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fix ndc/screen problem in blender/llff (#39)

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Summary:
X-link: https://github.com/fairinternal/pytorch3d/pull/39

Blender and LLFF cameras were sending screen space focal length and principal point to a camera init function expecting NDC

Reviewed By: shapovalov

Differential Revision: D37788686

fbshipit-source-id: 2ddf7436248bc0d174eceb04c288b93858138582
This commit is contained in:
Jeremy Reizenstein
2022-07-19 10:38:13 -07:00
committed by Facebook GitHub Bot
parent 67840f8320
commit 38fd8380f7
5 changed files with 42 additions and 11 deletions
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21
tests/implicitron/test_data_llff.py
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@@ -7,6 +7,7 @@
import os
import unittest
import torch
from pytorch3d.implicitron.dataset.blender_dataset_map_provider import (
BlenderDatasetMapProvider,
)
@@ -37,6 +38,11 @@ class TestDataLlff(TestCaseMixin, unittest.TestCase):
object_name="lego",
)
dataset_map = provider.get_dataset_map()
known_matrix = torch.zeros(1, 4, 4)
known_matrix[0, 0, 0] = 2.7778
known_matrix[0, 1, 1] = 2.7778
known_matrix[0, 2, 3] = 1
known_matrix[0, 3, 2] = 1
for name, length in [("train", 100), ("val", 100), ("test", 200)]:
dataset = getattr(dataset_map, name)
@@ -48,6 +54,11 @@ class TestDataLlff(TestCaseMixin, unittest.TestCase):
# corner of image is background
self.assertEqual(value.fg_probability[0, 0, 0], 0)
self.assertEqual(value.fg_probability.max(), 1.0)
self.assertIsInstance(value.camera, PerspectiveCameras)
self.assertEqual(len(value.camera), 1)
self.assertIsNone(value.camera.K)
matrix = value.camera.get_projection_transform().get_matrix()
self.assertClose(matrix, known_matrix, atol=1e-4)
self.assertIsInstance(value, FrameData)
def test_llff(self):
@@ -60,6 +71,11 @@ class TestDataLlff(TestCaseMixin, unittest.TestCase):
object_name="fern",
)
dataset_map = provider.get_dataset_map()
known_matrix = torch.zeros(1, 4, 4)
known_matrix[0, 0, 0] = 2.1564
known_matrix[0, 1, 1] = 2.1564
known_matrix[0, 2, 3] = 1
known_matrix[0, 3, 2] = 1
for name, length, frame_type in [
("train", 17, "known"),
@@ -73,6 +89,11 @@ class TestDataLlff(TestCaseMixin, unittest.TestCase):
self.assertIsInstance(value, FrameData)
self.assertEqual(value.frame_type, frame_type)
self.assertEqual(value.image_rgb.shape, (3, 378, 504))
self.assertIsInstance(value.camera, PerspectiveCameras)
self.assertEqual(len(value.camera), 1)
self.assertIsNone(value.camera.K)
matrix = value.camera.get_projection_transform().get_matrix()
self.assertClose(matrix, known_matrix, atol=1e-4)
self.assertEqual(len(dataset_map.test.get_eval_batches()), 3)
for batch in dataset_map.test.get_eval_batches():