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add align modes for cubify
Summary: Add alignment modes for cubify operation. Reviewed By: nikhilaravi Differential Revision: D21393199 fbshipit-source-id: 7022044e591229a6ed5efc361fd3215e65f43f86
This commit is contained in:
Georgia Gkioxari
committed by
Facebook GitHub Bot
Facebook GitHub Bot
parent
8fc28baa27
commit
a61c9376d5
@@ -3,16 +3,17 @@
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import unittest
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import torch
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from common_testing import TestCaseMixin
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from pytorch3d.ops import cubify
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class TestCubify(unittest.TestCase):
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class TestCubify(TestCaseMixin, unittest.TestCase):
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def test_allempty(self):
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N, V = 32, 14
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device = torch.device("cuda:0")
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voxels = torch.zeros((N, V, V, V), dtype=torch.float32, device=device)
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meshes = cubify(voxels, 0.5, 0)
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self.assertTrue(meshes.isempty)
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meshes = cubify(voxels, 0.5)
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self.assertTrue(meshes.isempty())
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def test_cubify(self):
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N, V = 4, 2
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@@ -29,155 +30,143 @@ class TestCubify(unittest.TestCase):
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voxels[3, 1, 1, 0] = 1.0
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# compute cubify
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meshes = cubify(voxels, 0.5, 0)
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meshes = cubify(voxels, 0.5)
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# 1st-check
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verts, faces = meshes.get_mesh_verts_faces(0)
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self.assertTrue(
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torch.allclose(faces.max().cpu(), torch.tensor([verts.size(0) - 1]))
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self.assertClose(faces.max().cpu(), torch.tensor(verts.size(0) - 1))
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self.assertClose(
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verts,
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torch.tensor(
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[
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[-1.0, -1.0, -1.0],
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[-1.0, -1.0, 1.0],
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[1.0, -1.0, -1.0],
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[1.0, -1.0, 1.0],
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[-1.0, 1.0, -1.0],
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[-1.0, 1.0, 1.0],
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[1.0, 1.0, -1.0],
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[1.0, 1.0, 1.0],
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],
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dtype=torch.float32,
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device=device,
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),
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)
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self.assertTrue(
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torch.allclose(
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verts,
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torch.tensor(
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[
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[-1.0, -1.0, -1.0],
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[-1.0, -1.0, 1.0],
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[1.0, -1.0, -1.0],
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[1.0, -1.0, 1.0],
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[-1.0, 1.0, -1.0],
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[-1.0, 1.0, 1.0],
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[1.0, 1.0, -1.0],
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[1.0, 1.0, 1.0],
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],
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dtype=torch.float32,
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device=device,
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),
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)
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)
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self.assertTrue(
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torch.allclose(
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faces,
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torch.tensor(
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[
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[0, 1, 4],
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[1, 5, 4],
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[4, 5, 6],
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[5, 7, 6],
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[0, 4, 6],
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[0, 6, 2],
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[0, 3, 1],
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[0, 2, 3],
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[6, 7, 3],
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[6, 3, 2],
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[1, 7, 5],
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[1, 3, 7],
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],
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dtype=torch.int64,
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device=device,
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),
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)
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self.assertClose(
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faces,
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torch.tensor(
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[
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[0, 1, 4],
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[1, 5, 4],
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[4, 5, 6],
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[5, 7, 6],
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[0, 4, 6],
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[0, 6, 2],
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[0, 3, 1],
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[0, 2, 3],
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[6, 7, 3],
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[6, 3, 2],
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[1, 7, 5],
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[1, 3, 7],
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],
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dtype=torch.int64,
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device=device,
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),
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)
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# 2nd-check
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verts, faces = meshes.get_mesh_verts_faces(1)
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self.assertTrue(
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torch.allclose(faces.max().cpu(), torch.tensor([verts.size(0) - 1]))
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self.assertClose(faces.max().cpu(), torch.tensor(verts.size(0) - 1))
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self.assertClose(
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verts,
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torch.tensor(
