx) * (1 - ddy) * (1 - ddz)]],
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device=vol.device,
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dtype=vol.dtype,
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),
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)
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# Also check IoU is 1 when computing overlap with the same shifted box
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vol, iou = overlap_fn(box2[None], box2[None])
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@ -152,6 +172,16 @@ class TestIoU3D(TestCaseMixin, unittest.TestCase):
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dtype=vol.dtype,
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),
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)
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# symmetry
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vol, _ = overlap_fn(box2r[None], box1r[None])
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self.assertClose(
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vol,
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torch.tensor(
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[[(1 - ddx) * (1 - ddy) * (1 - ddz)]],
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device=vol.device,
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dtype=vol.dtype,
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),
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)
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# 6th test
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ddx, ddy, ddz = random.random(), random.random(), random.random()
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@ -170,6 +200,17 @@ class TestIoU3D(TestCaseMixin, unittest.TestCase):
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),
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atol=1e-7,
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)
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# symmetry
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vol, _ = overlap_fn(box2r[None], box1r[None])
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self.assertClose(
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vol,
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torch.tensor(
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[[(1 - ddx) * (1 - ddy) * (1 - ddz)]],
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device=vol.device,
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dtype=vol.dtype,
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),
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atol=1e-7,
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)
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# 7th test: hand coded example and test with meshlab output
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@ -214,6 +255,10 @@ class TestIoU3D(TestCaseMixin, unittest.TestCase):
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vol, iou = overlap_fn(box1r[None], box2r[None])
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self.assertClose(vol, torch.tensor([[vol_inters]], device=device), atol=1e-1)
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self.assertClose(iou, torch.tensor([[iou_mesh]], device=device), atol=1e-1)
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# symmetry
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vol, iou = overlap_fn(box2r[None], box1r[None])
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self.assertClose(vol, torch.tensor([[vol_inters]], device=device), atol=1e-1)
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self.assertClose(iou, torch.tensor([[iou_mesh]], device=device), atol=1e-1)
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# 8th test: compare with sampling
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# create box1
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@ -232,7 +277,9 @@ class TestIoU3D(TestCaseMixin, unittest.TestCase):
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iou_sampling = self._box3d_overlap_sampling_batched(
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box1r[None], box2r[None], num_samples=10000
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)
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self.assertClose(iou, iou_sampling, atol=1e-2)
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# symmetry
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vol, iou = overlap_fn(box2r[None], box1r[None])
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self.assertClose(iou, iou_sampling, atol=1e-2)
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# 9th test: non overlapping boxes, iou = 0.0
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@ -240,6 +287,10 @@ class TestIoU3D(TestCaseMixin, unittest.TestCase):
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vol, iou = overlap_fn(box1[None], box2[None])
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self.assertClose(vol, torch.tensor([[0.0]], device=vol.device, dtype=vol.dtype))
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self.assertClose(iou, torch.tensor([[0.0]], device=vol.device, dtype=vol.dtype))
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# symmetry
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vol, iou = overlap_fn(box2[None], box1[None])
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self.assertClose(vol, torch.tensor([[0.0]], device=vol.device, dtype=vol.dtype))
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self.assertClose(iou, torch.tensor([[0.0]], device=vol.device, dtype=vol.dtype))
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# 10th test: Non coplanar verts in a plane
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box10 = box1 + torch.rand((8, 3), dtype=torch.float32, device=device)
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@ -284,6 +335,56 @@ class TestIoU3D(TestCaseMixin, unittest.TestCase):
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vols, ious = overlap_fn(box_skew_1[None], box_skew_2[None])
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self.assertClose(vols, torch.tensor([[vol_inters]], device=device), atol=1e-1)
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self.assertClose(ious, torch.tensor([[iou]], device=device), atol=1e-1)
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# symmetry
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vols, ious = overlap_fn(box_skew_2[None], box_skew_1[None])
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self.assertClose(vols, torch.tensor([[vol_inters]], device=device), atol=1e-1)
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self.assertClose(ious, torch.tensor([[iou]], device=device), atol=1e-1)
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# 12th test: Zero area bounding box (from GH issue #992)
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box12a = torch.tensor(
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[
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[-1.0000, -1.0000, -0.5000],
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[1.0000, -1.0000, -0.5000],
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[1.0000, 1.0000, -0.5000],
