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Updates to cameras and rasterizer to infer camera type correctly
Summary: Small update to the cameras and rasterizer to correctly infer the type of camera (perspective vs orthographic). Reviewed By: jcjohnson Differential Revision: D26267225 fbshipit-source-id: a58ed3bc2ab25553d2a4307c734204c1d41b5176
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@ -42,15 +42,16 @@ class CamerasBase(TensorProperties):
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It defines methods that are common to all camera models:
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- `get_camera_center` that returns the optical center of the camera in
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world coordinates
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world coordinates
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- `get_world_to_view_transform` which returns a 3D transform from
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world coordinates to the camera view coordinates (R, T)
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world coordinates to the camera view coordinates (R, T)
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- `get_full_projection_transform` which composes the projection
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transform (P) with the world-to-view transform (R, T)
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transform (P) with the world-to-view transform (R, T)
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- `transform_points` which takes a set of input points in world coordinates and
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projects to NDC coordinates ranging from [-1, -1, znear] to [+1, +1, zfar].
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projects to NDC coordinates ranging from [-1, -1, znear] to [+1, +1, zfar].
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- `transform_points_screen` which takes a set of input points in world coordinates and
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projects them to the screen coordinates ranging from [0, 0, znear] to [W-1, H-1, zfar]
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projects them to the screen coordinates ranging from
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[0, 0, znear] to [W-1, H-1, zfar]
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For each new camera, one should implement the `get_projection_transform`
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routine that returns the mapping from camera view coordinates to NDC coordinates.
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@ -268,6 +269,12 @@ class CamerasBase(TensorProperties):
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other = cam_type(device=self.device)
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return super().clone(other)
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def is_perspective(self):
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raise NotImplementedError()
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def get_znear(self):
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return self.znear if hasattr(self, "znear") else None
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############################################################
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# Field of View Camera Classes #
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@ -534,6 +541,9 @@ class FoVPerspectiveCameras(CamerasBase):
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unprojection_transform = to_ndc_transform.inverse()
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return unprojection_transform.transform_points(xy_sdepth)
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def is_perspective(self):
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return True
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def OpenGLOrthographicCameras(
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znear=1.0,
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@ -752,6 +762,9 @@ class FoVOrthographicCameras(CamerasBase):
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unprojection_transform = to_ndc_transform.inverse()
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return unprojection_transform.transform_points(xy_sdepth)
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def is_perspective(self):
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return False
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############################################################
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# MultiView Camera Classes #
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@ -927,6 +940,9 @@ class PerspectiveCameras(CamerasBase):
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)
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return unprojection_transform.transform_points(xy_inv_depth)
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def is_perspective(self):
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return True
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def SfMOrthographicCameras(
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focal_length=1.0, principal_point=((0.0, 0.0),), R=_R, T=_T, device="cpu"
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@ -1086,6 +1102,9 @@ class OrthographicCameras(CamerasBase):
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unprojection_transform = to_ndc_transform.inverse()
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return unprojection_transform.transform_points(xy_depth)
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def is_perspective(self):
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return False
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################################################
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# Helper functions for cameras #
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@ -139,8 +139,13 @@ class MeshRasterizer(nn.Module):
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if clip_barycentric_coords is None:
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clip_barycentric_coords = raster_settings.blur_radius > 0.0
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# TODO(jcjohns): Should we try to set perspective_correct automatically
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# based on the type of the camera?