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[
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[-1.0, -1.0, -1.0],
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[-1.0, -1.0, 1.0],
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[-1.0, -1.0, 3.0],
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[1.0, -1.0, -1.0],
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[1.0, -1.0, 1.0],
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[1.0, -1.0, 3.0],
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[3.0, -1.0, -1.0],
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[3.0, -1.0, 1.0],
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[3.0, -1.0, 3.0],
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[-1.0, 1.0, -1.0],
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[-1.0, 1.0, 1.0],
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[-1.0, 1.0, 3.0],
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[1.0, 1.0, -1.0],
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[1.0, 1.0, 3.0],
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[3.0, 1.0, -1.0],
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[3.0, 1.0, 1.0],
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[3.0, 1.0, 3.0],
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[-1.0, 3.0, -1.0],
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[-1.0, 3.0, 1.0],
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[-1.0, 3.0, 3.0],
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[1.0, 3.0, -1.0],
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[1.0, 3.0, 1.0],
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[1.0, 3.0, 3.0],
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[3.0, 3.0, -1.0],
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[3.0, 3.0, 1.0],
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[3.0, 3.0, 3.0],
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],
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dtype=torch.float32,
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device=device,
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),
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)
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self.assertTrue(
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torch.allclose(
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verts,
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torch.tensor(
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[
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[-1.0, -1.0, -1.0],
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[-1.0, -1.0, 1.0],
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[-1.0, -1.0, 3.0],
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[1.0, -1.0, -1.0],
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[1.0, -1.0, 1.0],
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[1.0, -1.0, 3.0],
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[3.0, -1.0, -1.0],
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[3.0, -1.0, 1.0],
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[3.0, -1.0, 3.0],
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[-1.0, 1.0, -1.0],
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[-1.0, 1.0, 1.0],
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[-1.0, 1.0, 3.0],
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[1.0, 1.0, -1.0],
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[1.0, 1.0, 3.0],
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[3.0, 1.0, -1.0],
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[3.0, 1.0, 1.0],
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[3.0, 1.0, 3.0],
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[-1.0, 3.0, -1.0],
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[-1.0, 3.0, 1.0],
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[-1.0, 3.0, 3.0],
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[1.0, 3.0, -1.0],
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[1.0, 3.0, 1.0],
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[1.0, 3.0, 3.0],
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[3.0, 3.0, -1.0],
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[3.0, 3.0, 1.0],
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[3.0, 3.0, 3.0],
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],
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dtype=torch.float32,
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device=device,
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),
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)
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)
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self.assertTrue(
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torch.allclose(
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faces,
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torch.tensor(
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[
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[0, 1, 9],
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[1, 10, 9],
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[0, 9, 12],
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[0, 12, 3],
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[0, 4, 1],
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[0, 3, 4],
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[1, 2, 10],
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[2, 11, 10],
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[1, 5, 2],
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[1, 4, 5],
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[2, 13, 11],
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[2, 5, 13],
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[3, 12, 14],
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[3, 14, 6],
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[3, 7, 4],
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[3, 6, 7],
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[14, 15, 7],
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[14, 7, 6],
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[4, 8, 5],
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[4, 7, 8],
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[15, 16, 8],
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[15, 8, 7],
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[5, 16, 13],
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[5, 8, 16],
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[9, 10, 17],
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[10, 18, 17],
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[17, 18, 20],
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[18, 21, 20],
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[9, 17, 20],
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[9, 20, 12],
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[10, 11, 18],
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[11, 19, 18],
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[18, 19, 21],
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[19, 22, 21],
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[11, 22, 19],
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[11, 13, 22],
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[20, 21, 23],
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[21, 24, 23],
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[12, 20, 23],
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[12, 23, 14],
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[23, 24, 15],
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[23, 15, 14],
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[21, 22, 24],
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[22, 25, 24],
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[24, 25, 16],
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[24, 16, 15],
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[13, 25, 22],
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[13, 16, 25],
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],
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dtype=torch.int64,
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device=device,
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),
