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Make transform_points_screen's with_xyflip configurable

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Summary: We'll need non-flipped screen coords in splatter.

Reviewed By: bottler

Differential Revision: D36337027

fbshipit-source-id: 897f88e8854bab215d2d0e502b25d15526ee86f1
This commit is contained in:
Krzysztof Chalupka 2022-05-16 18:23:51 -07:00 committed by Facebook GitHub Bot
parent 61e2b87019
commit 4372001981
2 changed files with 17 additions and 2 deletions
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9
pytorch3d/renderer/cameras.py
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@ -323,7 +323,7 @@ class CamerasBase(TensorProperties):
return world_to_ndc_transform.transform_points(points, eps=eps) return world_to_ndc_transform.transform_points(points, eps=eps)
def transform_points_screen( def transform_points_screen(
self, points, eps: Optional[float] = None, **kwargs self, points, eps: Optional[float] = None, with_xyflip: bool = True, **kwargs
) -> torch.Tensor: ) -> torch.Tensor:
""" """
Transforms points from PyTorch3D world/camera space to screen space. Transforms points from PyTorch3D world/camera space to screen space.
@ -341,6 +341,11 @@ class CamerasBase(TensorProperties):
stabilizes gradients since it leads to avoiding division stabilizes gradients since it leads to avoiding division
by excessively low numbers for points close to the by excessively low numbers for points close to the
camera plane. camera plane.
with_xyflip: If True, flip x and y directions. In world/camera/ndc coords,
+x points to the left and +y up. If with_xyflip is true, in screen
coords +x points right, and +y down, following the usual RGB image
convention. Warning: do not set to False unless you know what you're
doing!
Returns Returns
new_points: transformed points with the same shape as the input. new_points: transformed points with the same shape as the input.
@ -348,7 +353,7 @@ class CamerasBase(TensorProperties):
points_ndc = self.transform_points_ndc(points, eps=eps, **kwargs) points_ndc = self.transform_points_ndc(points, eps=eps, **kwargs)
image_size = kwargs.get("image_size", self.get_image_size()) image_size = kwargs.get("image_size", self.get_image_size())
return get_ndc_to_screen_transform( return get_ndc_to_screen_transform(
self, with_xyflip=True, image_size=image_size self, with_xyflip=with_xyflip, image_size=image_size
).transform_points(points_ndc, eps=eps) ).transform_points(points_ndc, eps=eps)
def clone(self): def clone(self):

10
tests/test_camera_pixels.py
View File

@ -204,6 +204,9 @@ class TestPixels(TestCaseMixin, unittest.TestCase):
for cameras in (data.camera_ndc, data.camera_screen): for cameras in (data.camera_ndc, data.camera_screen):
ndc_points = cameras.transform_points_ndc(points) ndc_points = cameras.transform_points_ndc(points)
screen_points = cameras.transform_points_screen(points) screen_points = cameras.transform_points_screen(points)
screen_points_without_xyflip = cameras.transform_points_screen(
points, with_xyflip=False
)
camera_points = cameras.transform_points(points) camera_points = cameras.transform_points(points)
for batch_idx in range(2): for batch_idx in range(2):
# NDC space agrees with the original # NDC space agrees with the original
@ -214,6 +217,13 @@ class TestPixels(TestCaseMixin, unittest.TestCase):
torch.tensor([data.x + 0.5, data.y + 0.5, 1.0]), torch.tensor([data.x + 0.5, data.y + 0.5, 1.0]),
atol=1e-5, atol=1e-5,
) )
# Screen coords without xyflip should have x, y that negate the non-
# flipped values, and unchanged z.
self.assertClose(
screen_points_without_xyflip[batch_idx][0],
torch.tensor([-(data.x + 0.5), -(data.y + 0.5), 1.0]),
atol=1e-5,
)
# Second point in screen space is the center of the screen # Second point in screen space is the center of the screen
self.assertClose( self.assertClose(
screen_points[batch_idx][1], screen_points[batch_idx][1],