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Address black + isort fbsource linter warnings

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Summary: Address black + isort fbsource linter warnings from D20558374 (previous diff)

Reviewed By: nikhilaravi

Differential Revision: D20558373

fbshipit-source-id: d3607de4a01fb24c0d5269634563a7914bddf1c8
This commit is contained in:
Patrick Labatut
2020-03-29 14:46:33 -07:00
committed by Facebook GitHub Bot
parent eb512ffde3
commit d57daa6f85
110 changed files with 705 additions and 1850 deletions
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55
tests/test_cameras.py
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@@ -26,10 +26,11 @@
# SOFTWARE.
import math
import numpy as np
import unittest
import torch
import numpy as np
import torch
from common_testing import TestCaseMixin
from pytorch3d.renderer.cameras import (
OpenGLOrthographicCameras,
OpenGLPerspectiveCameras,
@@ -43,8 +44,6 @@ from pytorch3d.renderer.cameras import (
from pytorch3d.transforms import Transform3d
from pytorch3d.transforms.so3 import so3_exponential_map
from common_testing import TestCaseMixin
# Naive function adapted from SoftRasterizer for test purposes.
def perspective_project_naive(points, fov=60.0):
@@ -58,9 +57,7 @@ def perspective_project_naive(points, fov=60.0):
coordinate (no z renormalization)
"""
device = points.device
halfFov = torch.tensor(
(fov / 2) / 180 * np.pi, dtype=torch.float32, device=device
)
halfFov = torch.tensor((fov / 2) / 180 * np.pi, dtype=torch.float32, device=device)
scale = torch.tan(halfFov[None])
scale = scale[:, None]
z = points[:, :, 2]
@@ -150,9 +147,9 @@ class TestCameraHelpers(TestCaseMixin, unittest.TestCase):
dist = 2.7
elev = 90.0
azim = 0.0
expected_position = torch.tensor(
[0.0, 2.7, 0.0], dtype=torch.float32
).view(1, 3)
expected_position = torch.tensor([0.0, 2.7, 0.0], dtype=torch.float32).view(
1, 3
)
position = camera_position_from_spherical_angles(dist, elev, azim)
self.assertClose(position, expected_position, atol=2e-7)
@@ -171,9 +168,9 @@ class TestCameraHelpers(TestCaseMixin, unittest.TestCase):
dist = torch.tensor(2.7)
elev = torch.tensor(0.0)
azim = torch.tensor(90.0)
expected_position = torch.tensor(
[2.7, 0.0, 0.0], dtype=torch.float32
).view(1, 3)
expected_position = torch.tensor([2.7, 0.0, 0.0], dtype=torch.float32).view(
1, 3
)
position = camera_position_from_spherical_angles(dist, elev, azim)
self.assertClose(position, expected_position, atol=2e-7)
@@ -181,9 +178,9 @@ class TestCameraHelpers(TestCaseMixin, unittest.TestCase):
dist = 2.7
elev = torch.tensor(0.0)
azim = 90.0
expected_position = torch.tensor(
[2.7, 0.0, 0.0], dtype=torch.float32
).view(1, 3)
expected_position = torch.tensor([2.7, 0.0, 0.0], dtype=torch.float32).view(
1, 3
)
position = camera_position_from_spherical_angles(dist, elev, azim)
self.assertClose(position, expected_position, atol=2e-7)
@@ -228,8 +225,7 @@ class TestCameraHelpers(TestCaseMixin, unittest.TestCase):
elev = torch.tensor([0.0])
azim = torch.tensor([90.0])
expected_position = torch.tensor(
[[2.0, 0.0, 0.0], [3.0, 0.0, 0.0], [5.0, 0.0, 0.0]],
dtype=torch.float32,
[[2.0, 0.0, 0.0], [3.0, 0.0, 0.0], [5.0, 0.0, 0.0]], dtype=torch.float32
)
position = camera_position_from_spherical_angles(dist, elev, azim)
self.assertClose(position, expected_position, atol=3e-7)
@@ -239,8 +235,7 @@ class TestCameraHelpers(TestCaseMixin, unittest.TestCase):
elev = 0.0
azim = torch.tensor(90.0)
expected_position = torch.tensor(
[[2.0, 0.0, 0.0], [3.0, 0.0, 0.0], [5.0, 0.0, 0.0]],
dtype=torch.float32,
[[2.0, 0.0, 0.0], [3.0, 0.0, 0.0], [5.0, 0.0, 0.0]], dtype=torch.float32
)
position = camera_position_from_spherical_angles(dist, elev, azim)
self.assertClose(position, expected_position, atol=3e-7)
@@ -364,9 +359,7 @@ class TestCameraHelpers(TestCaseMixin, unittest.TestCase):
):
cam = cam_type(R=R, T=T)
RT_class = cam.get_world_to_view_transform()
self.assertTrue(
torch.allclose(RT.get_matrix(), RT_class.get_matrix())
)
self.assertTrue(torch.allclose(RT.get_matrix(), RT_class.get_matrix()))
self.assertTrue(isinstance(RT, Transform3d))
@@ -539,9 +532,7 @@ class TestOpenGLOrthographicProjection(TestCaseMixin, unittest.TestCase):
# applying the scale puts the z coordinate at the far clipping plane
# so the z is mapped to 1.0
projected_verts = torch.tensor([2, 1, 1], dtype=torch.float32)
cameras = OpenGLOrthographicCameras(
znear=1.0, zfar=10.0, scale_xyz=scale
)
cameras = OpenGLOrthographicCameras(znear=1.0, zfar=10.0, scale_xyz=scale)
P = cameras.get_projection_transform()
v1 = P.transform_points(vertices)
v2 = orthographic_project_naive(vertices, scale)
@@ -578,9 +569,7 @@ class TestOpenGLOrthographicProjection(TestCaseMixin, unittest.TestCase):
far = torch.tensor([10.0])
near = 1.0
scale = torch.tensor([[1.0, 1.0, 1.0]], requires_grad=True)
cameras = OpenGLOrthographicCameras(
znear=near, zfar=far, scale_xyz=scale
)
cameras = OpenGLOrthographicCameras(znear=near, zfar=far, scale_xyz=scale)
P = cameras.get_projection_transform()
vertices = torch.tensor([1.0, 2.0, 10.0], dtype=torch.float32)
vertices_batch = vertices[None, None, :]
@@ -683,15 +672,11 @@ class TestSfMPerspectiveProjection(TestCaseMixin, unittest.TestCase):
self.assertClose(v3[..., :2], v2[..., :2])
def test_perspective_kwargs(self):
cameras = SfMPerspectiveCameras(
focal_length=5.0, principal_point=((2.5, 2.5),)
)
cameras = SfMPerspectiveCameras(focal_length=5.0, principal_point=((2.5, 2.5),))
P = cameras.get_projection_transform(
focal_length=2.0, principal_point=((2.5, 3.5),)
)
vertices = torch.randn([3, 4, 3], dtype=torch.float32)
v1 = P.transform_points(vertices)
v2 = sfm_perspective_project_naive(
vertices, fx=2.0, fy=2.0, p0x=2.5, p0y=3.5
)
v2 = sfm_perspective_project_naive(vertices, fx=2.0, fy=2.0, p0x=2.5, p0y=3.5)
self.assertClose(v1, v2)