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)
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self.assertClose(
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faces,
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torch.tensor(
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[
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[0, 1, 9],
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[1, 10, 9],
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[0, 9, 12],
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[0, 12, 3],
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[0, 4, 1],
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[0, 3, 4],
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[1, 2, 10],
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[2, 11, 10],
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[1, 5, 2],
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[1, 4, 5],
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[2, 13, 11],
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[2, 5, 13],
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[3, 12, 14],
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[3, 14, 6],
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[3, 7, 4],
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[3, 6, 7],
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[14, 15, 7],
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[14, 7, 6],
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[4, 8, 5],
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[4, 7, 8],
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[15, 16, 8],
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[15, 8, 7],
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[5, 16, 13],
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[5, 8, 16],
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[9, 10, 17],
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[10, 18, 17],
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[17, 18, 20],
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[18, 21, 20],
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[9, 17, 20],
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[9, 20, 12],
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[10, 11, 18],
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[11, 19, 18],
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[18, 19, 21],
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[19, 22, 21],
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[11, 22, 19],
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[11, 13, 22],
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[20, 21, 23],
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[21, 24, 23],
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[12, 20, 23],
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[12, 23, 14],
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[23, 24, 15],
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[23, 15, 14],
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[21, 22, 24],
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[22, 25, 24],
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[24, 25, 16],
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[24, 16, 15],
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[13, 25, 22],
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[13, 16, 25],
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],
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dtype=torch.int64,
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device=device,
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),
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)
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# 3rd-check
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@@ -187,91 +176,127 @@ class TestCubify(unittest.TestCase):
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# 4th-check
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verts, faces = meshes.get_mesh_verts_faces(3)
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self.assertTrue(
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torch.allclose(
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verts,
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torch.tensor(
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[
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[1.0, -1.0, -1.0],
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[1.0, -1.0, 1.0],
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[1.0, -1.0, 3.0],
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[3.0, -1.0, -1.0],
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[3.0, -1.0, 1.0],
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[3.0, -1.0, 3.0],
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[-1.0, 1.0, 1.0],
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[-1.0, 1.0, 3.0],
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[1.0, 1.0, -1.0],
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[1.0, 1.0, 1.0],
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[1.0, 1.0, 3.0],
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[3.0, 1.0, -1.0],
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[3.0, 1.0, 1.0],
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[3.0, 1.0, 3.0],
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[-1.0, 3.0, 1.0],
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[-1.0, 3.0, 3.0],
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[1.0, 3.0, -1.0],
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[1.0, 3.0, 1.0],
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[1.0, 3.0, 3.0],
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[3.0, 3.0, -1.0],
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[3.0, 3.0, 1.0],
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[3.0, 3.0, 3.0],
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],
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dtype=torch.float32,
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device=device,
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),
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)
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self.assertClose(
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verts,
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torch.tensor(
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[
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[1.0, -1.0, -1.0],
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[1.0, -1.0, 1.0],
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[1.0, -1.0, 3.0],
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[3.0, -1.0, -1.0],
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[3.0, -1.0, 1.0],
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[3.0, -1.0, 3.0],
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[-1.0, 1.0, 1.0],
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[-1.0, 1.0, 3.0],
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[1.0, 1.0, -1.0],
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[1.0, 1.0, 1.0],
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[1.0, 1.0, 3.0],
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[3.0, 1.0, -1.0],
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[3.0, 1.0, 1.0],
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[3.0, 1.0, 3.0],
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[-1.0, 3.0, 1.0],
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[-1.0, 3.0, 3.0],
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[1.0, 3.0, -1.0],
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[1.0, 3.0, 1.0],
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[1.0, 3.0, 3.0],
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[3.0, 3.0, -1.0],
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[3.0, 3.0, 1.0],
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[3.0, 3.0, 3.0],
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],
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dtype=torch.float32,
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device=device,
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),
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)
