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| | import unittest |
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|
| | import torch |
| | from pytorch3d.renderer.materials import Materials |
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|
| | from .common_testing import TestCaseMixin |
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|
| |
|
| | class TestMaterials(TestCaseMixin, unittest.TestCase): |
| | def test_init(self): |
| | """ |
| | Initialize Materials class with the default values. |
| | """ |
| | device = torch.device("cuda:0") |
| | mat = Materials(device=device) |
| | self.assertTrue(torch.is_tensor(mat.ambient_color)) |
| | self.assertTrue(torch.is_tensor(mat.diffuse_color)) |
| | self.assertTrue(torch.is_tensor(mat.specular_color)) |
| | self.assertTrue(torch.is_tensor(mat.shininess)) |
| | self.assertTrue(mat.ambient_color.device == device) |
| | self.assertTrue(mat.diffuse_color.device == device) |
| | self.assertTrue(mat.specular_color.device == device) |
| | self.assertTrue(mat.shininess.device == device) |
| | self.assertTrue(mat.ambient_color.shape == (1, 3)) |
| | self.assertTrue(mat.diffuse_color.shape == (1, 3)) |
| | self.assertTrue(mat.specular_color.shape == (1, 3)) |
| | self.assertTrue(mat.shininess.shape == (1,)) |
| |
|
| | def test_materials_clone_to(self): |
| | device = torch.device("cuda:0") |
| | cpu = torch.device("cpu") |
| | mat = Materials() |
| | new_mat = mat.clone().to(device) |
| | self.assertTrue(mat.ambient_color.device == cpu) |
| | self.assertTrue(mat.diffuse_color.device == cpu) |
| | self.assertTrue(mat.specular_color.device == cpu) |
| | self.assertTrue(mat.shininess.device == cpu) |
| | self.assertTrue(new_mat.ambient_color.device == device) |
| | self.assertTrue(new_mat.diffuse_color.device == device) |
| | self.assertTrue(new_mat.specular_color.device == device) |
| | self.assertTrue(new_mat.shininess.device == device) |
| | self.assertSeparate(new_mat.ambient_color, mat.ambient_color) |
| | self.assertSeparate(new_mat.diffuse_color, mat.diffuse_color) |
| | self.assertSeparate(new_mat.specular_color, mat.specular_color) |
| | self.assertSeparate(new_mat.shininess, mat.shininess) |
| |
|
| | def test_initialize_materials_broadcast(self): |
| | materials = Materials( |
| | ambient_color=torch.randn(10, 3), |
| | diffuse_color=torch.randn(1, 3), |
| | specular_color=torch.randn(1, 3), |
| | shininess=torch.randn(1), |
| | ) |
| | self.assertTrue(materials.ambient_color.shape == (10, 3)) |
| | self.assertTrue(materials.diffuse_color.shape == (10, 3)) |
| | self.assertTrue(materials.specular_color.shape == (10, 3)) |
| | self.assertTrue(materials.shininess.shape == (10,)) |
| |
|
| | def test_initialize_materials_broadcast_fail(self): |
| | """ |
| | Batch dims have to be the same or 1. |
| | """ |
| | with self.assertRaises(ValueError): |
| | Materials( |
| | ambient_color=torch.randn(10, 3), diffuse_color=torch.randn(15, 3) |
| | ) |
| |
|
| | def test_initialize_materials_dimensions_fail(self): |
| | """ |
| | Color should have shape (N, 3) or (1, 3), Shininess should have shape |
| | (1), (1, 1), (N) or (N, 1) |
| | """ |
| | with self.assertRaises(ValueError): |
| | Materials(ambient_color=torch.randn(10, 4)) |
| |
|
| | with self.assertRaises(ValueError): |
| | Materials(shininess=torch.randn(10, 2)) |
| |
|
| | def test_initialize_materials_mixed_inputs(self): |
| | mat = Materials(ambient_color=torch.randn(1, 3), diffuse_color=((1, 1, 1),)) |
| | self.assertTrue(mat.ambient_color.shape == (1, 3)) |
| | self.assertTrue(mat.diffuse_color.shape == (1, 3)) |
| |
|
| | def test_initialize_materials_mixed_inputs_broadcast(self): |
| | mat = Materials(ambient_color=torch.randn(10, 3), diffuse_color=((1, 1, 1),)) |
| | self.assertTrue(mat.ambient_color.shape == (10, 3)) |
| | self.assertTrue(mat.diffuse_color.shape == (10, 3)) |
| | self.assertTrue(mat.specular_color.shape == (10, 3)) |
| | self.assertTrue(mat.shininess.shape == (10,)) |
| |
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