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[-1.0000, 1.0000, -0.5000],
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[-1.0000, -1.0000, 0.5000],
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[1.0000, -1.0000, 0.5000],
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[1.0000, 1.0000, 0.5000],
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[-1.0000, 1.0000, 0.5000],
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],
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device=device,
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dtype=torch.float32,
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)
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box12b = torch.tensor(
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[
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[0.0, 0.0, 0.0],
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[0.0, 0.0, 0.0],
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[0.0, 0.0, 0.0],
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[0.0, 0.0, 0.0],
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[0.0, 0.0, 0.0],
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[0.0, 0.0, 0.0],
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[0.0, 0.0, 0.0],
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[0.0, 0.0, 0.0],
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],
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device=device,
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dtype=torch.float32,
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)
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msg = "Planes have zero areas"
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with self.assertRaisesRegex(ValueError, msg):
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overlap_fn(box12a[None], box12b[None])
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# symmetry
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with self.assertRaisesRegex(ValueError, msg):
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overlap_fn(box12b[None], box12a[None])
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# 13th test: From GH issue #992
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# Zero area coplanar face after intersection
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ctrs = torch.tensor([[0.0, 0.0, 0.0], [-1.0, 1.0, 0.0]])
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whl = torch.tensor([[2.0, 2.0, 2.0], [2.0, 2, 2]])
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box13a = TestIoU3D.create_box(ctrs[0], whl[0])
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box13b = TestIoU3D.create_box(ctrs[1], whl[1])
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vol, iou = overlap_fn(box13a[None], box13b[None])
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self.assertClose(vol, torch.tensor([[2.0]], device=vol.device, dtype=vol.dtype))
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def _test_real_boxes(self, overlap_fn, device):
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data_filename = "./real_boxes.pkl"
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@ -577,6 +678,13 @@ def box_planar_dir(box: torch.Tensor, eps=1e-4) -> torch.Tensor:
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msg = "Plane vertices are not coplanar"
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raise ValueError(msg)
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# Check all faces have non zero area
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area1 = torch.cross(v1 - v0, v2 - v0, dim=-1).norm(dim=-1) / 2
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area2 = torch.cross(v3 - v0, v2 - v0, dim=-1).norm(dim=-1) / 2
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if (area1 < eps).any().item() or (area2 < eps).any().item():
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msg = "Planes have zero areas"
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raise ValueError(msg)
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# We can write: `ctr = v0 + a * e0 + b * e1 + c * n`, (1).
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# With <e0, n> = 0 and <e1, n> = 0, where <.,.> refers to the dot product,
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# since that e0 is orthogonal to n. Same for e1.
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@ -607,6 +715,27 @@ def box_planar_dir(box: torch.Tensor, eps=1e-4) -> torch.Tensor:
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return n
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def tri_verts_area(tri_verts: torch.Tensor) -> torch.Tensor:
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"""
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Computes the area of the triangle faces in tri_verts
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Args:
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tri_verts: tensor of shape (T, 3, 3)
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Returns:
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areas: the area of the triangles (T, 1)
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"""
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add_dim = False
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if tri_verts.ndim == 2:
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tri_verts = tri_verts.unsqueeze(0)
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add_dim = True
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v0, v1, v2 = tri_verts.unbind(1)
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areas = torch.cross(v1 - v0, v2 - v0, dim=-1).norm(dim=-1) / 2.0
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if add_dim:
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areas = areas[0]
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return areas
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def box_volume(box: torch.Tensor) -> torch.Tensor:
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"""
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Computes the volume of each box in boxes.
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@ -988,7 +1117,10 @@ def box3d_overlap_naive(box1: torch.Tensor, box2: torch.Tensor):
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keep2 = torch.ones((tri_verts2.shape[0],), device=device, dtype=torch.bool)
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for i1 in range(tri_verts1.shape[0]):
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for i2 in range(tri_verts2.shape[0]):
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if coplanar_tri_faces(tri_verts1[i1], tri_verts2[i2]):
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if (
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coplanar_tri_faces(tri_verts1[i1], tri_verts2[i2])
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and tri_verts_area(tri_verts1[i1]) > 1e-4
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):
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keep2[i2] = 0
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keep2 = keep2.nonzero()[:, 0]
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tri_verts2 = tri_verts2[keep2]
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