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self.assertTrue(
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torch.allclose(
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faces,
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torch.tensor(
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[
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[0, 1, 8],
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[1, 9, 8],
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[0, 8, 11],
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[0, 11, 3],
|
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[0, 4, 1],
|
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[0, 3, 4],
|
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[11, 12, 4],
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[11, 4, 3],
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[1, 2, 9],
|
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[2, 10, 9],
|
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[1, 5, 2],
|
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[1, 4, 5],
|
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[12, 13, 5],
|
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[12, 5, 4],
|
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[2, 13, 10],
|
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[2, 5, 13],
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[6, 7, 14],
|
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[7, 15, 14],
|
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[14, 15, 17],
|
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[15, 18, 17],
|
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[6, 14, 17],
|
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[6, 17, 9],
|
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[6, 10, 7],
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[6, 9, 10],
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[7, 18, 15],
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[7, 10, 18],
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[8, 9, 16],
|
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[9, 17, 16],
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[16, 17, 19],
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[17, 20, 19],
|
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[8, 16, 19],
|
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[8, 19, 11],
|
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[19, 20, 12],
|
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[19, 12, 11],
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[17, 18, 20],
|
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[18, 21, 20],
|
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[20, 21, 13],
|
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[20, 13, 12],
|
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[10, 21, 18],
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[10, 13, 21],
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],
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dtype=torch.int64,
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device=device,
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),
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)
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self.assertClose(
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faces,
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torch.tensor(
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[
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[0, 1, 8],
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[1, 9, 8],
|
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[0, 8, 11],
|
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[0, 11, 3],
|
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[0, 4, 1],
|
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[0, 3, 4],
|
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[11, 12, 4],
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[11, 4, 3],
|
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[1, 2, 9],
|
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[2, 10, 9],
|
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[1, 5, 2],
|
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[1, 4, 5],
|
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[12, 13, 5],
|
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[12, 5, 4],
|
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[2, 13, 10],
|
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[2, 5, 13],
|
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[6, 7, 14],
|
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[7, 15, 14],
|
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[14, 15, 17],
|
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[15, 18, 17],
|
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[6, 14, 17],
|
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[6, 17, 9],
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[6, 10, 7],
|
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[6, 9, 10],
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[7, 18, 15],
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[7, 10, 18],
|
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[8, 9, 16],
|
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[9, 17, 16],
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[16, 17, 19],
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[17, 20, 19],
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[8, 16, 19],
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[8, 19, 11],
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[19, 20, 12],
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[19, 12, 11],
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[17, 18, 20],
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[18, 21, 20],
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[20, 21, 13],
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[20, 13, 12],
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[10, 21, 18],
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[10, 13, 21],
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],
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dtype=torch.int64,
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device=device,
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),
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)
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def test_align(self):
|
||||
N, V = 1, 2
|
||||
device = torch.device("cuda:0")
|
||||
voxels = torch.ones((N, V, V, V), dtype=torch.float32, device=device)
|
||||
|
||||
# topleft align
|
||||
mesh = cubify(voxels, 0.5)
|
||||
verts, faces = mesh.get_mesh_verts_faces(0)
|
||||
self.assertClose(verts.min(), torch.tensor(-1.0, device=device))
|
||||
self.assertClose(verts.max(), torch.tensor(3.0, device=device))
|
||||
|
||||
# corner align
|
||||
mesh = cubify(voxels, 0.5, align="corner")
|
||||
verts, faces = mesh.get_mesh_verts_faces(0)
|
||||
self.assertClose(verts.min(), torch.tensor(-1.0, device=device))
|
||||
self.assertClose(verts.max(), torch.tensor(1.0, device=device))
|
||||
|
||||
# center align
|
||||
mesh = cubify(voxels, 0.5, align="center")
|
||||
verts, faces = mesh.get_mesh_verts_faces(0)
|
||||
self.assertClose(verts.min(), torch.tensor(-2.0, device=device))
|
||||
self.assertClose(verts.max(), torch.tensor(2.0, device=device))
|
||||
|
||||
# invalid align
|
||||
with self.assertRaisesRegex(ValueError, "Align mode must be one of"):
|
||||
cubify(voxels, 0.5, align="")
|
||||
|
||||
# invalid align
|
||||
with self.assertRaisesRegex(ValueError, "Align mode must be one of"):
|
||||
cubify(voxels, 0.5, align="topright")
|
||||
|
||||
# inside occupancy, similar to GH#185 use case
|
||||
N, V = 1, 4
|
||||
voxels = torch.zeros((N, V, V, V), dtype=torch.float32, device=device)
|
||||
voxels[0, : V // 2, : V // 2, : V // 2] = 1.0
|
||||
mesh = cubify(voxels, 0.5, align="corner")
|
||||
verts, faces = mesh.get_mesh_verts_faces(0)
|
||||
self.assertClose(verts.min(), torch.tensor(-1.0, device=device))
|
||||
self.assertClose(verts.max(), torch.tensor(0.0, device=device))
|
||||
|
||||
@staticmethod
|
||||
def cubify_with_init(batch_size: int, V: int):
|
||||
device = torch.device("cuda:0")
|
||||
|
||||
Reference in New Issue
Block a user