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# If not specified, infer perspective_correct from the camera
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cameras = kwargs.get("cameras", self.cameras)
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if raster_settings.perspective_correct is not None:
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perspective_correct = raster_settings.perspective_correct
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else:
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perspective_correct = cameras.is_perspective()
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pix_to_face, zbuf, bary_coords, dists = rasterize_meshes(
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meshes_screen,
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image_size=raster_settings.image_size,
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@ -148,7 +153,7 @@ class MeshRasterizer(nn.Module):
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faces_per_pixel=raster_settings.faces_per_pixel,
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bin_size=raster_settings.bin_size,
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max_faces_per_bin=raster_settings.max_faces_per_bin,
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perspective_correct=raster_settings.perspective_correct,
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perspective_correct=perspective_correct,
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clip_barycentric_coords=clip_barycentric_coords,
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cull_backfaces=raster_settings.cull_backfaces,
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)
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@ -794,6 +794,11 @@ class TestFoVPerspectiveProjection(TestCaseMixin, unittest.TestCase):
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new_points = cam.transform_points(points)
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self.assertClose(new_points, projected_points)
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def test_perspective_type(self):
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cam = FoVPerspectiveCameras(znear=1.0, zfar=10.0, fov=60.0)
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self.assertTrue(cam.is_perspective())
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self.assertEquals(cam.get_znear(), 1.0)
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############################################################
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# FoVOrthographic Camera #
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@ -885,6 +890,11 @@ class TestFoVOrthographicProjection(TestCaseMixin, unittest.TestCase):
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)
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self.assertClose(scale_grad, grad_scale)
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def test_perspective_type(self):
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cam = FoVOrthographicCameras(znear=1.0, zfar=10.0)
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self.assertFalse(cam.is_perspective())
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self.assertEquals(cam.get_znear(), 1.0)
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############################################################
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# Orthographic Camera #
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@ -937,6 +947,11 @@ class TestOrthographicProjection(TestCaseMixin, unittest.TestCase):
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v1 = P.transform_points(vertices)
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self.assertClose(v1, projected_verts)
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def test_perspective_type(self):
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cam = OrthographicCameras(focal_length=5.0, principal_point=((2.5, 2.5),))
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self.assertFalse(cam.is_perspective())
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self.assertEquals(cam.get_znear(), None)
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############################################################
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# Perspective Camera #
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@ -983,3 +998,8 @@ class TestPerspectiveProjection(TestCaseMixin, unittest.TestCase):
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v1 = P.transform_points(vertices)
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v2 = sfm_perspective_project_naive(vertices, fx=2.0, fy=2.0, p0x=2.5, p0y=3.5)
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self.assertClose(v1, v2, atol=1e-6)
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def test_perspective_type(self):
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cam = PerspectiveCameras(focal_length=5.0, principal_point=((2.5, 2.5),))
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self.assertTrue(cam.is_perspective())
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self.assertEquals(cam.get_znear(), None)
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@ -242,7 +242,10 @@ class TestRenderImplicit(TestCaseMixin, unittest.TestCase):
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rasterizer=MeshRasterizer(
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cameras=cameras_randomized,
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raster_settings=RasterizationSettings(
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image_size=image_size, blur_radius=1e-3, faces_per_pixel=10
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image_size=image_size,
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blur_radius=1e-3,
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faces_per_pixel=10,
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perspective_correct=False,
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),
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),
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shader=SoftPhongShader(
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@ -500,6 +500,7 @@ class TestRenderMeshes(TestCaseMixin, unittest.TestCase):
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blur_radius=np.log(1.0 / 1e-4 - 1.0) * blend_params.sigma,
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faces_per_pixel=100,
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clip_barycentric_coords=True,
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perspective_correct=False,
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)
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# Load reference image
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@ -844,7 +845,10 @@ class TestRenderMeshes(TestCaseMixin, unittest.TestCase):
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cameras = FoVPerspectiveCameras(device=device, R=R, T=T)
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raster_settings = RasterizationSettings(
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image_size=512, blur_radius=0.0, faces_per_pixel=1
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image_size=512,
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blur_radius=0.0,
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faces_per_pixel=1,
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perspective_correct=False,
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)
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lights = PointLights(
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@ -919,7 +923,10 @@ class TestRenderMeshes(TestCaseMixin, unittest.TestCase):
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R, T = look_at_view_transform(2.7, 0.0, 0.0)
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cameras = FoVPerspectiveCameras(device=device, R=R, T=T)
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raster_settings = RasterizationSettings(
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image_size=512, blur_radius=0.0, faces_per_pixel=1
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image_size=512,
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blur_radius=0.0,
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faces_per_pixel=1,
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perspective_correct=False,
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)
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# Init shader settings
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