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316b77782e
Summary: adds `corresponding_cameras_alignment` function that estimates a similarity transformation between two sets of cameras. The function is essential for computing camera errors in SfM pipelines. ``` Benchmark Avg Time(μs) Peak Time(μs) Iterations -------------------------------------------------------------------------------- CORRESPONDING_CAMERAS_ALIGNMENT_10_centers_False 32219 36211 16 CORRESPONDING_CAMERAS_ALIGNMENT_10_centers_True 32429 36063 16 CORRESPONDING_CAMERAS_ALIGNMENT_10_extrinsics_False 5548 8782 91 CORRESPONDING_CAMERAS_ALIGNMENT_10_extrinsics_True 6153 9752 82 CORRESPONDING_CAMERAS_ALIGNMENT_100_centers_False 33344 40398 16 CORRESPONDING_CAMERAS_ALIGNMENT_100_centers_True 34528 37095 15 CORRESPONDING_CAMERAS_ALIGNMENT_100_extrinsics_False 5576 7187 90 CORRESPONDING_CAMERAS_ALIGNMENT_100_extrinsics_True 6256 9166 80 CORRESPONDING_CAMERAS_ALIGNMENT_1000_centers_False 32020 37247 16 CORRESPONDING_CAMERAS_ALIGNMENT_1000_centers_True 32776 37644 16 CORRESPONDING_CAMERAS_ALIGNMENT_1000_extrinsics_False 5336 8795 94 CORRESPONDING_CAMERAS_ALIGNMENT_1000_extrinsics_True 6266 9929 80 -------------------------------------------------------------------------------- ``` Reviewed By: shapovalov Differential Revision: D22946415 fbshipit-source-id: 8caae7ee365b304d8aa1f8133cf0dd92c35bc0dd
24 lines
683 B
Python
24 lines
683 B
Python
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
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import itertools
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from fvcore.common.benchmark import benchmark
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from test_cameras_alignment import TestCamerasAlignment
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def bm_cameras_alignment() -> None:
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case_grid = {
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"batch_size": [10, 100, 1000],
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"mode": ["centers", "extrinsics"],
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"estimate_scale": [False, True],
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}
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test_cases = itertools.product(*case_grid.values())
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kwargs_list = [dict(zip(case_grid.keys(), case)) for case in test_cases]
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benchmark(
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TestCamerasAlignment.corresponding_cameras_alignment,
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"CORRESPONDING_CAMERAS_ALIGNMENT",
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kwargs_list,
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warmup_iters=1,
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)
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