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Llff & blender convention fix

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Summary: Images were coming out in the wrong format.

Reviewed By: shapovalov

Differential Revision: D37291278

fbshipit-source-id: c10871c37dd186982e7abf2071ac66ed583df2e6
This commit is contained in:
Jeremy Reizenstein 2022-06-22 05:54:54 -07:00 committed by Facebook GitHub Bot
parent 2e42ef793f
commit 731ea53c80
3 changed files with 4 additions and 2 deletions
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2
pytorch3d/implicitron/dataset/blender_dataset_map_provider.py
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@ -42,7 +42,7 @@ class BlenderDatasetMapProvider(SingleSceneDatasetMapProviderBase):
) )
H, W, focal = hwf H, W, focal = hwf
H, W = int(H), int(W) H, W = int(H), int(W)
images = torch.from_numpy(images) images = torch.from_numpy(images).permute(0, 3, 1, 2)[:, :3]
# pyre-ignore[16] # pyre-ignore[16]
self.poses = _interpret_blender_cameras(poses, H, W, focal) self.poses = _interpret_blender_cameras(poses, H, W, focal)

2
pytorch3d/implicitron/dataset/llff_dataset_map_provider.py
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@ -50,7 +50,7 @@ class LlffDatasetMapProvider(SingleSceneDatasetMapProviderBase):
i_split = (i_train, i_test, i_test) i_split = (i_train, i_test, i_test)
H, W, focal = hwf H, W, focal = hwf
H, W = int(H), int(W) H, W = int(H), int(W)
images = torch.from_numpy(images) images = torch.from_numpy(images).permute(0, 3, 1, 2)
poses = torch.from_numpy(poses) poses = torch.from_numpy(poses)
# pyre-ignore[16] # pyre-ignore[16]

2
tests/implicitron/test_data_llff.py
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@ -40,6 +40,7 @@ class TestDataLlff(TestCaseMixin, unittest.TestCase):
self.assertEqual(len(dataset), length) self.assertEqual(len(dataset), length)
# try getting a value # try getting a value
value = dataset[0] value = dataset[0]
self.assertEqual(value.image_rgb.shape, (3, 800, 800))
self.assertIsInstance(value, FrameData) self.assertIsInstance(value, FrameData)
def test_llff(self): def test_llff(self):
@ -62,6 +63,7 @@ class TestDataLlff(TestCaseMixin, unittest.TestCase):
value = dataset[0] value = dataset[0]
self.assertIsInstance(value, FrameData) self.assertIsInstance(value, FrameData)
self.assertEqual(value.frame_type, frame_type) self.assertEqual(value.frame_type, frame_type)
self.assertEqual(value.image_rgb.shape, (3, 378, 504))
self.assertEqual(len(dataset_map.test.get_eval_batches()), 3) self.assertEqual(len(dataset_map.test.get_eval_batches()), 3)
for batch in dataset_map.test.get_eval_batches(): for batch in dataset_map.test.get_eval_batches():