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Fix Pytorch3D PnP test
Summary: EPnP fails the test when the number of points is below 6. As suggested, quadratic option is in theory to deal with as few as 4 points (so num_pts_thresh=3 is set). And when num_pts > num_pts_thresh=4, skip_q is False. To avoid bumping num_pts_thresh while passing all the original tests, check_output is set to False when num_pts < 6, similar to the logic in Line 123-127. It makes sure that the algo doesn't crash. Reviewed By: shapovalov Differential Revision: D37804438 fbshipit-source-id: 74576d63a9553e25e3ec344677edb6912b5f9354
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@ -54,9 +54,7 @@ class TestPerspectiveNPoints(TestCaseMixin, unittest.TestCase):
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R_quat = rotation_conversions.matrix_to_quaternion(R)
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num_pts = x_world.shape[-2]
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# quadratic part is more stable with fewer points
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num_pts_thresh = 5 if skip_q else 4
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if check_output and num_pts > num_pts_thresh:
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if check_output:
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assert_msg = (
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f"test_perspective_n_points assertion failure for "
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f"n_points={num_pts}, "
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@ -90,7 +88,12 @@ class TestPerspectiveNPoints(TestCaseMixin, unittest.TestCase):
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print("R_hat | R_gt\n", R_gt)
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print("T_hat | T_gt\n", T_gt)
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def _testcase_from_2d(self, y, print_stats, benchmark, skip_q=False):
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def _testcase_from_2d(
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self, y, print_stats, benchmark, skip_q=False, skip_check_thresh=5
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):
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"""
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In case num_pts < 6, EPnP gets unstable, so we check it doesn't crash
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"""
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x_cam, x_world, R, T = TestPerspectiveNPoints._generate_epnp_test_from_2d(
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y[None].repeat(16, 1, 1)
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)
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@ -107,7 +110,15 @@ class TestPerspectiveNPoints(TestCaseMixin, unittest.TestCase):
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return result
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self._run_and_print(x_world, y, R, T, print_stats, skip_q, check_output=True)
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self._run_and_print(
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x_world,
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y,
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R,
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T,
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print_stats,
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skip_q,
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check_output=True if y.shape[1] > skip_check_thresh else False,
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)
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# in the noisy case, there are no guarantees, so we check it doesn't crash
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if print_stats:
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