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PLY load normals

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Summary: Add ability to load normals when they are present in a PLY file.

Reviewed By: nikhilaravi

Differential Revision: D26458971

fbshipit-source-id: 658270b611f7624eab4f5f62ff438038e1d25723
This commit is contained in:
Jeremy Reizenstein
2021-05-04 05:35:24 -07:00
committed by Facebook GitHub Bot
parent b314beeda1
commit 6fa66f5534
2 changed files with 105 additions and 21 deletions
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51
tests/test_io_ply.py
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@@ -216,14 +216,18 @@ class TestMeshPlyIO(TestCaseMixin, unittest.TestCase):
[[0, 0, 0], [0, 0, 1], [0, 1, 0], [1, 0, 0]], dtype=torch.float32
)
faces = torch.tensor([[0, 1, 2], [0, 2, 3]])
normals = torch.tensor(
[[0, 1, 0], [1, 0, 0], [1, 4, 1], [1, 0, 0]], dtype=torch.float32
)
vert_colors = torch.rand_like(verts)
texture = TexturesVertex(verts_features=[vert_colors])
for do_textures in itertools.product([True, False]):
for do_textures, do_normals in itertools.product([True, False], [True, False]):
mesh = Meshes(
verts=[verts],
faces=[faces],
textures=texture if do_textures else None,
verts_normals=[normals] if do_normals else None,
)
device = torch.device("cuda:0")
@@ -236,12 +240,57 @@ class TestMeshPlyIO(TestCaseMixin, unittest.TestCase):
mesh2 = mesh2.cpu()
self.assertClose(mesh2.verts_padded(), mesh.verts_padded())
self.assertClose(mesh2.faces_padded(), mesh.faces_padded())
if do_normals:
self.assertTrue(mesh.has_verts_normals())
self.assertTrue(mesh2.has_verts_normals())
self.assertClose(
mesh2.verts_normals_padded(), mesh.verts_normals_padded()
)
else:
self.assertFalse(mesh.has_verts_normals())
self.assertFalse(mesh2.has_verts_normals())
self.assertFalse(torch.allclose(mesh2.verts_normals_padded(), normals))
if do_textures:
self.assertIsInstance(mesh2.textures, TexturesVertex)
self.assertClose(mesh2.textures.verts_features_list()[0], vert_colors)
else:
self.assertIsNone(mesh2.textures)
def test_save_load_with_normals(self):
points = torch.tensor(
[[0, 0, 0], [0, 0, 1], [0, 1, 0], [1, 0, 0]], dtype=torch.float32
)
normals = torch.tensor(
[[0, 1, 0], [1, 0, 0], [1, 4, 1], [1, 0, 0]], dtype=torch.float32
)
features = torch.rand_like(points)
for do_features, do_normals in itertools.product([True, False], [True, False]):
cloud = Pointclouds(
points=[points],
features=[features] if do_features else None,
normals=[normals] if do_normals else None,
)
device = torch.device("cuda:0")
io = IO()
with NamedTemporaryFile(mode="w", suffix=".ply") as f:
io.save_pointcloud(cloud.cuda(), f.name)
f.flush()
cloud2 = io.load_pointcloud(f.name, device=device)
self.assertEqual(cloud2.device, device)
cloud2 = cloud2.cpu()
self.assertClose(cloud2.points_padded(), cloud.points_padded())
if do_normals:
self.assertClose(cloud2.normals_padded(), cloud.normals_padded())
else:
self.assertIsNone(cloud.normals_padded())
self.assertIsNone(cloud2.normals_padded())
if do_features:
self.assertClose(cloud2.features_packed(), features)
else:
self.assertIsNone(cloud2.features_packed())
def test_save_ply_invalid_shapes(self):
# Invalid vertices shape
with self.assertRaises(ValueError) as error: